Power use cost analysis device

Abstract

To provide a power use cost analysis device, method, and program for analyzing a power use cost of a power consumer in a power supply and demand system based on a billing scheme in which a billing amount to the power consumer determined in accordance with a power transaction market price that fluctuates depending on a power supply possible amount that changes according to the weather is determined in advance.SOLUTION: A power use cost analysis device includes: a weather data acquisition unit Q; a conversion rule holding unit R that holds rules for converting weather data into representative weather information; a maximum demand power information holding unit A; a maximum power use amount information holding unit B that holds the maximum daily power use amount and information associated with the acquired representative weather information; a monthly power use amount information holding unit C that holds the monthly power use amount and information associated with the acquired representative weather information; a total monthly power use amount information holding unit D; a total monthly power charge information holding unit E; and an information output unit F for outputting one or more pieces of the information.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an electric power usage cost analysis device capable of outputting weather information at the time of electric power usage of an electric power consumer, which is a consumer who purchases and uses electric power, and one or more of various information showing the electric power usage status and cost information in order to reduce the cost of electric power usage of the electric power consumer who purchases and uses electric power and to reduce the amount of electric power usage in consideration of the environment. Also, the above "any one or more" may be changed to "any two or more". In relation to this, the invention also includes an invention relating to a method of operating the device which is a computer and a program which can be read and operated by the device which is a computer. [Background technology]

[0002] Conventionally, the amount of electricity used and the electricity charges associated with the use have generally been understood by looking at the contents of an electricity bill periodically sent by an electricity retailer or by using an online electricity bill calculation simulation service provided by the electricity retailer. An electricity bill displays, for example, the amount of electricity used for each time period in a specified past period (e.g., one month from the last meter reading date to the day before the meter reading date of the following month), the total amount of electricity used during the same period, and the billed amount corresponding to the total amount of electricity used. In addition, in an online electricity bill calculation simulation service, information on the electricity charges to be billed is displayed by inputting the contract type and the amount of electricity used. By using these services, an electricity consumer who purchases electricity from an electricity retailer can understand the amount of electricity used and the electricity charges based on the respective pieces of information.

[0003] The power saving sheet described in Patent Document 1 presents the maximum demand value during the basic electricity charge calculation period (i.e., one year) for each electricity consumer, a candidate value smaller than the maximum demand value, and the estimated electricity charge amount at that time to the electricity consumer, and can show how much the electricity charge can be reduced if the current maximum demand value is lowered. Also, by using information on the business site during the basic electricity charge calculation period (information on business hours, weather, staff ID, sales, etc.) in addition to the demand value data, it is possible to recall what kind of day each detection date and time was, analyze the contents of events that occurred there, and take more detailed power saving measures.

[0004] The energy saving behavior support system described in Patent Document 2 visualizes the correlation between the energy consumption data and temperature data of a standard energy consumer and a target energy consumer who receive supply from the same electricity retailer in a graph and compares them to raise awareness. Examples of comparing electricity consumption results for 30 days per season, and a number of specific days including the specified day with the corresponding same days for the past year or multiple years are also mentioned. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent Publication No. 2014-176277

[0006] [Patent Document 2] Patent Publication No. 2008-225826 Summary of the Invention [Problem to be solved by the invention]

[0007] The invention described in Patent Document 1 aims to lower the basic charge portion of the electricity fee, which is determined by the maximum demand value, and does not mention reducing electricity fees other than the basic charge (especially the metered portion of the electricity fee, which changes according to the amount of electricity used). Therefore, in a billing system in which the amount charged to electricity consumers is determined in advance in conjunction with the electricity trading market price, which fluctuates according to the amount of electricity that can be supplied, which changes according to the weather, there was a problem that the billing includes more than the basic charge (e.g. the metered portion), and it is not possible to reduce the electricity fee, which is the cost of electricity usage, or to analyze the amount of electricity used and develop improvements related to electricity usage based on the analysis.

[0008] The invention described in Patent Document 2 compares standard energy consumption data obtained by calculating the average energy consumption of a sample of multiple energy consumers at the same temperature for each temperature with the target energy consumer, but does not compare the data with the energy consumption tendency of the target energy consumer himself. In addition, the only weather factor considered was temperature, and other factors were not considered.

[0009] In the present invention, the system is based on a billing system in which the amount of electricity charged to an electricity consumer is determined in advance in conjunction with the electricity trading market price, which varies according to the amount of electricity that can be supplied, which varies according to the weather. The system provides electricity consumers with the following information: (1) maximum demand electricity information for a demand time period during a certain month; (2) maximum electricity usage information for a day included in the month; (3) monthly electricity usage information for the month; and (4) one or more of the total electricity usage during a specified active time period during the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays, as well as information regarding the weather for the month or the quarter including that month (one or more of temperature, humidity, wind speed, sunny, cloudy, rainy, and sunshine hours). The present invention provides an electric power usage cost analysis device that outputs one or more of (1) to (5) (or "any two or more") of the following: (1) total monthly electricity usage information, which is information relating to the amount of electricity consumed by an electric power consumer, and (5) total monthly electricity charge information, which indicates the total electricity charge for the month; and (6) total monthly electricity charge information, which indicates the amount of electricity consumed by an electric power consumer for the month. The present invention aims to provide an electric power usage cost analysis device that can indicate when an electric power consumer consumed the most electricity in relation to the weather or how much an electric power consumer has spent on electricity, thereby reducing the amount of charges that are determined in conjunction with the electric power trading market price, which fluctuates according to the amount of available electric power supply, which changes according to the weather; and can motivate and encourage analysis of electric power usage and the formulation of improvements regarding electric power usage based on the analysis. [Means for solving the problem]

[0010] In order to solve the above problems related to the power usage cost analysis device, the present application provides, as a first invention, An apparatus for analyzing the electricity usage costs of an electricity consumer in an electricity supply and demand system based on a billing system in which a charge amount for an electricity consumer is determined in advance in conjunction with an electricity trading market price that fluctuates according to an available amount of electricity that changes according to weather, the apparatus comprising: A weather data acquisition unit (Q) that acquires weather data at a predetermined time interval, the weather data being one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours; a conversion rule storage unit (R) for storing conversion rules for converting the acquired weather data, such as temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, into representative weather information, which is information related to representative weather of any one or more of the demand time slots, days, weeks, months, and quarters (demand time slots, days, weeks, months, and quarters are time lengths equal to or longer than the predetermined time intervals; the same applies below) in which the weather data was observed; a maximum demand power information storage unit (A) for storing maximum demand power information, which is information obtained by acquiring and associating a monthly maximum demand power, a demand time period in which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather of the demand time period or / a day including the demand time period (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours); a maximum electricity usage information storage unit (B) for storing maximum electricity usage information that is information obtained by acquiring representative weather information (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) regarding the maximum electricity usage for one day included in the month based on the acquired weather data and the stored conversion rule and associating the representative weather information with the weather information for the one day or / the week including the one day based on the acquired weather data and the stored conversion rule; a monthly electricity usage information storage unit (C) for storing monthly electricity usage information that is information obtained by acquiring representative weather information (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) regarding the weather of the month or a quarter including the month based on the electricity usage for the month, the acquired weather data, and the stored conversion rule, and associating the information with the representative weather information; a total monthly electricity usage information storage unit (D) for storing total monthly electricity usage information that is information obtained by acquiring and associating representative weather information (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) regarding the weather of the month or the quarter including the month, which is acquired based on the acquired weather data and the stored conversion rule, with one or more of the total electricity usage during a predetermined active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays; and one or more of the following: a total monthly electricity charge information storage unit (E) for storing total monthly electricity charge information indicating the total electricity charge for the month; An information output unit (F) for outputting any one or more of the information; The present invention provides an electric power usage cost analysis device having the following features.

[0011] As the second invention, based on the first invention, The present invention provides an electric power usage cost analysis device, which further includes a monthly adaptive electricity usage charge information storage unit (G) for storing adaptive electricity usage charge plan information, which is information indicating a charge plan for charges that change according to the amount of electricity usage, and monthly adaptive electricity usage charge information, which is information indicating the monthly adaptive electricity usage charge fee.

[0012] As a third invention, based on either the first invention or the second invention, The power usage cost analysis device further includes a comparison unit (H) for comparing at least one of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the stored information for a different day, month, year, or period corresponding to the stored information.

[0013] As the fourth invention, based on the third invention, The comparison unit (H) provides an electric power usage cost analysis device having a superiority / inferiority judgment means (J) for each specified demand time period that makes a superiority / inferiority judgment, which is a judgment showing the superiority / inferiority of the same specified demand time period (compared to the previous day, week, month, last year, etc.) from the perspective of power consumption efficiency for each electric power consumer.

[0014] As a fifth invention, based on either the third invention or the fourth invention, The comparison unit (H) provides an electricity usage cost analysis device having an electricity consumer superiority / inferiority determination means (K) for making a superiority / inferiority determination, which is a determination showing superiority / inferiority between different electricity consumer from the standpoint of electricity consumption efficiency for each specified demand time period.

[0015] As a sixth invention, based on any one of the first to fifth inventions, The present invention provides an electricity usage cost analysis device that further has an electricity consumption tendency information storage unit (L) that stores electricity consumption tendency information, which is information indicating the electricity consumption tendency of each electricity consumer, when the electricity consumption tendency of the electricity consumer changes depending on the weather.

[0016] As a seventh invention, based on any one of the third to fifth inventions, or the sixth invention based on any one of the third to fifth inventions, The comparison unit (H) further includes a demand time slot maximum demand power occurrence frequency acquisition means (M) for acquiring the frequency at which maximum demand power occurs in a day for each demand time slot.

[0017] As an eighth invention, based on any one of the third to fifth inventions or the seventh invention, or the sixth invention based on any one of the third to fifth inventions, The comparison unit (H) further includes a temperature-specific maximum power demand acquisition means (N) for acquiring maximum power demand per temperature, which is the maximum power demand per demand time slot for each temperature.

[0018] As a ninth invention, based on any one of the first to eighth inventions, A future weather information acquisition unit (O) for acquiring future weather information, which is information indicating future weather including at least temperature; The present invention provides an electricity usage cost analysis device further having a future maximum electricity demand predicted value acquisition unit (P) that acquires a future maximum electricity demand predicted value, which is a predicted value of maximum electricity demand at a future point in time, from the temperature included in the acquired future weather information.

[0019] Furthermore, there are also provided a method for operating the power usage cost analysis device, which is the computer of the first to ninth aspects of the present invention, and a program for executing the method. The program may be recorded on a recording medium. Effect of the Invention

[0020] The electricity usage cost analysis device of the present invention having the above-mentioned configuration can output one or more of monthly maximum demand electricity information, maximum electricity usage information, monthly electricity usage information, total monthly electricity usage information, or total monthly electricity bill information for the above-mentioned five types of information, thereby showing when the electricity consumer himself consumes the most electricity in relation to the weather, or showing how much electricity he or she has spent, thereby motivating and promoting a comprehensive reduction in electricity consumption itself and a comprehensive reduction in the billing amount which is determined in conjunction with the electricity trading market price which fluctuates according to the available electricity supply amount which changes according to the weather. [Brief description of the drawings]

[0021] The numbers in [ ] after the brief description of each figure indicate the main paragraph numbers of the figure description or the description using the figure. [Figure 1] Functional block diagram of the invention according to embodiment 1 [0058-0113] [Diagram 2] Operational flow chart of the invention according to the first embodiment [0124-0125] [Diagram 3] Hardware diagram of the invention according to embodiment 1 [0126-0131] [Figure 4] Functional block diagram of the invention according to embodiment 2 [0134-0139] [Diagram 5] Operational flow chart of the invention according to the second embodiment [0140-0141] [Figure 6] Hardware diagram of the invention according to embodiment 2 [0142-0147] [Figure 7] Functional block diagram of the invention according to embodiment 3 [0150-0158] [Figure 8] Operational flow chart of the invention according to the third embodiment [0159-0160] [Figure 9] Hardware diagram of the invention according to embodiment 3 [0161-0166] [Figure 10] Functional block diagram of the invention according to embodiment 4 [0169-0176] [Figure 11] Operational flow chart of the invention according to the fourth embodiment [0177-0178] [Figure 12] Hardware diagram of the invention according to embodiment 4 [0179-0184] [Figure 13] Functional block diagram of the invention according to embodiment 5 [0187-0191] [Figure 14] Operational flow chart of the invention according to the fifth embodiment [0192-0193] [Figure 15] Hardware diagram of the invention according to embodiment 5 [0194-0199] [Figure 16] Functional block diagram of the invention according to embodiment 6 [0202-0207] [Figure 17] Operational flow chart of the invention according to the sixth embodiment [0208-0209] [Figure 18] Hardware diagram of the invention according to embodiment 6 [0210-0215] [Figure 19] Functional block diagram of the invention according to embodiment 7 [0218-0223] [Figure 20] Operational flow chart of the invention according to the seventh embodiment [0224-0225] [Figure 21] Hardware diagram of the invention according to embodiment 7 [0226-0231] [Figure 22] Functional block diagram of the invention according to embodiment 8 [0234-0241] [Diagram 23] Operational flow chart of the invention according to embodiment 8 [0242-0243] [Figure 24] Hardware diagram of the invention according to embodiment 8 [0244-0249] [Diagram 25] Functional block diagram of the invention according to embodiment 9 [0252-0259] [Figure 26] Operational flow chart of the invention according to embodiment 9 [0260-0261] [Figure 27] Hardware diagram of the invention according to embodiment 9 [0262-0267] [Figure 28]Schematic diagram of the overall configuration of the device of the present invention

[0030] [Figure 29] Example of hardware configuration of the device of the present invention: [Diagram 30] Example 1 of a screen when analyzing electricity usage costs using the device of the present invention [0117-0118] [Diagram 31] Example 2 of a screen showing power usage cost analysis using the device of the present invention [0119-0123] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0022] <Prerequisites for the explanation of all embodiments> <Hardware that can constitute the present invention> The present invention is, in principle, an invention that utilizes a computer, but at least a part of it is realized by software, hardware, or a combination of software and hardware. In this case, the software uses hardware resources to perform various calculations and realizes various functions through the required data and information. It can be said that information processing by software is specifically realized using hardware resources.

[0023] Hardware that realizes all or part of the constituent elements of the present invention is composed of the basic components of a computer, such as a CPU, memory, a bus, an input / output device, various peripheral devices, a user interface, etc. The various peripheral devices may include a storage device, an internet interface, an internet device, a LAN device, a Wifi (registered trademark) device, a display, a display interface, a keyboard, a mouse, a speaker, a microphone, a camera, a video, a television, a CD device, a DVD device, a Blu-ray device, a USB memory, a USB memory interface, a removable hard disk, a general hard disk, a projector device, an SSD, a telephone, a fax, a copy machine, a printer, a movie editing device, various sensor devices, etc.

[0024] In addition, the device does not necessarily have to be made up of a single housing, but may be made up of multiple housings connected by communication. The communication may be a LAN, a WAN, Wifi (registered trademark), Bluetooth (registered trademark), infrared communication, ultrasonic communication, near field communication (NFC), or a mobile phone network, and some of the devices may be installed across national borders.

[0025] <Fulfillment of the Laws of Nature in All Embodiments of the Present Invention>

[0026] The present invention functions through the cooperation of a computer and software. In the present invention, weather information is obtained from an electricity consumer via a network such as the Internet, and information relating to the electricity consumer's past month or the maximum daily electricity usage included in that month, total electricity usage for a specific period of the month, etc., which are stored in the user's computer, is associated with the weather information, and the total electricity bill for the month is output. Since the invention includes processing unique to ICT, such as exchanging the various information as data and searching on a computer, it is a so-called business model patent. From this perspective, the present invention is considered to utilize a law of nature if resources such as a computer are judged based on the matters described in the claims and specification, and the technical common sense related to those matters.

[0027] <Applicant's understanding of the significance of utilizing the laws of nature required by patent law>

[0028] The use of the law of nature required by the Patent Law is required to ensure that the invention can be used industrially from the viewpoint that the invention must have industrial applicability and contribute to the development of industry based on the purpose of the law. In other words, it is required that the invention be industrially useful, that is, the effect of the invention declared at the time of application can be reproduced with a certain degree of certainty by implementing the invention. From this perspective, the use of the law of nature is interpreted as the function of each of the invention-specific matters (invention constituent elements) that constitute the invention to achieve the effect of the invention is achieved by utilizing the law of nature. Furthermore, the effect of the invention is sufficient if it can provide a certain usefulness to the user who uses the invention, and should not be viewed from the perspective of how the user feels or thinks about the usefulness. Therefore, even if the effect that electricity consumers and the manager and operator of the device of the present invention obtain from this electricity usage cost analysis device is a psychological effect (such as a sense of security), the effect itself is not a subject matter for determining whether or not the required use of the law of nature is available.

[0029] <Hardware configuration>

[0030] An outline of the overall configuration of this device is shown in Fig. 28. A server device (2851) on which the program of this device runs, a high-voltage substation equipment monitoring device A (2853A) that monitors the high-voltage substation equipment from which power consumer A receives high-voltage power, a high-voltage substation equipment A (2854A) that receives high-voltage power, a PC (2855A) used by power consumer A, a high-voltage substation equipment monitoring device B (2853B) that monitors the high-voltage substation equipment from which power consumer B receives high-voltage power, a high-voltage substation equipment B (2854B) that receives high-voltage power, a PC (2855B) used by power consumer B, a smart meter (2853C) from which power consumer C, a general household, receives low-voltage power, and a smartphone (2855C) used by power consumer C are connected by wire or wirelessly (such as Wifi (registered trademark) or a mobile phone network) via an Internet line (2850) (which may be another commercial line or a dedicated line). Although only one server device (2851) is shown in FIG. 28, it may be configured with multiple devices. There may be a person (manager / operator (2852) in FIG. 28) who manages and / or operates the server device of the device of the present invention. The server device can be accessed via an information terminal (such as a PC) that can connect to the Internet, or the server device can be managed and / or operated by an information terminal directly connected to the server device. Alternatively, the server device may be configured as an application that runs on an information terminal such as a PC or smartphone used by each power consumer without a server device. A high-voltage substation equipment monitoring device that monitors high-voltage substation equipment may be integrated with the high-voltage substation equipment.

[0031] Fig. 29 is a diagram showing an example of the hardware configuration of an electric power usage cost analysis device constituting an electric power usage cost analysis device in each embodiment of the present invention. Taking an example in which the configuration is similar to that of a PC, the hardware configuration of the electric power usage cost analysis device in this embodiment will be described with reference to Fig. 29. Note that the server device shown in Fig. 28 may also be configured similar to that of a PC, and as the description of the hardware configuration is the same as that given below, a description thereof will be omitted.

[0032] As shown in this figure, the computer is composed of a chipset, a CPU, a non-volatile memory, a main memory, various buses, a BIOS (or UEFI), various peripheral devices such as USB and LAN, an interface for connecting to a communication line, a real-time clock, etc., which are configured on a motherboard. These operate in cooperation with an operating system, a device driver (for various interfaces such as USB, cameras, microphones, speakers or headphones, displays, etc. for incorporating various devices), various programs, etc. The various programs and various data constituting the present invention are configured to efficiently utilize these hardware resources to execute various processes using input signals such as a keyboard and a mouse connected via a USB terminal (or PS / 2 port). The computer is connected to an Internet line through a LAN terminal or the like. The computer may be connected to the Internet line using WiFi (registered trademark) or via a mobile phone line network.

[0033] The following describes examples of main components constituting a computer as hardware, although the present invention is not limited to these examples. Chipset

[0034] A "chipset" is a set of large-scale integrated circuits (LSIs) that are mounted on the motherboard of a computer and integrate a communication function between the external bus of the CPU and a standard bus that connects non-volatile memory and peripheral devices mounted on the motherboard, that is, a bridge function. In the past, it was a two-chip configuration consisting of a north bridge that was connected to the CPU and performed processing that required high speed, such as between the main memory and a graphics card equipped with a chip (GPU) for graphics processing, and a south bridge that was connected to the north bridge and performed processing between a relatively slow interface. In recent years, the north bridge function has been integrated into the CPU, and only the previous south bridge remains, but it is still called a chipset. In this specification, we will explain the single-chip configuration of only the south bridge with the north bridge function built into the CPU. The effects of the present invention will not change whether it is a two-chip configuration of a north bridge and a south bridge as described above, or if there is no chipset with the south bridge function integrated into the CPU.

[0035] (South Bridge) When the chipset is a single chip configuration, the south bridge is responsible for I / O functions such as PCI Express interface (slot), SATA (Serial ATA) or eSATA interface, USB interface, LAN (Ethernet) interface, real-time clock, and sound functions. When the chipset is a single chip configuration, it is the chip that controls interfaces such as displays, external connections such as USB / LAN terminals, SATA for connecting to HDDs and SSDs, and PCI Express, and is connected to the CPU via a point-to-point hardware interface (for example, DMI: Direct Media Interface). Some chips support RAID (Redundant Arrays of Inexpensive Disks: a technology that recognizes and displays multiple HDDs as a single drive) for non-volatile memory (such as HDDs). In addition, to support devices that are rarely used in recent years and where high-speed operation is not required or possible, such as PS / 2 ports, floppy disk drives, serial ports such as RS-232C, parallel ports such as IEEE1284 for printers, and ISA buses, a separate LSI called a super I / O chip is used, which connects to the south bridge via a low pin count bus.

[0036] <Bus> There are parallel buses and serial buses. A parallel bus prepares signal lines for the number of bits and transmits data in synchronization with a clock. A dedicated line for the clock signal is set up in parallel with the data line, and synchronizes data demodulation on the receiving side. A serial bus transfers data one bit at a time. A bus is used to connect peripheral devices and various control units on the motherboard to the CPU (MPU). The internal bus connects the CPU core to cache memory and other internal memory, while the external bus connects the CPU to memory outside the CPU. The external bus that connects the memory controller built into the CPU to the main memory is a 64-bit parallel bus in the case of a DDR4 standard that uses DDR4-SDRAM (Double-Data-Rate4 Synchronous Dynamic Random Access Memory). For example, if the DDR4-3200 memory standard is supported, the bandwidth is 3200MHz maximum memory operating frequency x 64 (bit) bus width ÷ 8 (bit → byte conversion) = 25.6 (GB / s). The connection between the CPU and the south bridge is a point-to-point connection such as DMI (Direct Media Interface) as mentioned above. External expansion buses such as PCI Express and SATA are connected by chipsets. Parallel buses include GPIB, IDE / (parallel)ATA, SCSI, PCI, etc. A serial bus transfers data one bit at a time. Because there is a limit to how fast it can be, the improved version of PCI, PCI Express, uses point-to-point wiring and a serial transfer method. USB and SATA also transfer data serially.

[0037] CPU

[0038] The CPU reads a sequence of instructions called a program in main memory in order, interprets and executes them, and outputs information consisting of signals to the main memory. The CPU functions as the center of calculations within a computer. The CPU is composed of the CPU core, which is the center of calculations, and its peripheral parts, and includes registers, cache memory (primary, secondary, tertiary), an internal bus that connects the cache memory to the CPU core, a memory controller, a timer, and an interface with the connection bus to the south bridge. If the CPU has an integrated graphics function (GPU), it also includes a graphics interface and an internal bus that connects to the CPU core. If an external graphics board is used with a CPU with a built-in GPU, it is connected to the graphics interface (PCI Express, etc.) built into the CPU. Note that a single CPU (chip) may have multiple CPU cores. The embodiment is described as a two-core type, but is not limited to this. Also, a configuration may be provided with multiple CPU chips. A program may also be built into the CPU.

[0039] <Non-volatile memory>

[0040] (HDD)

[0041] The basic structure of a hard disk drive consists of a magnetic disk, a magnetic head, and an arm on which the magnetic head is mounted. External interfaces include SATA (previously ATA) and SAS (Serial Attached SCSI, previously SCSI). HDD interfaces are broadly divided into the ATA and SCSI types mentioned above. The ATA type is a method of sending data unilaterally to the physically connected device, and since it relies on the BIOS (or UEFI) on the motherboard, it constantly requires CPU processing time. The SCSI type is a method of sending data accurately while checking the status of the connected device, and since the HDD has a control system inside, the load on the CPU can be reduced. The ATA type is inexpensive and has a large capacity, but the SCSI type evolved from a system for servers, and is excellent in terms of speed and expandability, and since it can process SCSI commands in multithreading, it is highly reliable even under high-load environments. HDDs have an excellent cost per unit of capacity, but as mentioned above, they contain moving parts which take time to access and there is the risk of mechanical failure. Therefore, for server equipment that requires high reliability, RAID can be used to distribute reading and writing to multiple HDDs simultaneously, or the same file can be written to multiple HDDs.

[0042] (Flash memory) Currently, two types of flash memory are commonly used: NAND flash memory and NOR flash memory. Although there are pros and cons regarding read / write speed, NAND flash memory is more advantageous for high integration and is used for data storage. Compared to hard disk drives, it is small because it has no moving parts and does not generate vibration or noise during operation. However, the cost per capacity has not yet fallen to the point where it can replace hard disk drives. Although it is more expensive than hard disk drives, it has the advantage of being compact and resistant to shocks. Smartphones and mobile information terminals usually have a memory capacity of around 64GB to 256GB for data storage purposes, so flash memory is used to make them smaller and lighter. In PCs and other devices, solid-state drives (SSDs) made of flash memory are beginning to be used for frequently accessed drives that store the OS and application software.

[0043] <Main memory>

[0044] The CPU directly accesses and executes various programs in main memory. Main memory is a volatile memory that uses DRAM. Programs in main memory are expanded from non-volatile memory to main memory upon receiving a program start command. The CPU then executes the program according to various execution commands and execution procedures within the program.

[0045] Operating System (OS)

[0046] An operating system is used to manage the resources available to applications on a computer, to manage various device drivers, and to manage the computer itself (the hardware). In small computers, firmware may be used as the operating system.

[0047] ≪UEFI≫

[0048] In recent years, UEFI (Unified Extensible Firmware Interface), which plays a similar role as an evolved successor to the previously used BIOS, has been used. UEFI is also stored in a flash ROM and installed on the motherboard, just like BIOS. The flash ROM chip containing UEFI causes the CPU to execute procedures to start up the computer hardware and run the operating system, and is most typically the hardware that the CPU reads first when it receives a computer startup command. The address of the operating system stored on the disk (non-volatile memory) is written here, and the operating system is sequentially loaded into main memory by the UEFI loaded into the CPU and becomes operational. UEFI also has a check function that checks the presence or absence of various devices connected to the bus. The check results are stored in main memory and are made available to the operating system as appropriate. UEFI may be configured to check external devices, etc.

[0049] As shown in the figure, the present invention can basically be configured with a general-purpose computer program and various devices. The computer basically operates in a form in which a program recorded in a non-volatile memory is loaded into the main memory, and processing is executed by the main memory, the CPU, and various devices. Communication with the devices is performed via an interface connected to a bus line. Possible interfaces include a display interface, USB, a LAN terminal, a PCI Express interface, and a communication buffer.

[0050] Each of the functional blocks constituting the device of the present invention described below can be realized by any of hardware, software, or both. Specifically, if a computer is used, the hardware components include a CPU, main memory, GPU, image memory, graphic board, bus, or secondary storage device (non-volatile memory such as a hard disk or flash memory, storage media such as CDs or DVDs, and reading drives for those media), input devices such as operation buttons used for information input, a mouse, a touch panel, an electronic pen used solely for touching a touch panel, a joystick or a joystick-like pointer position input device, and other external peripheral devices, as well as interfaces for those external peripheral devices, communication interfaces such as LAN terminals, GPS receiving interfaces, GPS arithmetic units, gyro sensors, acceleration sensors, rotation detection sensors, processing devices for signals from these sensors, cameras, image file processing circuits, speakers, microphones, audio file processing circuits, communication interfaces, barcode readers, electronic card readers, POS terminals, face authentication devices, encryption devices, biometric authentication devices such as fingerprint authentication devices, palm print authentication devices, and retina authentication devices, and driver programs and other application programs for controlling those hardware. In particular, it utilizes smartphones, tablet devices, mobile phones, smart watches, personal computers, data center server equipment, wired and wireless networks and interfaces.

[0051] The CPU performs arithmetic processing according to the program deployed on the main memory, and processes and stores data input from input devices and other interfaces and held in the memory or hardware, and generates commands for controlling the hardware and software. The above programs may be realized as multiple modularized programs, or may be realized as a single program by combining two or more programs.

[0052] The present invention can also be partially configured as software. Furthermore, storage media on which such software is recorded are naturally included within the technical scope of the present invention (this is not limited to this embodiment, but is the same throughout this specification).

[0053] <Terminology used in the present invention>

[0054] "Identification information" refers to symbols, letters, codes, etc. used to identify something. However, there may be cases where the identification information itself is the information being identified. For example, identification information that identifies character string record A may be character string record A itself. Therefore, for example, electricity consumer identification information that identifies an electricity consumer may be a mere symbol, letter, code, or the name, business name, address, or contact information of the electricity consumer identified by the symbol, letter, code, etc. at the same time.

[0055] The term "association" is used in this specification to mean not only a case where two or more pieces of information are directly associated with each other, but also a case where two or more pieces of information are indirectly associated with each other via one or more other pieces of information. An indirect association is not necessarily limited to an association within one device (a device having a single housing), but also includes a case where the association is made across multiple devices.

[0056] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0057] <Overview of embodiment 1> Mainly claims 1, 10, and 19 The electricity usage cost analysis device of embodiment 1 is a device that analyzes the electricity usage costs of electricity consumers in an electricity supply and demand system based on a billing system in which the amount charged to electricity consumers is predetermined and determined in conjunction with the electricity trading market price, which fluctuates according to the amount of electricity supply that changes depending on the weather, and is configured to acquire weather data in order to reduce the electricity bill for a certain month, and output one or more of the following: maximum demand power information, which is information used to reduce the maximum demand power during a demand time period within a certain month; maximum electricity usage information, which is information used to reduce the electricity usage on a daily basis within the certain month; monthly electricity usage information, which is information used to reduce the electricity usage within the certain month by dividing it into active and inactive time periods within the certain month; and total monthly electricity rate information, which is information for reducing the electricity rate on a monthly basis.

[0058] <Functional configuration of embodiment 1> Fig. 1 shows a functional block diagram of an electric power usage cost analysis device according to embodiment 1. The electric power usage cost analysis device (0100) according to embodiment 1 is a device for analyzing electric power usage costs of electric power consumers in an electric power supply and demand system based on a billing system in which the amount of charge to the electric power consumer is determined in advance in conjunction with the electric power trading market price that fluctuates according to the amount of electric power that can be supplied, which changes according to the weather, and has a maximum electric power demand information storage unit (A) (0101), a maximum electric power usage information storage unit (B) (0102), a monthly electric power usage information storage unit (C) (0103), a total monthly electric power usage information storage unit (D) (0104), a total monthly electric power charge information storage unit (E) (0105), and an information output unit (F) (0106).

[0059] The above functional blocks are merely an example for implementing the present invention, and functions may be omitted or new functions may be added as appropriate within the scope that does not contradict the problems to be overcome by the present invention and its effects. The same applies to the following description of the first embodiment and subsequent embodiments.

[0060] <Description of the configuration of embodiment 1>

[0061] <Embodiment 1: Electricity Usage Cost Analysis Device (0100)> The "electricity usage cost analysis device" (0100) is configured to be a device for analyzing the electricity usage costs of electricity consumers in an electricity supply and demand system based on a billing system in which the amount charged to electricity consumers is determined in advance in conjunction with the electricity trading market price, which fluctuates according to the amount of electricity that can be supplied, which changes depending on the weather.

[0062] "Available power supply that changes with the weather" refers to the available power supply that varies with the weather, such as photovoltaic power generation, which converts sunlight into electricity using solar cells, thermal power generation, which concentrates sunlight in a solar furnace, power generation that uses sunlight as a heat source for a Stirling engine, and wind power generation, which uses wind power to turn a windmill to generate electricity. The amount of power generated varies with the amount and duration of sunlight in photovoltaic power generation, and with wind power generation, the amount of power generated varies with the strength and duration of wind. Photovoltaic power generation is affected by latitude and climate (areas that snowfall in winter are not suitable because the solar panels are hidden by snow, and high latitude regions are not suitable because the hours of sunlight are short). Wind power generation cannot be operated if the wind is too strong due to concerns that the windmills will be damaged, so it is used within the appropriate wind speed range (power generation occurs at wind speeds of 3 to 25 m / s, but areas with an annual average wind speed of 6 m or more are preferable).

[0063] "Electricity trading market price that fluctuates according to the amount of available electricity supply that changes according to the weather" refers to, as an example of power generation where the amount of available electricity supply changes according to the weather, when a generator sells electricity generated by solar power on the electricity trading market, in seasons where the weather is likely to be clear and the hours of sunshine are long (e.g. summer), a large amount of generated electricity is sold during the day, so the supply exceeds the demand for electricity and the electricity trading market price falls. If it rains during the daytime in summer, solar power generation cannot be performed during the day and the amount of electricity supplied falls, but the demand for electricity for cooling purposes does not decrease, so the daytime electricity trading market price rises. In this way, the electricity trading market price fluctuates according to the predicted amount of available electricity supply, which changes according to the weather forecast for the next day.

[0064] An "electricity trading market" is a market that mediates electricity transactions between power generators and electricity retailers. For example, in Japan, the equivalent is the Japan Electric Power Exchange (JEPX), a general incorporated association.

[0065] "A billing system in which the amount charged to an electricity consumer is determined in advance in accordance with the electricity trading market price" refers to a system in which, in a contract in which an electricity consumer purchases electricity from an electricity retailer and / or sells electricity to an electricity retailer, the electricity purchase price charged to the electricity consumer and / or the amount acquired by selling electricity are determined in advance to be linked to the electricity trading market price (this does not preclude the case where they are the same as the electricity trading market price). As an example of a billing system, a billing system in which at least a part of the metered portion charged according to the electricity consumption of the electricity consumer is a unit price (e.g., yen / kWh) linked to the electricity trading market price. The billing system may be a combination of a fixed fee and a metered portion, or the metered portion may include a unit price portion that is not linked to the electricity trading market price (e.g., a fuel cost adjustment amount). Note that "linked" means dependent with an arbitrary relationship, and does not necessarily require a fixed relationship (although it may be).

[0066] <Embodiment 1: Electricity Usage Cost Analysis Device: Example of Billing System> An example of a billing system is a billing system in which the unit price portion of the metered portion of the electricity bill, which is appropriately set by the electricity retailer, is a unit price linked to the electricity trading market price (unit price). The electricity bill may be composed of a fixed fee and a metered portion whose amount increases according to the amount of electricity used. The fixed fee portion may be, for example, a basic fee according to the contracted ampere number of the breaker for an ordinary household, a basic fee according to the maximum demand power in the past per demand time period for an electricity consumer with a high-voltage power contract, or a commission fee of the electricity retailer. If the fuel cost adjustment amount for thermal power generation is a fixed amount, it can be included in the fixed fee portion. The basic fee included in the fixed fee in the above explanation may be a fixed unit price fee according to the contracted ampere number or the maximum demand power.

[0067] The unit price of the metered portion may be the market price (unit price) as it is, or may be a billing system that is linked to the power trading market price (unit price) but is not the market price (unit price) itself, such as the unit price obtained by adding a certain fee of the power retailer to the power trading market price (unit price). An example of a calculation formula in which the unit price of the metered portion is not the power trading market price (unit price) itself is fixed charge + (external factor fixed unit price + power trading market price linked unit price) x electricity usage. For the metered portion from the second item onwards in this formula, in addition to the power trading market price linked unit price, there are fixed unit prices that depend on external factors that do not depend on the power retailer, such as the wheeling charge (unit price) paid to the power transmission company between the power generation company (power plant) and the power consumer as external factor fixed unit prices, renewable energy surcharge (unit price), and fuel price adjustment fee (unit price determined monthly). In addition, as mentioned above, the supply management fee unit price as a profit and recovery of expenses required by the power retailer for purchasing electricity and expenses for running the business can be appropriately set in the above formula.

[0068] <Embodiment 1: Power usage cost analysis device: Consideration of reducing electricity usage and electricity charges> The device of the present invention is a device that analyzes the environmental friendliness that can be improved by reducing the electricity usage cost and electricity usage of the electricity consumer when the electricity consumer purchases electricity from the electricity retailer (or conversely, when the electricity consumer sells surplus electricity generated by solar power generation or the like to the electricity retailer) in a contract between the electricity retailer and the electricity consumer under a billing system linked to the electricity trading market price that fluctuates according to the amount of electricity generated (amount of electricity supplyable) that fluctuates according to the weather. In other words, not only money but also environmental considerations are considered at the same time. It is possible to infer why electricity usage was particularly high during the time period (or demand time period) of a day, on the day of the month, or in the month of the month, in light of representative weather information (representative weather information) described later. It is possible to infer why the amount of electricity usage is high during the active time period and the inactive time period, or between weekdays and holidays, by comparing the amount of electricity usage in relation to the representative weather information described later. In addition, even when trying to improve the way of business activities at a workplace based on this information, it is possible to make improvements while considering life-work balance. For example, by analyzing this information, it is possible to consider measures such as having employees commute during avoidable peak hours, introducing teleworking, etc. From the results of the inference, electricity consumers can obtain and implement measures to reduce electricity usage and / or electricity bills.

[0069] <Embodiment 1: Power Usage Cost Analysis Device: Configuration Example for Reducing Electricity Charges> In addition, a future electricity trading market price (unit price) or a price (unit price) linked to the electricity trading market price, which is in the future from the time when the reduction of electricity usage or the reduction of electricity charges is being considered, can be acquired in association with information on the weather at the target time (one or more of temperature, humidity, wind speed, sunny with clouds and rain, and sunshine hours), and a future electricity usage schedule can be created or revised based on the acquired electricity trading market-linked unit price and information output from the device of the present invention. The temperature, humidity, wind speed, sunny with clouds and rain, and sunshine hours, which are exemplified as weather information, affect the electricity usage amount of electricity consumers. In addition, the wind speed and sunshine hours (weather: sunny with clouds and rain may be included) among the weather information also affect the amount of electricity generated (electricity supplyable amount) by wind power generation, solar power generation, etc.

[0070] For example, tomorrow's electricity trading market linked price is obtained in association with weather information, and consideration is given to shifting activities from time periods (or demand time periods) when the electricity trading market price (unit price), which fluctuates according to the amount of available electricity supply that changes according to the weather, to time periods (or demand time periods) when the price is high, to time periods (or demand time periods) when the price is low.When considering shifting activity times, a prediction is made as to which electricity bill will be cheaper, if the activity times are shifted or not, taking into account factors such as the amount of electricity used (electricity bill) for air conditioning and lighting predicted from weather information such as temperature.

[0071] For this purpose, in addition to the configuration of the first embodiment, an electricity trading market linked price acquisition unit that acquires a future electricity trading market price (unit price) or a price (unit price) linked to the electricity trading market price, which is future than the time point at which a reduction in electricity usage or an electricity bill is being considered, in association with information on the weather at the target time point (one or more of temperature, humidity, wind speed, sunny, cloudy, rainy, and sunshine hours), an electricity trading market linked price retention unit that retains the acquired electricity trading market linked price, a future electricity usage plan information retention unit that retains future electricity usage plan information which is information showing a future electricity usage plan, and an electricity usage control unit that controls electricity usage so that the future electricity bill will be lower than the currently retained electricity usage plan, based on the acquired electricity trading market linked price, the output information, and the retained future electricity usage plan information. This can be achieved by configuring the system further to have an electricity usage schedule editing rule holding unit that holds electricity usage schedule editing rules for editing (creating, modifying) the schedule, a current future electricity rate estimation unit that estimates the current future electricity rate, which is the future electricity rate, based on the acquired electricity trading market linked unit price, the output information, and current future electricity usage schedule information, which is future electricity usage schedule information at the current time, and a future electricity usage schedule information acquisition unit that acquires future electricity usage schedule information in which the electricity rate is lower than the current future electricity rate, based on the acquired electricity trading market linked unit price, the output information, current future electricity usage schedule information, which is future electricity usage schedule information at the current time, the estimated current future electricity rate, and the electricity usage schedule editing rules.

[0072] <Embodiment 1 Weather Data Acquisition Unit (Q) (0116)> The 'weather data acquisition unit (Q)' (0116) is configured to acquire weather data, such as one or more of the following data at predetermined time intervals: temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours.

[0073] "Weather data" refers to data such as temperature, humidity, wind speed, sunny with cloudy weather, and sunshine hours observed by the Japan Meteorological Agency at various weather stations and observation stations. Observation stations under the jurisdiction of the Japan Meteorological Agency include wired robotic rain gauges that only observe precipitation, wired robotic weather meters that measure precipitation, temperature, wind direction, and wind speed, and ground-based meteorological observation devices that observe precipitation, temperature, wind direction, wind speed, sunshine hours, relative humidity, air pressure (excluding some observation stations), and snow depth (limited to some observation stations). Weather data is not limited to the Japan Meteorological Agency. It may be obtained and used from private weather companies (e.g., Weathernews, etc.). Weather information such as sunny with cloudy weather and rain may be obtained from the Japan Weather Association or the aforementioned private weather companies. Regarding weather, snow may be used instead of rain in winter. Also, instead of the three stages of sunny with cloudy weather and rain, weather expressed with "occasionally," "later," or "temporarily," such as "sunny with occasional cloudy weather," "sunny with rain later," or "sunny with occasional rain" may also be used. According to the Japan Meteorological Agency's definition, "occasionally" means that the phenomenon occurs intermittently and the total duration of the phenomenon is less than half the forecast period. "temporarily" means that the phenomenon occurs continuously and the duration of the phenomenon is less than a quarter of the forecast period. "later" means that the weather changes between the first and second halves of the forecast time.

[0074] The "predetermined time interval" may be, for example, the shortest interval (e.g., 10 minutes) for observing the weather data. As another example, it may be every time period of the demand time zone (every 30 minutes in Japan).

[0075] <Embodiment 1: Conversion rule storage unit (R) (0117)> The "weather data acquisition unit (Q)" (0117) is configured to hold conversion rules, which are rules for converting the acquired weather data, such as temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, based on the acquired weather data, into representative weather information, which is information regarding representative weather for one or more of the demand time period, day, week, month, and quarter (demand time period, day, week, month, and quarter are time lengths equal to or longer than the specified time interval; the same applies below) in which the weather data was observed.

[0076] The data is obtained from public data of the Japan Meteorological Agency, sales data of meteorological companies (for example, Weathernews), etc. Here, "representative" refers to a value that typically affects the use of electricity, and in the case where the meteorological data is numerical information, examples include, but are not limited to, the median, average, maximum average value and standard deviation, and the time integral value of these numerical values. Data related to weather may be a value obtained by quantifying the weather as described in paragraph number 0083 below, or may be the weather in which the weather is observed in the largest area among the areas to which the weather data related to weather is applied. Also, it may be the weather in which the weather is observed for the longest period of time. In addition, the conversion rule may be configured to be customizable according to the user of this system, and for this purpose, the conversion rule may be stored in association with user identification information, and the user identification information may be acquired when this system is used, and the conversion rule associated with the user identification information may be adopted to perform calculations. In addition, it is preferable that this conversion rule is editable, and for example, this function can be realized by providing a conversion rule editing unit.

[0077] In relation to electricity trading, "demand" refers to the average value of electricity (demanded power: in kW or MW) requested by electricity consumers in the shortest time when trading with electricity retailers (30 minutes in Japan as of early 2023). In Japan as of 2023, one demand time slot will be from 0 minutes to 30 minutes and from 30 minutes to 60 minutes of every hour, and a day will be divided into 48 demand time slots. Information related to the time slot that indicates which time slot the demand is for will be referred to as the "demand time slot" in this specification.

[0078] Unless otherwise specified, the term "day" used herein means one day. It may be a calendar day or a continuous 24-hour period that corresponds to one calendar day.

[0079] "Week" means one week unless otherwise specified in this specification. It may start on Sunday or Monday (or on any other day of the week). It may be seven consecutive days, which is the number of days that corresponds to one calendar week.

[0080] "Month" means one month unless otherwise specified in this specification. It may be one calendar month or a continuous period of time that is the number of days equivalent to one calendar month (e.g., 30 days).

[0081] Unless otherwise specified in this specification, a "quarter" refers to a period of three months that divides a year into four parts. Usually, it refers to one of the four periods from April to June, July to September, October to December, or January to March.

[0082] The "representative weather information" refers to a value that typically affects the use of electricity. There is at least one weather data within a period such as a demand time zone, day, week, month, or quarter (demand time zone, day, week, month, or quarter is a time length equal to or longer than a predetermined time interval for observing the weather data), and when there are multiple weather data, it is also a value that represents the multiple weather data. The conversion rule determines how to obtain the representative value. For weather data expressed as numerical values ​​such as temperature, humidity, or wind speed, the conversion rule may be, for example, a median, average value, maximum average value, standard deviation, or a time integral value of these numerical values, as described above, but is not limited thereto. For non-numerical weather data such as sunny, cloudy, rainy, or wind direction, the representative value may be the weather data observed for the longest time within the period such as a demand time zone, day, week, month, or quarter in which the weather data was observed, or the weather data in which the area in which the weather data (e.g. sunny, cloudy, rainy, or wind direction) is observed in the largest area within the region to which the weather data is applied. In this way, based on the acquired weather data, information regarding the acquired weather data such as temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours that is representative of one or more of the typical weather conditions of the demand time period, day, week, month, or quarter in which the weather data was observed is the representative weather information.

[0083] The "conversion rule" is a rule for converting the acquired weather data into representative weather information, which is information on one or more representative weather of the demand time slot, day, week, month, or quarter to which the time of observation belongs. For example, the data of the observation point in Tokyo at 12:10 noon on March 1, 2024 was 14.6°C in temperature, 52% relative humidity, average wind speed 4.1 m northwest, maximum instantaneous wind speed 8.2 m northwest, 10 minutes of sunshine, and fine weather. Therefore, the rule may be that this one data is the representative weather information for the demand time slot from 12:00 to 12:30. Alternatively, the rule may be that one data of the weather data at 12:00, which is the start time, or 12:30, which is the end time, is the representative weather information for the demand time slot from 12:00 to 12:30. Alternatively, the rule may be that the average of the four weather data at 12:00, 12:10, 12:20, and 12:30, which are data every 10 minutes, is the representative weather. In this case, for example, sunny, cloudy, and rainy, a rule may be used to determine the average score of sunny, cloudy, and rainy by rounding off the average score to the nearest 1 digit, or a rule may be used to determine the most frequently occurring weather as the representative weather. In cases where the weather changes over the observation period of the meteorological data, such as "sunny with occasional rain," "sunny with occasional rain," or "sunny with rain later," a rule may be used to determine the weather that has been observed for the longest period as the representative weather information.

[0084] The conversion rules for converting into representative weather information for a demand time period have been described as an example, but if the predetermined time interval for acquiring weather data is shorter than a day, week, month, or quarter, as in the above example, the same conversion rules as in the above example can also be applied to a day, week, month, or quarter. For example, in the case of a "month," weather data observed within the target month is acquired at least once at a predetermined time interval (e.g., 10-minute interval, 1-hour interval), and the average value, most frequent value, or median value is used as the representative weather information.

[0085] <Embodiment 1: Maximum Demand Power Information Storage Unit (A) (0101)> The "maximum demand power information storage unit (A)" (0101) is configured to store maximum demand power information, which is information obtained by acquiring and associating the maximum demand power for the month, the demand time period during which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather during the demand time period or / on the day that includes the demand time period (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours).

[0086] Based on the acquired weather data and the stored conversion rule, representative weather information is acquired regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) of the day including the demand time period during which the maximum power demand for the month occurred. The maximum power demand information storage unit (A) is configured to store maximum power demand information that is information that associates the maximum power demand for the month with the acquired representative weather information.

[0087] "Monthly" means within one month unless otherwise specified in this specification. It may be one calendar month or a continuous period of time that is the number of days equivalent to one calendar month (e.g., 30 days).

[0088] "Maximum demand power information" refers to information that associates the maximum demand power during a demand time slot in a certain month when the average demand power during that demand time slot in a contract with an electricity retailer is maximum with representative weather information regarding the demand time slot in which the maximum demand power occurred and / or the weather on the day that includes that demand time slot, which is obtained based on the acquired weather data and the stored conversion rule. Hereinafter, in this specification, the average demand power during a demand time slot will be referred to simply as the demand power during the demand time slot.

[0089] Since the "maximum demand power information" is information that correlates the maximum demand power, the demand time slot during which the maximum demand power occurred, and representative weather information regarding the weather of the demand time slot and / or the day that includes the demand time slot (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours), it is possible to know what kind of weather (representative weather information) the maximum demand power occurred in. If the maximum demand power occurs during a demand time slot in the afternoon of summer, and the temperature during the day is over 30°C, but there is no wind all day, it is cloudy, and there is almost no sunshine, it can be inferred that even if solar or wind power generation is installed for private power generation, it makes little contribution, and the demand power purchased from the power retailer for power demand for air conditioners for cooling has reached its maximum. Since the maximum power demand indicates the maximum value of the power demand per demand hour in a certain month as described above, investigating the cause of the maximum power demand (e.g., temperature, business activities of the power consumer, time-of-day trends in electricity use, power consumption tendency, etc.) helps to reduce the maximum power demand and reduce the monthly electricity usage of the relevant month or the monthly electricity usage of the following month and thereafter. In order to investigate the cause, it is preferable to compare the maximum power demand information of a month other than the month described above as in the third embodiment described below. By comparing information on the demand time period, day of the week, weather, etc., it becomes easier to grasp the cause. The maximum power demand during the power supply contract period (usually one year, but not limited to this) determines the basic fee of the electricity fee, which is the charge, but the effect of the present invention is that by analyzing the maximum power demand per month in this way, training to reduce the maximum power demand can be performed on a regular basis. Therefore, although it does not directly lead to a reduction in the basic fee, it can be said that the training effect indirectly leads to a reduction in the basic fee.

[0090] The system may further include a maximum demand power information acquisition unit that acquires the maximum demand power information, which is information obtained by acquiring the maximum demand power for the month, the demand time period in which the maximum demand power occurred, and representative weather information related to the weather (at least one of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the demand time period or / including the demand time period, and then associates the representative weather information with the maximum demand power information. The maximum demand power may be configured to have a maximum demand power output unit in the power receiving equipment that receives the power, and the maximum demand power information acquisition unit has weather information acquisition means for acquiring weather data from the weather data acquisition unit (Q). The power receiving equipment corresponds to a smart meter if the power consumer is a general household, and corresponds to a high-voltage power receiving equipment if the power consumer is a high-voltage power receiver. The system may include a maximum demand power output unit that outputs the maximum demand power to a smart meter or a monitoring device for the high-voltage power receiving and transforming equipment (which may be integrated with the high-voltage power receiving and transforming equipment), or to the high-voltage power receiving and transforming equipment itself. The system may be configured to output the maximum electricity usage, monthly electricity usage, and total electricity usage, which will be described later, from the power receiving equipment in the same manner as the maximum demand power. Alternatively, the data on maximum demand power and electricity usage may be output by the power receiving equipment, and received and stored by a computer or a center server device used by the power consumer, and after a specified period of information has been stored, the data may be obtained as maximum electricity usage, monthly electricity usage, or total electricity usage.

[0091] The power consumer identification information storage unit may further include power consumer identification information that identifies a power consumer who is a consumer of power, and may be configured to store the maximum power demand information of the power consumer in association with the power consumer identification information. The power consumer identification information is preferably configured to be stored in association with the maximum power consumption information, monthly power consumption information, total monthly power consumption information, and total monthly electricity charge information, which will be described later, when each of the information is stored in each storage unit. The center server device may be configured to store various information of a large number of power consumers (including at least "information" described in all claims) so that the center server device can perform statistical processing and the like for comparison and analysis. From this perspective, the power usage cost analysis device of the present invention may be configured to be constructed in the center server device, and each power consumer may be configured to be able to view the information via a network. In this case, the present invention is implemented in two tiers, namely, implementation in the center server device and implementation established by each power consumer viewing the information (Patent Law, Article 2, Paragraph 3). However, the power usage cost analysis device may be configured to be constructed in a computer used by each power consumer.

[0092] The maximum demand power included in the maximum demand power information is also the data that determines the basic charge in the billing system contract when the power consumer purchases high-voltage power from the power retailer. However, even when the basic charge is determined in "amperes" like an ordinary household, i.e., when it is determined by the maximum current usage, the "maximum current usage" is included in the "maximum demand power" as referred to in this specification. The basic charge is determined by the maximum demand power during the basic charge calculation period (e.g., one year; generally, power purchase contracts are one-year contracts, so the basic charge calculation period is one year, but is not limited to this), so maintaining or reducing the maximum demand power is effective in reducing electricity charges.

[0093] <Embodiment 1: Maximum Electricity Usage Information Storage Unit (B) (0102)> The "maximum electricity usage information storage unit (B)" (0102) is configured to store maximum electricity usage information, which is information obtained by acquiring representative weather information on the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for a day or / the week in which the day is included based on the maximum electricity usage for a day included in the month and the acquired weather data and the stored conversion rule, and then storing the maximum electricity usage information associated with the representative weather information.

[0094] The "maximum electricity usage information" refers to the maximum amount of electricity usage used in one day within the same month, relative to the maximum demand power information in which the demand power per demand time period is the maximum. The unit of electricity usage is "kWh" or "MWh", but is not limited thereto. Any unit of electricity usage may be used. By acquiring and associating weather information for that day and / or representative weather information for the week including that day, it is possible to infer whether there is a weather factor that maximizes electricity usage. Investigating the cause of the maximum electricity usage used in one day (e.g., temperature, business activities of the electricity consumer, time-of-day trends in electricity usage, electricity consumption tendency, etc.) helps to reduce the maximum electricity usage in one day, and thus reduces the monthly electricity usage for the month. By reducing the electricity usage, it is possible to reduce the electricity fee (charged amount), which is the electricity usage cost of the electricity consumer, and also to improve environmental friendliness. In order to investigate the cause, it is preferable to compare with the maximum electricity usage information for a month other than the month, as in the embodiment 3 described later. It becomes easier to understand the cause by comparing weekday / holiday distinctions, days of the week, weather information, etc.

[0095] The system can be further configured to have a maximum electricity usage information acquisition unit that acquires maximum electricity usage information that associates the maximum electricity usage for a day within the month with information regarding the weather (one or more of temperature, humidity, wind speed, sunny, cloudy, rainy, and sunshine hours) for that day and / or the week that includes that day.

[0096] <Embodiment 1: Monthly Electricity Usage Information Storage Unit (C) (0103)> The "monthly electricity usage information storage unit (C)" (0103) is configured to store monthly electricity usage information, which is information associated with the monthly electricity usage, representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including that month, based on the acquired weather data and the stored conversion rules.

[0097] "Monthly electricity usage information" is information that associates the electricity usage for the month with information on the weather for that month or the quarter (3 months) including that month. It is possible to infer why electricity usage for a certain month was the same from representative weather information for that month or the quarter including that month. For example, in Japan, from July to September, especially in August, the temperature rises, and when it is sunny, it becomes tropical nights and extremely hot days during the day, and electricity usage related to air conditioning for cooling increases. From December to February, it gets cold during the day and night, so electricity usage related to air conditioning for heating increases. Investigating the causes (e.g., temperature, business activities of electricity consumers, time trends of electricity usage, electricity consumption tendency, etc.) in this way helps to reduce monthly electricity usage. Reducing electricity usage can reduce electricity charges (charges), which are the electricity usage costs of electricity consumers, and also improve environmental friendliness. In order to investigate the causes, it is preferable to compare monthly electricity usage information for a month other than the month mentioned above, as in the third embodiment described below. It becomes easier to understand the cause by comparing weekday / holiday distinctions, days of the week, weather information, etc.

[0098] The system can be further configured to have a monthly electricity usage information acquisition unit that acquires monthly electricity usage information, which is information that associates the monthly electricity usage with information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and hours of sunshine) for that month or the quarter including that month.

[0099] <First embodiment: Total monthly electricity usage information storage unit (D) (0104)> The "total monthly electricity usage information storage unit (D)" (0104) is configured to store total monthly electricity usage information, which is information obtained by correlating representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including that month, obtained based on the acquired weather data and the stored conversion rule, with one or more of the total electricity usage during a specified active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays.

[0100] The "total monthly electricity usage information" is information obtained by acquiring representative weather information and associating one or more of the total electricity usages for a certain month during a specific active time period, a non-active time period, weekdays, and holidays. The "specific active time period" is, for example, the time period from when the electricity consumer enters the place where electricity is used until when he / she leaves. For example, in the case of a store, the business hours of the store (which may include the time for preparation before opening and the time for tidying up after closing) are the specific active time period, and the closing time (which may be the time from when the tidying up after closing is finished until the start of preparation before the next opening) is the non-active time period. In the case of an ordinary household where the family members are at home during the day, the specific active time period is from when they wake up until when they go to bed, and the bedtime is the non-active time period. In the case of an ordinary household where both partners work, the specific active time period is the morning from when they wake up until when they go to work, and in the evening from when they get home until when they go to bed, and the other times when they are sleeping and when they are absent are the non-active time periods. In the case of a factory that operates 24 hours a day with shift work, the time period from morning to evening when the number of workers in the factory increases as daytime workers join, and the time period from evening to morning when only night shift workers are present and the number of workers in the factory decreases may be the inactive time period. As an extreme example, in a factory that produces products using unmanned automatic machines, the designated active time period is when there are no people on the production line in the factory and production is being carried out, and the inactive time period is when there are people on the production line and the production equipment is stopped to perform maintenance work. In addition, in the case of a store or factory, holidays are non-working days (inactive time period) and other days are working days (designated active time period), and it is thought that there will be a difference in electricity usage. In order to understand the difference in electricity usage due to the activity and inactivity of electricity consumers, information that is further linked to representative weather information is the total monthly electricity usage information.

[0101] Dividing the time for a certain month into a predetermined active time period and an inactive time period, and investigating the cause of the amount of electricity used in each time period, or the amount of electricity used on weekdays and holidays, while also taking into account representative weather information (e.g., temperature, business activities of the electricity consumer, time-of-day trends in electricity use, electricity consumption tendency, etc.), can help reduce the total monthly electricity use, and ultimately reduce the monthly electricity use for the month. Reducing the amount of electricity use can reduce the electricity bill (charged amount), which is the electricity usage cost of the electricity consumer, and can also improve environmental friendliness. In order to investigate the cause, it is preferable to compare the total monthly electricity use information for a month other than the month, as in the embodiment 3 described below. By comparing information on events caused by the electricity consumer and weather information, it is easier to grasp the cause.

[0102] The system can be further configured to include a total monthly electricity usage information acquisition unit that acquires total monthly electricity usage information, which is information obtained by acquiring one or more of the total electricity usage during a specified active time period of the month, the total electricity usage during an inactive time period, the total electricity usage on weekdays, and the total electricity usage on holidays, and representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or a quarter including that month, and associating these with the representative weather information. It is preferable to accept input regarding active time periods and inactive time periods from the electricity consumer, and distinguish between the electricity usage during the active time periods and the electricity usage during the inactive time periods according to the time periods. This function can be accepted by the active time period and inactive time period input acceptance unit, and the electricity usage can be acquired according to the division of the accepted time periods.

[0103] <First embodiment: Total monthly electricity charge information storage unit (E) (0105)> The 'total monthly electricity charge information storage unit (E)' (0105) is configured to store total monthly electricity charge information indicating the total electricity charge for the month.

[0104] "Total monthly electricity charge information" refers to the total electricity charge for the month to which one or more of the following information belongs: maximum demand power information, maximum electricity usage information, monthly electricity usage information, and total monthly electricity usage information. It is desirable for electricity consumers to reduce their electricity charges. Therefore, total monthly electricity charge information is important to electricity consumers, and in order to reduce their electricity charges, electricity consumers are motivated to reduce their electricity usage (which affects the metered charge portion of the electricity charge) and maintain or reduce their maximum demand power (maximum demand power affects the basic charge amount of the electricity purchase contract).

[0105] Taking weather information into consideration, investigating the cause of such a total monthly electricity bill (e.g. temperature, business activities of the power consumer, time-of-day trends in electricity use, power consumption tendencies, etc.) can help reduce the total monthly electricity bill. It can also help reduce future monthly electricity usage in the month in question or the following month. Reducing electricity usage can reduce the electricity bill (charged amount), which is the power usage cost of the power consumer, and also improve environmental friendliness. To investigate the cause, it is preferable to compare with total monthly electricity bill information for a month other than the month in question. It is easier to grasp the cause by comparing information on events caused by the power consumer, weather information, time-of-day trends in electricity use, power consumption tendencies, etc.

[0106] The power receiving facility that receives power purchased by the power consumer from the power retailer may have a demand-per-demand energy amount acquiring unit that acquires demand-per-demand energy amount information that is information indicating the demand energy per demand time, a demand-per-demand energy amount holding unit that holds the demand-per-demand energy amount, and a demand-per-demand energy amount output unit that has been held, and the information terminal of the power consumer may have a demand-per-demand energy amount information acquiring unit that acquires the demand-per-demand energy amount information that is output from the power receiving facility, a demand-per-demand energy amount information holding unit that holds the demand-per-demand energy amount information, and an electricity fee estimation unit that estimates the electricity fee that the power consumer will pay to the power retailer based on the held demand-per-demand energy amount information and power contract information that is information indicating the contract between the power consumer and the power retailer.

[0107] <Embodiment 1 Information Output Unit (F) (0106)> The "information output unit (F)" (0106) is configured to output any one or more of the above-mentioned information. The above-mentioned information is meteorological data (any one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours), representative weather information, maximum power demand information, maximum electricity usage information, monthly electricity usage information, and total monthly electricity usage information. Furthermore, the information may also include monthly maximum power demand, daily maximum electricity usage, monthly electricity usage, monthly total electricity usage during a specific active period, total electricity usage during a non-active period, total electricity usage on weekdays, and total electricity usage on holidays.

[0108] The output is made to one or more of the power consumer, the power retailer, and the manager and operator of the device of the present invention. The output may be output as an e-mail via an Internet line, or may be configured to be viewed on a display using a dedicated app or web browser. Alternatively, it may be printed on paper. When outputting one or more of the maximum power demand information, the maximum electricity usage information, and the monthly electricity usage information to the power consumer (especially when outputting on paper), it is preferable to use a predetermined format that specifies that the same information is written in a predetermined location. By showing one or more of the maximum power demand information, the maximum electricity usage information, and the monthly electricity usage information to the power consumer in a certain format, it is easy to compare them with information output in the past, and it becomes easy to make the power consumer aware of the part where the power consumer's own electricity usage is high. When showing one or more of the maximum power demand information, the maximum electricity usage information, and the monthly electricity usage information, it is easy to grasp the influence of weather on electricity usage by showing representative weather information associated with each of them. The output format can be said to be a power saving sheet that can contribute to reducing electricity usage.

[0109] The output information can also be configured to be stored in chronological order. When comparing with previously output information as described above, it becomes easier to know what point in time the information is being compared with. Also, various combinations of comparisons can be made, such as comparing a certain month with the month before, a certain month with the same month of the previous year, a year to which a certain month belongs with another year, and a season (or quarter) to which a certain month belongs with a month in another season (quarter). The output information can be used to help power consumers consider ways to reduce electricity usage and cut electricity bills. Reducing electricity usage can reduce electricity bills (charges), which are the power usage costs for power consumers, and also improve environmental friendliness.

[0110] In addition, the output may not only be provided to the electricity consumer to which the output information applies, but may also be used by electricity retailers to understand the electricity usage history of electricity consumers with whom they have contracts, or for other electricity consumers to compare their own electricity usage history with that of other electricity consumers (it is preferable that when viewing the electricity usage history of electricity consumers other than oneself, the names and detailed addresses of other electricity consumers are hidden).

[0111] The information output from the information output unit may be configured to output the results of simple regression analysis or multiple regression analysis between the representative weather information and the total monthly electricity usage information.The user data may be grouped by type of business or size, regression coefficients, p-values, t-values, etc. may be compiled for each group, a representative regression line for each group may be created, and a comparison result with the group representative regression line may be output.

[0112] By using the device of the present invention, electricity consumers can easily view at once various information obtained, for example, from the Japan Meteorological Agency (or a private weather company such as Weathernews), weather information from the Japan Weather Association, electricity trading market prices from JEPX, and monthly maximum demand power, daily maximum electricity usage, monthly electricity usage, total monthly electricity usage, etc., from electricity retailers. In particular, the device of the present invention provides information such as monthly maximum demand power, daily maximum electricity usage, monthly electricity usage, and total monthly electricity usage to electricity consumers in association with representative weather information, making it easy to grasp the correlation with representative weather information when electricity usage increases, and has the effect of making it easy to notice the need to reduce electricity usage.

[0113] The device of the present invention has a weather data acquisition unit (Q), a conversion rule storage unit (R), a total monthly electricity bill information storage unit (E), and an information output unit (F), and further has one or more of a maximum demand power information storage unit (A), a maximum electricity usage information storage unit (B), a monthly electricity usage information storage unit (C), and a total monthly electricity usage information storage unit (D).

[0114] <Embodiment 1: Electricity Usage Cost Analysis Device: Modification> As a modification of the first embodiment, the maximum demand power information storage unit (A), the maximum electricity usage information storage unit (B), the monthly electricity usage information storage unit (C), and the total monthly electricity usage information storage unit (D) can be configured to have two or more of them, instead of one or more of them. By using two or more of the maximum demand power information, the maximum electricity usage information, the monthly electricity usage information, and the total monthly electricity usage information, instead of one or more of them, the cause of such electricity usage can be investigated from multiple perspectives, and more effective measures for reduction can be considered. By reducing the electricity usage, the electricity fee (charge amount), which is the electricity usage cost of the electricity consumer, can be reduced, and environmental friendliness can also be improved. To this end, the following configuration can be adopted (the parts in " " are different from the first embodiment).

[0115] An apparatus for analyzing the electricity usage costs of an electricity consumer in an electricity supply and demand system based on a billing system in which a charge amount for an electricity consumer is determined in advance in conjunction with an electricity trading market price that fluctuates according to an available amount of electricity that changes according to weather, the apparatus comprising: A weather data acquisition unit (Q) that acquires weather data at a predetermined time interval, the weather data being one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours; a conversion rule storage unit (R) for storing conversion rules for converting the acquired weather data, such as temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, into representative weather information, which is information related to representative weather of any one or more of the demand time slots, days, weeks, months, and quarters (demand time slots, days, weeks, months, and quarters are time lengths equal to or longer than the predetermined time intervals; the same applies below) in which the weather data was observed; a maximum demand power information storage unit (A) for storing maximum demand power information, which is information obtained by acquiring and associating a monthly maximum demand power, a demand time period in which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather of the demand time period or / a day including the demand time period (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours); a maximum electricity usage information storage unit (B) for storing maximum electricity usage information that is information obtained by acquiring representative weather information (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) regarding the maximum electricity usage for one day included in the month based on the acquired weather data and the stored conversion rule and associating the representative weather information with the weather information for the one day or / the week including the one day based on the acquired weather data and the stored conversion rule; a monthly electricity usage information storage unit (C) for storing monthly electricity usage information that is information obtained by acquiring representative weather information (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) regarding the weather of the month or a quarter including the month based on the electricity usage for the month, the acquired weather data, and the stored conversion rule, and associating the information with the representative weather information; a total monthly electricity usage information storage unit (D) for storing total monthly electricity usage information that associates one or more of the total electricity usage during a predetermined active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays with representative weather information regarding the weather of the month or a quarter including the month (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) acquired based on the acquired weather data and the stored conversion rule; "Any two or more of the above" a total monthly electricity charge information storage unit (E) for storing total monthly electricity charge information indicating the total electricity charge for the month; An information output unit (F) for outputting any one or more of the information; In addition, when there are two or more information storage units and two or more pieces of information are output, the power usage cost analysis device may be configured to obtain the correlation between each piece of information using artificial intelligence.

[0116] <Embodiment 1: Electricity Usage Cost Analysis Device: Example of Use> An example of an electricity usage cost analysis using the electricity usage cost analysis device of the present invention will be described with reference to Figures 30 and 31. The electricity usage cost analysis device of the present invention can be used by consumers to analyze their own electricity usage costs, or by electricity retailers to analyze and present the electricity usage costs of consumers as part of their sales activities to their customers. In the following explanation, an example will be given in which a consumer uses the device of the present invention to analyze his or her own electricity usage costs. The same applies when used by an electricity retailer.

[0117] <Embodiment 1: Power usage cost analysis device: Usage example: Output setting: Output item selection> FIG. 30 is an example of a screen where the owner or manager of the Sato Building in Shinjuku Ward, Tokyo, sets output items and the like to analyze electricity usage costs. As output items, one or more of the following is selected: maximum demand power per demand time slot within a specified month; maximum electricity usage, which is the maximum electricity usage per day within a specified month; monthly electricity usage, which is the electricity usage for a specified month; total monthly electricity usage, which is one or more of the total electricity usage during a specified active time slot within a specified month, total electricity usage during a non-active time slot, total electricity usage on weekdays, and total electricity usage on holidays; and total monthly electricity fee, which indicates the total electricity fee for a specified month. In FIG. 30, two buttons, "output" and "not output," are provided for each output item, and one is selected by pressing either one. In FIG. 30, "output" is selected for all five items.

[0118] <Embodiment 1: Power usage cost analysis device: Usage example: Output setting: Comparison type selection> Under Output Item Selection, select the comparison type for the period to be compared and output. The demand time period within a "month" and days are given as output items in the above explanation as the specified period. Under Comparison Type, press a radio button to select one of the following: "Monthly Comparison" for a comparison with the previous month of the month to be specified later, "Year-to-Year Comparison" for a comparison with the same month of the previous year corresponding to the specified month, or "Year-to-Year Comparison" for a comparison with the specified year and the previous year. In Figure 30, "Monthly Comparison" is selected. Under Comparison Type, enter the year and month of the month to be compared in drum format. When you have finished entering the settings, press the "Confirm" button at the bottom right of the screen. To cancel your selection, press the "Cancel" button, or to cancel the power usage cost analysis, press the "Back" button.

[0119] <Embodiment 1: Power usage cost analysis device: Example of use: Example of month-to-month comparison> Figure 31 is a table comparing the electricity usage cost analysis for the Sato Building with the previous month (October 2022) with November 2022. When "Output" is selected on the screen of Figure 30, five items are displayed: maximum demand power, maximum electricity usage, monthly electricity usage, total monthly electricity usage, and total monthly electricity charge. In addition, the electricity price at JEPX is shown as a reference value as "electricity trading market price that fluctuates according to the amount of electricity supply that changes depending on the weather" regardless of the item selected in Figure 30. Note that Figure 31 is a comparison with the previous month, but the same effect can be obtained by comparing with the same month of the previous year or the previous year. In addition, the specified period may be a week, quarter, or year instead of a day or month.

[0120] For each item of maximum power demand, maximum electricity usage, monthly electricity usage, total monthly electricity usage, and total monthly electricity bill, representative weather information is obtained regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the period that includes the corresponding period of the above five pieces of information (demand time period, day, month, week, etc.) based on the weather data acquired by this device and the stored conversion rules, and this is entered in each column in association with the corresponding information (maximum power demand, maximum electricity usage, monthly electricity usage, total monthly electricity usage, total monthly electricity bill).

[0121] Looking at the table in Figure 31, when comparing the maximum demand power in November 2022 with the previous month of October 2022, both occurred during the daytime in the afternoon, and the target November was 27 kW less than the previous month. The weather (representative weather information) corresponding to the time of occurrence was cloudy in November compared to sunny in the previous month, and the temperature during the corresponding time was 4.8°C lower. Therefore, the decrease in maximum demand power is thought to be due to the influence of weather and temperature. The maximum electricity usage was 380 kWh higher in November. This is thought to be because the maximum temperature, which is the representative weather information corresponding to the day of occurrence, was higher in November, and the weather was sunny followed by cloudy and sunshine. Monthly electricity usage also increased by 1,236 kWh in November. Comparing the monthly representative weather (weather: representative weather information), it was rainy in October, but sunny in November, and the monthly maximum temperature was high. This is thought to be why electricity usage increased.

[0122] The total monthly electricity bill for November increased by 92,014 yen compared to the previous month, an increase of approximately 10%. The increase in electricity usage itself is thought to be due to increased electricity use for air conditioning caused by the influence of temperature and weather (representative weather information). The increase in electricity bill is larger than the increase in electricity usage because the electricity trading market price (unit price) at JEPX, shown at the bottom, was higher in November.

[0123] In this way, the present device is configured to obtain representative weather information regarding the weather for a period including a period during which the maximum power demand or maximum electricity usage occurred based on the obtained weather information and the stored conversion rule, and then to associate and store the representative weather information with the maximum power demand or maximum electricity usage. With this configuration, if a person who is trying to analyze electricity usage costs using the present device looks at the power usage and the representative weather information and it seems that the power usage is increasing regardless of the weather, it can be used as a starting point to find reasons other than the weather. If the amount of electricity usage increases or decreases depending on the weather, it can be used as an opportunity to consider how to reduce electricity usage when it seems that electricity usage is increasing due to weather factors.

[0124] <Embodiment 1 Operation Method> Fig. 2 is a flowchart of the operation method of the electric power usage cost analysis device of embodiment 1. As shown in this figure, the operation method of the electric power usage cost analysis device of embodiment 1 performs a weather data acquisition step (q) (S0201) and a conversion rule storage step (r) (S0202), performs one or more of a maximum demand electric power information storage step (a) (S0204), a maximum electric power usage information storage step (b) (S0206), a monthly electric power usage information storage step (c) (S0208), and a total monthly electric power usage information storage step (d) (S0210), performs a total monthly electric power fee information storage step (e) (S0211), and an information output step (f) (S0213).

[0125] Here, the method of operating the power usage cost analysis device, which is a computer and is an apparatus for analyzing the power usage costs of power consumers in a power supply and demand system based on a billing system in which the amount of charge to the power consumer is determined in advance in conjunction with the power trading market price that fluctuates according to the amount of available power supply that changes depending on the weather, is as follows: The meteorological data acquisition step (q) (S0201) performs a process of acquiring meteorological data, which is one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, at a predetermined time interval; The conversion rule holding step (r) (S0202) performs a process of holding a conversion rule which is a rule for converting the acquired weather data, i.e., temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine duration, into representative weather information which is information on representative weather of any one or more of the demand time slot, day, week, month, and quarter (demand time slot, day, week, month, and quarter are time lengths equal to or longer than the predetermined time interval; the same applies below) in which the weather data was observed, based on the acquired weather data; In (S0203), it is determined whether to execute the maximum demand power information storage step (a) (S0204), and if not, (S0204) is skipped and the process proceeds to before (S0205). The maximum demand power information holding step (a) (S0204) performs a process of holding maximum demand power information, which is information obtained by acquiring the maximum demand power for the month, a demand time period in which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather of the demand time period or / the day including the demand time period (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours), and associating the information with the maximum demand power information; In (S0205), it is determined whether to execute the maximum electricity usage information storage step (b) (S0206), and if not, (S0206) is skipped and the process proceeds to before (S0207). The maximum electricity usage information storage step (b) (S0206) performs a process of acquiring representative weather information on the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for a day or / a week including the day based on the maximum electricity usage included in the month, the acquired weather data, and the stored conversion rule, and then storing the maximum electricity usage information associated with the representative weather information; In (S0207), it is determined whether to execute the monthly electricity usage information retention step (c) (S0208), and if not, (S0208) is skipped and the process proceeds to before (S0209). A monthly electricity usage information storage step (c) (S0208) performs a process of acquiring representative weather information on the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including the month based on the monthly electricity usage, the acquired weather data, and the stored conversion rule, and storing monthly electricity usage information which is information associated with the representative weather information; In (S0209), it is determined whether to execute the total monthly electricity usage information storage step (d) (S0210), and if not, (S0210) is skipped and the process proceeds to before (S0211). The total monthly electricity usage information storage step (d) (S0210) performs a process of storing total monthly electricity usage information, which is information obtained by acquiring representative weather information (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) regarding the weather of the month or the quarter including the month, which is acquired based on the acquired weather data and the stored conversion rule, and associating the information with the total monthly electricity usage information; A total monthly electricity charge information holding step (e) (S0211) performs a process of holding total monthly electricity charge information indicating a total electricity charge for the month, In (S0212), it is determined whether to output one or more of maximum demand power information, maximum electricity usage information, monthly electricity usage information, total monthly electricity usage information, and total monthly electricity charge information. If not, the process proceeds to before (S0201). The information output step (f) (S0213) performs a process of outputting one or more of the above-mentioned pieces of information, which are selected pieces of information. This is an operating method for causing an electric power usage cost analysis device, which is a computer, to execute such a series of processes.

[0126] . <Hardware configuration of embodiment 1> The hardware configuration of the electricity usage cost analysis device in this embodiment will be described with reference to FIG.

[0127] Fig. 3 is a diagram showing the hardware configuration of the electricity usage cost analysis device in the present embodiment 1. As shown in this diagram, the electricity usage cost analysis device in this embodiment includes a "CPU (Central Processing Unit)" that performs various arithmetic processing, a "chipset", a "main memory", a "graphics card", a "non-volatile memory" that holds various programs and data (information), an "I / O controller", a "USB, SATA, LAN terminal, etc.", a "BIOS (UEFI)", a "PCI Express slot", and a "real-time clock". These are then interconnected by a data communication path such as a "system bus" to transmit and receive information and perform processing.

[0128] The various programs and data (information) stored in the non-volatile memory are expanded into the main memory when the device is started up, and upon receiving an execution command, the CPU sequentially executes the programs to perform calculations using the data.

[0129] When the device is started, the various programs and data (information) stored in the "non-volatile memory" are read, expanded, and stored in the "main memory," which also provides a work area for those programs. By receiving execution commands, the "CPU" sequentially executes the programs using the data to perform calculations. Note that multiple addresses are assigned to the "main memory" and "non-volatile memory," and programs executed by the "CPU" can identify and access those addresses to exchange data with each other and perform processing.

[0130] In this embodiment, the programs stored in the "main memory" are a weather data acquisition program (q), a conversion rule storage program (r), one or more of the maximum power demand information storage program (a), the maximum electricity usage information storage program (b), the monthly electricity usage information storage program (c), and the total monthly electricity usage information storage program (d), a total monthly electricity charge information storage program (e), and an information output program (f). In addition, the "main memory" and the "non-volatile memory" store weather data, conversion rules, one or more of the maximum power demand information, the maximum electricity usage information, the monthly electricity usage information, and the total monthly electricity usage information, and total monthly electricity charge information. FIG. 3 shows a case where all the above programs and all the information are stored in the "main memory" and the "non-volatile memory". The following program operation description will be made for a case where all the programs and all the information are stored and functioned as described above. The same effect can be obtained even if the programs and information described as "any one or more" are not all four but one or more.

[0131] "CPU" is The weather data acquisition program (q) stored in the "main memory" is executed to acquire weather data, such as one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, at a predetermined time interval via the Internet line via "USB, SATA, LAN terminal, etc." The conversion rule storage program (r) stored in the "main memory" is executed to store conversion rules, which are rules for converting the acquired weather data, such as temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, based on the acquired weather data, into representative weather information, which is information regarding representative weather for one or more of the demand time period, day, week, month, and quarter (demand time period, day, week, month, and quarter are time lengths equal to or longer than the specified time interval; the same applies below) in which the weather data was observed. The maximum demand power information holding program (a) stored in the "main memory" is executed to hold maximum demand power information, which is information obtained by acquiring and correlating the maximum demand power for the month, the demand time period in which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the demand time period or / the day in which the demand time period is included. A maximum electricity usage information retention program (b) stored in the "main memory" is executed to acquire representative weather information regarding the maximum electricity usage for a day included in the above-mentioned month and the weather (one or more of temperature, humidity, wind speed, sunny, cloudy, rainy, and sunshine hours) for that day and / or the week that includes that day based on the acquired weather data and the stored conversion rule, and then retain maximum electricity usage information which is information associated with this. A monthly electricity usage information retention program (c) stored in the "main memory" is executed to acquire representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including that month based on the electricity usage for the month, the acquired weather data, and the stored conversion rules, and then retain monthly electricity usage information which is information associated with this. A total monthly electricity usage information retention program (d) stored in the "main memory" is executed to retain total monthly electricity usage information, which is information obtained by correlating one or more of the total electricity usage during a specified active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays with representative weather information regarding the weather for the month or the quarter including that month (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and hours of sunshine) obtained based on the obtained weather data and the stored conversion rule. A total monthly electricity charge information holding program (e) stored in the "main memory" is executed to hold total monthly electricity charge information showing the total electricity charge for the month. An information output program (f) stored in the "main memory" is executed to output one or more of the above information via an Internet line through "USB, SATA, LAN terminal, etc.", or via an "I / O controller" or "graphics card" for display on a display, or via "USB, SATA, LAN terminal, etc." for printing on a printer.

[0132] <Effects of the First Embodiment> The power usage cost analysis device of the first embodiment can show information about the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) or information relating the weather information to the total amount of electricity usage during a specified active period or non-active period to the power consumer, so that the power consumer can consider measures to reduce the amount of electricity usage. By reducing the amount of electricity usage, the power consumer's electricity bill (charge amount), which is the power usage cost, can be reduced and environmental friendliness can be improved.

[0133] <Overview of embodiment 2> Mainly claims 2, 11, and 20 The power usage cost analysis device of the second embodiment is configured to further include a monthly electricity usage charge information storage unit (G) for storing monthly electricity usage charge information.

[0134] <Functional configuration of embodiment 2> Fig. 4 shows a functional block diagram of an electric power usage cost analysis device according to a second embodiment based on the first embodiment. In addition to the configuration of the first embodiment, the second embodiment further includes a monthly electricity usage charge information storage unit (G) (0407). Since the components other than the monthly electricity usage charge information storage unit (G) (0407) are the same as those of the first embodiment, only the monthly electricity usage charge information storage unit (G) (0407) will be described.

[0135] <Description of the configuration of embodiment 2> <Second embodiment: Monthly electricity usage charge information storage unit (G) (0407)> The “monthly adaptive electricity usage charge fee information storage unit (G)” (0407) is configured to store adaptive electricity usage charge plan information, which is information indicating a charge plan for a charge that changes according to the amount of electricity usage, and monthly adaptive electricity usage charge fee information, which is information indicating the monthly adaptive electricity usage charge fee.

[0136] The "electricity usage-responsive billing plan information" is information indicating a billing plan for a billing portion that changes according to the electricity usage of an electric power consumer. As described in the first embodiment, the billing system in which an electric power consumer has a contract with an electric power retailer is generally a billing system consisting of a fixed fee portion and a portion that changes according to the electricity usage. The electricity usage-responsive billing plan information is information indicating a billing plan for a billing portion that changes according to the electricity usage in the billing system. For the metered portion that changes according to the electricity usage, the billing can be calculated by multiplying the electricity usage by the unit price. There are several possible unit prices, such as a fixed unit price that does not change depending on the electricity usage, a stepped fixed unit price that has a fixed unit price but changes in several steps depending on the amount of electricity usage, and a unit price that is determined in conjunction with the electricity trading market price (electricity trading market unit price) as in the present invention.

[0137] "Electricity usage-responsive charge" is the charge according to the amount of electricity usage that can be obtained based on the electricity usage-responsive charge plan information and the amount of electricity usage. The charge only for the pay-as-you-go portion of the charge system that changes according to the amount of electricity usage is set as the electricity usage-responsive charge, and information indicating the electricity usage-responsive charge is stored. In the case of a charge system consisting of a fixed charge and a pay-as-you-go charge, the pay-as-you-go charge is set as the electricity usage-responsive charge.

[0138] By retaining information showing the amount of electricity usage charged, which changes according to the amount of electricity usage, it becomes easier to understand the effect of reducing electricity bills when electricity usage is reduced. By making the effect easier to understand, it is possible to increase the motivation of electricity consumers to reduce electricity usage. By reducing electricity usage, it is possible to reduce electricity bills (charges), which are the electricity usage costs of electricity consumers, and also to improve environmental friendliness.

[0139] In addition to the configuration of the second embodiment, the system may be configured to have a monthly adaptive electricity usage charge information acquisition unit that acquires adaptive electricity usage charge plan information, which is information indicating a charge plan for a charge that changes according to the amount of electricity usage, and monthly adaptive electricity usage charge information, which is information indicating the monthly adaptive electricity usage charge fee. In addition to the configuration of the second embodiment, the system may be configured to have a monthly adaptive electricity usage charge information output unit that outputs the stored monthly adaptive electricity usage charge information.

[0140] <Embodiment 2: Operation Method> 5 is a flowchart of an operation method of the power usage cost analysis device of the second embodiment based on the first embodiment. As shown in this figure, the operation method of the power usage cost analysis device of the second embodiment performs a weather data acquisition step (q) (S0501) and a conversion rule storage unit (r) (S0502), performs one or more of a maximum demand power information storage step (a) (S0504), a maximum electricity usage information storage step (b) (S0506), a monthly electricity usage information storage step (c) (S0508), and a total monthly electricity usage information storage step (d) (S0510), performs a total monthly electricity fee information storage step (e) (S0511), a monthly electricity usage charge fee information storage step (g) (S0512), and an information output step (f) (S0514).

[0141] Here, the method of operating the power usage cost analysis device, which is a computer and is an apparatus for analyzing the power usage costs of power consumers in a power supply and demand system based on a billing system in which the amount of charge to the power consumer is determined in advance in conjunction with the power trading market price that fluctuates according to the amount of available power supply that changes depending on the weather, is as follows: The meteorological data acquisition step (q) (S0501) performs a process of acquiring meteorological data, which is one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, at a predetermined time interval; The conversion rule storage step (r) (S0502) performs a process of storing a conversion rule that is a rule for converting the acquired weather data, such as temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine duration, into representative weather information that is information on representative weather of any one or more of the demand time slots, days, weeks, months, and quarters (demand time slots, days, weeks, months, and quarters are time lengths equal to or longer than the predetermined time intervals; the same applies below) in which the weather data was observed, based on the acquired weather data; In (S0503), it is determined whether to execute the maximum demand power information storage step (a) (S0504), and if not, (S0504) is skipped and the process proceeds to before (S0505). The maximum demand power information holding step (a) (S0504) performs a process of holding maximum demand power information, which is information obtained by acquiring the maximum demand power for the month, a demand time period in which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather of the demand time period or / the day including the demand time period (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) and associating the information with the maximum demand power information; In (S0505), it is determined whether to execute the maximum electricity usage information storage step (b) (S0506), and if not, (S0506) is skipped and the process proceeds to before (S0507). The maximum electricity usage information storage step (b) (S0506) performs a process of acquiring representative weather information on the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for a day or / a week including the day based on the maximum electricity usage included in the month, the acquired weather data, and the stored conversion rule, and then storing the maximum electricity usage information associated with the representative weather information; In (S0507), it is determined whether to execute the monthly electricity usage information storage step (c) (S0508), and if not, (S0508) is skipped and the process proceeds to before (S0509). A monthly electricity usage information storage step (c) (S0508) performs a process of acquiring representative weather information on the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including the month based on the monthly electricity usage, the acquired weather data, and the stored conversion rule, and storing monthly electricity usage information which is information associated with the representative weather information; In (S0509), it is determined whether to execute the total monthly electricity usage information storage step (d) (S0510), and if not, (S0510) is skipped and the process proceeds to before (S0511). The total monthly electricity usage information holding step (d) (S0510) performs a process of holding total monthly electricity usage information, which is information obtained by acquiring representative weather information (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) regarding the weather of the month or the quarter including the month, which is acquired based on the acquired weather data and the stored conversion rule, and associating the representative weather information with the total monthly electricity usage information; A total monthly electricity charge information holding step (e) (S0511) performs a process of holding total monthly electricity charge information indicating a total electricity charge for the month, The monthly adaptive electricity usage charge information storage step (g) (S0512) performs a process of storing adaptive electricity usage charge plan information, which is information indicating a charge plan for a charge that changes according to the amount of electricity usage, and monthly adaptive electricity usage charge information, which is information indicating the monthly adaptive electricity usage charge fee, In (S0513), it is determined whether to output one or more of maximum demand power information, maximum electricity usage information, monthly electricity usage information, total monthly electricity usage information, and total monthly electricity charge information. If not, the process proceeds to before (S0501). The information output step (f) (S0514) performs a process of outputting one or more of the above-mentioned pieces of information, which are selected information. This is an operating method for causing an electric power usage cost analysis device, which is a computer, to execute such a series of processes.

[0142] <Hardware Configuration of Second Embodiment> The hardware configuration of the electricity usage cost analysis device in the second embodiment will be described with reference to FIG.

[0143] Fig. 6 is a diagram showing the hardware configuration of an electricity usage cost analysis device in embodiment 2 based on embodiment 1. As shown in this diagram, the electricity usage cost analysis device in this embodiment includes a "CPU (Central Processing Unit)" that performs various calculation processes, a "chipset", a "main memory", a "graphics card", a "non-volatile memory" that stores various programs and data (information), an "I / O controller", a "USB, SATA, LAN terminal, etc.", a "BIOS (UEFI)", a "PCI Express slot", and a "real-time clock". These are then interconnected by a data communication path such as a "system bus" to transmit and receive information and perform processing.

[0144] The various programs and data (information) stored in the non-volatile memory are expanded into the main memory when the device is started up, and upon receiving an execution command, the CPU sequentially executes the programs to perform calculations using the data.

[0145] When the device is started, the various programs and data (information) stored in the "non-volatile memory" are read, expanded, and stored in the "main memory," which also provides a work area for those programs. By receiving execution commands, the "CPU" sequentially executes the programs using the data to perform calculations. Note that multiple addresses are assigned to the "main memory" and "non-volatile memory," and programs executed by the "CPU" can identify and access those addresses to exchange data with each other and perform processing.

[0146] In this embodiment, the programs stored in the "main memory" are a weather data acquisition program (q), a conversion rule storage program (r), one or more of a maximum demand power information storage program (a), a maximum electricity usage information storage program (b), a monthly electricity usage information storage program (c), and a total monthly electricity usage information storage program (d), a total monthly electricity charge information storage program (e), an information output program (f), and a monthly electricity usage charge fee information storage program (g). In addition, the "main memory" and the "non-volatile memory" store weather data, conversion rules, one or more of maximum demand power information, maximum electricity usage information, monthly electricity usage information, and total monthly electricity usage information, total monthly electricity charge information, and monthly electricity usage charge fee information. FIG. 6 shows a case where all the above programs and all the information are stored in the "main memory" and the "non-volatile memory". The following operation of the programs will be described for a case where all the programs and all the information are stored and functioned as described above. The same effect can be obtained even if the programs and information described as "any one or more" refer to one or more but not all four.

[0147] "CPU" is The weather data acquisition program (q) stored in the "main memory" is executed to acquire weather data, such as one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, at a predetermined time interval via the Internet line via "USB, SATA, LAN terminal, etc." The conversion rule storage program (r) stored in the "main memory" is executed to store conversion rules, which are rules for converting the acquired weather data, such as temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, based on the acquired weather data, into representative weather information, which is information regarding representative weather for one or more of the demand time period, day, week, month, and quarter (demand time period, day, week, month, and quarter are time lengths equal to or longer than the specified time interval; the same applies below) in which the weather data was observed. The maximum demand power information holding program (a) stored in the "main memory" is executed to hold maximum demand power information, which is information obtained by acquiring and correlating the maximum demand power for the month, the demand time period in which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the demand time period or / the day in which the demand time period is included. A maximum electricity usage information retention program (b) stored in the "main memory" is executed to acquire representative weather information regarding the maximum electricity usage for a day included in the above-mentioned month and the weather (one or more of temperature, humidity, wind speed, sunny, cloudy, rainy, and sunshine hours) for that day and / or the week that includes that day based on the acquired weather data and the stored conversion rule, and then retain maximum electricity usage information which is information associated with this. A monthly electricity usage information retention program (c) stored in the "main memory" is executed to acquire representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including that month based on the electricity usage for the month, the acquired weather data, and the stored conversion rules, and then retain monthly electricity usage information which is information associated with this. A total monthly electricity usage information retention program (d) stored in the "main memory" is executed to retain total monthly electricity usage information, which is information obtained by correlating one or more of the total electricity usage during a specified active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays with representative weather information regarding the weather for the month or the quarter including that month (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and hours of sunshine) obtained based on the obtained weather data and the stored conversion rule. A total monthly electricity charge information holding program (e) stored in the "main memory" is executed to hold total monthly electricity charge information showing the total electricity charge for the month. The monthly adaptive electricity usage charge fee information retention program (g) stored in the "main memory" is executed to retain adaptive electricity usage charge plan information, which is information indicating a charge plan for charges that change according to electricity usage, and monthly adaptive electricity usage charge fee information, which is information indicating the adaptive electricity usage charge fee for the month. An information output program (f) stored in the "main memory" is executed to output one or more of the above information via an Internet line through "USB, SATA, LAN terminal, etc.", or via an "I / O controller" or "graphics card" for display on a display, or via "USB, SATA, LAN terminal, etc." for printing on a printer.

[0148] <Effects of the second embodiment> In addition to the effects of the first embodiment, the power usage cost analysis device of the second embodiment holds information on a billing plan based on the amount of electricity usage, making it easier to understand the effect of reducing electricity charges when electricity usage is reduced. By making the effect easier to understand, it is possible to increase the motivation of electricity consumers to reduce electricity usage. By reducing electricity usage, it is possible to reduce the electricity charges (billing amount), which are the electricity usage costs of the electricity consumers, and also to improve environmental friendliness.

[0149] <Overview of embodiment 3> Mainly claims 3, 12, and 21 The electricity usage cost analysis device of embodiment 3 is further configured to have a comparison unit (H) that compares one or more of the stored maximum demand electricity information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information for a different day, month, year, or equivalent period of a different year.

[0150] <Functional configuration of embodiment 3> Fig. 7 shows a functional block diagram of an electric power usage cost analysis device of embodiment 3 based on either embodiment 1 or embodiment 2. The electric power usage cost analysis device of embodiment 3 based on embodiment 1 further includes a comparison unit (H) (0708). Since the components other than the comparison unit (H) (0708) are the same as embodiment 1, only the comparison unit (H) (0708) will be described. Note that the same effects can be obtained even when embodiment 2 is used as a base.

[0151] <Description of the configuration of embodiment 3> <Embodiment 3 Comparison Unit (H) (0708)> The “comparison unit (H)” (0708) is configured to compare one or more of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information for a different period of a day, a month, a year, or a different year.

[0152] "A different equivalent period corresponding to that information" refers to a period of similar length corresponding to one or more of the three types of information held, such as the demand time period when the maximum demand power occurred in a different month, the day when the maximum electricity usage occurred in a different month, or another month, for the maximum demand power information, maximum electricity usage information, and monthly electricity usage information.

[0153] For example, the demand time period during which the maximum power demand occurred last month is compared with the demand time period during which the maximum power demand occurred this month. Since weather information is associated with the corresponding maximum power demand information, the time and weather information for the demand time periods during the previous month and this month are compared. By comparing, it is possible to understand whether the power demand was maximum during a similar time period and weather, whether it was maximum during the same time period but with different weather, or whether it was maximum during a different time period. If it was maximum during the same time period and weather, it is possible to determine the cause, such as weather (electricity used for air conditioning because it is hot or cold) or because it was the time period when activity is most active. If the weather is different during the same time period, it is possible to determine the cause of the maximum power demand by referring to weather information such as the weather (sunny, cloudy, rainy, etc.) and temperature. If it was maximum during a different time period, it is possible to determine the cause by looking back at weather factors and the activities of the power consumer himself.

[0154] In another example, by comparing the maximum electricity usage information with the day last month when the maximum electricity usage occurred and its weather information, and the day this month when the maximum electricity usage occurred and its weather information, it is possible to understand the factors that caused the maximum electricity usage, such as whether the day was a weekday or a holiday, whether the weather was high or low in temperature, or whether it was sunny. In another example, by comparing the monthly electricity usage information with the electricity usage this month and the same month last year, including weather information, it is possible to understand the factors that caused the maximum electricity usage. Understanding the factors that caused the maximum electricity usage can help power consumers who receive the information output from the information output unit (F) find ways to reduce electricity usage.

[0155] By comparing with corresponding information for a corresponding period in this manner, the power consumer can ascertain the cause of the maximum power demand or maximum electricity usage. Also, by comparing the monthly electricity usage in question with other monthly electricity usage in a corresponding period, the power consumer can ascertain the cause of the monthly electricity usage. Based on the obtained information on the causes, measures can be taken in future electricity usage to reduce the maximum power demand or maximum electricity usage or monthly electricity usage, thereby reducing electricity bills. Examples of measures include limiting the appliances that use electricity, updating to equipment that consumes less electricity, and shifting activities to times when electricity rates are cheaper.

[0156] By comparing with other periods, electricity consumers can easily consider measures to reduce their electricity usage. By reducing electricity usage, it is possible to reduce electricity charges (billing amounts), which are the electricity usage costs for electricity consumers, and also to improve environmental friendliness.

[0157] <Embodiment 3 Comparison Unit (H): Configuration Example When Using Comparison Rules> The comparison unit (H) can be configured to make the comparison based on a comparison rule that defines how to make the comparison. This can be achieved by configuring as follows: The power usage cost analysis device further includes a comparison rule storage unit that stores a comparison rule, which is a rule for comparing one or more of the stored maximum power demand information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information in a different period of one day, one month, one year, or a different year, and the comparison unit (H) compares one or more of the stored maximum power demand information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information in a different period of one day, one month, one year, or a different year, based on the stored comparison rule.

[0158] <Embodiment 3 Comparison Unit (H): Configuration Example for Specifying Information to be Compared> Furthermore, the system may be configured to acquire information for specifying which information to compare when making a comparison. To this end, the system may be configured to further include a comparison target designation information acquisition unit that acquires comparison target designation information, which is information that designates one or more of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information, as the information to be compared.

[0159] <Embodiment 3: Operation Method> Fig. 8 is a flowchart of the operation method of the power usage cost analysis device of the third embodiment based on the first embodiment. As shown in this figure, the operation method of the power usage cost analysis device of the third embodiment performs a weather data acquisition step (q) (S0801) and a conversion rule storage step (r) (S0802), performs one or more of a maximum demand power information storage step (a) (S0804), a maximum electricity usage information storage step (b) (S0806), a monthly electricity usage information storage step (c) (S0808), and a total monthly electricity usage information storage step (d) (S0810), performs a total monthly electricity fee information storage step (e) (S0811), a comparison step (h) (S0812), and an information output step (f) (S0814). The same effect can be obtained even if the second embodiment is used as a base.

[0160] Here, the method of operating the power usage cost analysis device, which is a computer and is an apparatus for analyzing the power usage costs of power consumers in a power supply and demand system based on a billing system in which the amount of charge to the power consumer is determined in advance in conjunction with the power trading market price that fluctuates according to the amount of available power supply that changes depending on the weather, is as follows: The meteorological data acquisition step (q) (S0801) performs a process of acquiring meteorological data, which is one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, at a predetermined time interval; A conversion rule storage step (r) (S0802) performs a process of storing a conversion rule that is a rule for converting the acquired weather data, which are temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine duration, into representative weather information that is information on representative weather of any one or more of the demand time slot, day, week, month, and quarter (demand time slot, day, week, month, and quarter are time lengths equal to or longer than the predetermined time interval; the same applies below) in which the weather data was observed, based on the acquired weather data; In (S0803), it is determined whether to execute the maximum demand power information storage step (a) (S0804), and if not, (S0804) is skipped and the process proceeds to before (S0805). The maximum demand power information holding step (a) (S0804) performs a process of holding maximum demand power information, which is information obtained by acquiring the maximum demand power for the month, a demand time period in which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather of the demand time period or / the day including the demand time period (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) and associating the information with the maximum demand power information; In (S0805), it is determined whether to execute the maximum electricity usage information storage step (b) (S0806), and if not, (S0806) is skipped and the process proceeds to before (S0807). The maximum electricity usage information storage step (b) (S0806) performs a process of acquiring representative weather information on the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for a day or / a week including the day based on the maximum electricity usage included in the month, the acquired weather data, and the stored conversion rule, and then storing the maximum electricity usage information associated with the representative weather information; In (S0807), it is determined whether to execute the monthly electricity usage information storage step (c) (S0808), and if not, (S0808) is skipped and the process proceeds to before (S0809). A monthly electricity usage information storage step (c) (S0808) performs a process of acquiring representative weather information on the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including the month based on the monthly electricity usage, the acquired weather data, and the stored conversion rule, and then storing monthly electricity usage information which is information associated with the representative weather information; In (S0809), it is determined whether to execute the step (d) (S0810) of storing the total monthly electricity usage information. If not, (S0810) is skipped and the process proceeds to before (S0811). The total monthly electricity usage information storage step (d) (S0810) performs a process of storing total monthly electricity usage information, which is information obtained by acquiring representative weather information (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including the month based on one or more of the total electricity usage during a predetermined active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays, based on the acquired weather data and the stored conversion rule, and associating the representative weather information with the weather information; A total monthly electricity charge information holding step (e) (S0811) performs a process of holding total monthly electricity charge information indicating a total electricity charge for the month, A comparison step (h) (S0812) performs a process of comparing one or more of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information for a different day, month, year, or different year corresponding to the information; In (S0813), it is determined whether to output one or more of maximum demand power information, maximum electricity usage information, monthly electricity usage information, total monthly electricity usage information, and total monthly electricity charge information. If not, the process proceeds to before (S0801). The information output step (f) (S0814) performs a process of outputting one or more of the above-mentioned pieces of information, which are selected information. This is an operating method for causing the power usage cost analysis device, which is a computer, to execute such a series of processes.

[0161] <Embodiment 3: Hardware Configuration> The hardware configuration of the electricity usage cost analysis device in the third embodiment will be described with reference to FIG.

[0162] FIG. 9 is a diagram showing the hardware configuration of an electric power usage cost analysis device in the third embodiment based on the first embodiment. As shown in this diagram, the electric power usage cost analysis device in this embodiment includes a "CPU (Central Processing Unit)" that performs various arithmetic processing, a "chipset", a "main memory", a "graphics card", a "non-volatile memory" that stores various programs and data (information), an "I / O controller", a "USB, SATA, LAN terminal, etc.", a "BIOS (UEFI)", a "PCI Express slot", and a "real-time clock". These are connected to each other by a data communication path such as a "system bus" to transmit and receive information and perform processing. The same effect can be obtained even if the second embodiment is used as a base.

[0163] The various programs and data (information) stored in the non-volatile memory are expanded into the main memory when the device is started up, and upon receiving an execution command, the CPU sequentially executes the programs to perform calculations using the data.

[0164] When the device is started, the various programs and data (information) stored in the "non-volatile memory" are read, expanded, and stored in the "main memory," which also provides a work area for those programs. By receiving execution commands, the "CPU" sequentially executes the programs using the data to perform calculations. Note that multiple addresses are assigned to the "main memory" and "non-volatile memory," and programs executed by the "CPU" can identify and access those addresses to exchange data with each other and perform processing.

[0165] In this embodiment, the programs stored in the "main memory" are a weather data acquisition program (q), a conversion rule storage program (r), one or more of the maximum demand power information storage program (a), the maximum electricity usage information storage program (b), the monthly electricity usage information storage program (c), and the total monthly electricity usage information storage program (d), a total monthly electricity charge information storage program (e), an information output program (f), and a comparison program (h). In addition, the "main memory" and the "non-volatile memory" store weather data, conversion rules, one or more of the maximum demand power information, the maximum electricity usage information, the monthly electricity usage information, and the total monthly electricity usage information, and total monthly electricity charge information. FIG. 9 shows a case where all the above programs and all the information are stored in the "main memory" and the "non-volatile memory". The following program operation description will be made for a case where all the programs and all the information are stored and functioned as described above. The same effect can be obtained even if the programs and information described as "any one or more" are not all four but one or more.

[0166] "CPU" is The weather data acquisition program (q) stored in the "main memory" is executed to acquire weather data, such as one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, at a predetermined time interval via the Internet line via "USB, SATA, LAN terminal, etc." The conversion rule storage program (r) stored in the "main memory" is executed to store conversion rules, which are rules for converting the acquired weather data, such as temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, based on the acquired weather data, into representative weather information, which is information regarding representative weather for one or more of the demand time period, day, week, month, and quarter (demand time period, day, week, month, and quarter are time lengths equal to or longer than the specified time interval; the same applies below) in which the weather data was observed. The maximum demand power information holding program (a) stored in the "main memory" is executed to hold maximum demand power information, which is information obtained by acquiring and correlating the maximum demand power for the month, the demand time period in which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the demand time period or / the day in which the demand time period is included. A maximum electricity usage information retention program (b) stored in the "main memory" is executed to acquire representative weather information regarding the maximum electricity usage for a day included in the above-mentioned month and the weather (one or more of temperature, humidity, wind speed, sunny, cloudy, rainy, and sunshine hours) for that day and / or the week that includes that day based on the acquired weather data and the stored conversion rule, and then retain maximum electricity usage information which is information associated with this. A monthly electricity usage information retention program (c) stored in the "main memory" is executed to acquire representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including that month based on the electricity usage for the month, the acquired weather data, and the stored conversion rules, and then retain monthly electricity usage information which is information associated with this. A total monthly electricity usage information retention program (d) stored in the "main memory" is executed to retain total monthly electricity usage information, which is information obtained by correlating one or more of the total electricity usage during a specified active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays with representative weather information regarding the weather for the month or the quarter including that month (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and hours of sunshine) obtained based on the obtained weather data and the stored conversion rule. A total monthly electricity charge information holding program (e) stored in the "main memory" is executed to hold total monthly electricity charge information showing the total electricity charge for the month. A comparison program (h) stored in the "main memory" is executed to compare one or more of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information for a different period of a day, month, year, or year. An information output program (f) stored in the "main memory" is executed to output one or more of the above information via an Internet line through "USB, SATA, LAN terminal, etc.", or via an "I / O controller" or "graphics card" for display on a display, or via "USB, SATA, LAN terminal, etc." for printing on a printer.

[0167] <Effects of the Third Embodiment> In addition to the effects of the first embodiment, the power usage cost analysis device of the third embodiment can compare one or more of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information in a different day, month, year, or different year corresponding to the information, thereby understanding the cause of the maximum electricity usage and helping the power consumer to obtain a measure to reduce the electricity usage. By reducing the electricity usage, the electricity bill (charge amount), which is the power usage cost of the power consumer, can be reduced and environmental friendliness can be improved.

[0168] <Overview of embodiment 4> Mainly claims 4, 13, and 22 The electricity usage cost analysis device of embodiment 4, which is based on embodiment 3, is configured in the comparison unit (H) to further include a superiority / inferiority judgment means (J) for each specified demand time period that makes a superiority / inferiority judgment, which is a judgment showing the superiority / inferiority of the same specified demand time period (compared to the previous day, week, month, last year, etc.) from the perspective of electricity consumption efficiency for each electricity consumer.

[0169] <Functional Configuration of Fourth Embodiment> Fig. 10 shows a functional block diagram of an electric power usage cost analysis device of embodiment 4 based on embodiment 3. The electric power usage cost analysis device of embodiment 4 based on embodiment 3 further has a superiority / inferiority determination means (J) (1009) for each predetermined demand time slot in the comparison unit (H) (1008). Since everything other than the superiority / inferiority determination means (J) (1009) for each predetermined demand time slot is the same as embodiment 3, only the superiority / inferiority determination means (J) (1009) for each predetermined demand time slot will be explained.

[0170] <Description of the Configuration of the Fourth Embodiment> <Fourth embodiment: Means for determining superiority / inferiority of each demand time period (J) (1009)> The "means for determining superiority / inferiority for each specified demand time period (J)" (1009) is configured within the comparison unit (H) (1008) so as to make a superiority / inferiority determination, which is a determination showing superiority / inferiority for each specified demand time period (compared to the previous day, the previous week, the previous month, last year, etc.) from the standpoint of power consumption efficiency for each power consumer.

[0171] "Power consumption efficiency" refers to, for example, the amount of electricity used (demanded power) during each demand time period, and the lower the amount, the better the power consumption efficiency. Or, for example, even if the amount of electricity used during a demand time period is the same, a time period with a low electricity rate can be considered to have better power consumption efficiency than a demand time period with a high electricity rate, and so on.

[0172] A "predetermined demand time period" may be a demand time period at a specific time, such as from 12:00 to 12:30, or may mean a series of multiple demand time periods from a specific start time to an end time.

[0173] For example, if the demand time period with the highest demand for this month is 14:00-14:30 on the 10th, a judgment is made to show the superiority or inferiority of the power consumption efficiency based on the demand power and weather information for the demand time period from 14:00-14:30 on the previous day, the demand time period from 14:00-14:30 on the same day of the previous week, the demand time period from 14:00-14:30 on the 10th of the previous month, and the demand time period from 14:00-14:30 on the 10th of the same month last year. By making the judgment, the power consumer can be made aware of the superiority or inferiority of the power consumption efficiency in similar demand time periods, and can investigate the reason for the superiority or inferiority, thereby reducing the power demand and reducing the electricity bill. By reducing the demand power and reducing the amount of electricity used, the electricity bill (charged amount), which is the power usage cost of the power consumer, can be reduced, and environmental friendliness can be improved. Note that the same predetermined demand time period is not limited to the unit demand time period as described above, but may be a plurality of consecutive demand time periods from a specific start time to an end time.

[0174] A demand time slot power demand information holding unit may be provided that holds information indicating the amount of electricity used (demanded power) per demand time slot of a certain power consumer.

[0175] The comparison unit (H) may further include a means for storing rules for determining superiority / inferiority for each predetermined demand time slot, which is a rule for determining superiority / inferiority for a certain power consumer, for each of the same predetermined demand time slots (compared to the previous day, week, month, last year, etc.) in terms of power consumption efficiency. The rules for determining superiority / inferiority for each predetermined demand time slot may include, for example, a method for defining power consumption efficiency, a method for selecting a comparison target (compared to the previous day, week, month, last year, etc.), and a criterion for determining superiority / inferiority. For example, a rule for determining superiority / inferiority for each predetermined demand time slot may be a rule for comparing the amount of electricity consumption during the demand time slots from 14:00 to 14:30 on Mondays of the previous week and this week in terms of power consumption efficiency, and judging the one with the lower amount of electricity consumption as superior. Possible rules include a rule that determines that the lower electricity rate during the relevant demand time period is better if the amount of electricity used is the same, or a rule that determines that the better option is one where the temperature during the relevant demand time period is not between 20°C and 27°C, which is a range that can be tolerated without operating air conditioning, even if the amount of electricity used is the same.

[0176] In this embodiment 4, for example, a comparison can be made between the electricity consumption of a certain electricity consumer during the same demand time period on the current day and the previous day, or the electricity consumption for the same length of time during the day and night on one day (or on a different day).

[0177] <Embodiment 4: Operation Method> Fig. 11 is a flowchart of an operation method of the power usage cost analysis device of embodiment 4 based on embodiment 3. As shown in this figure, the operation method of the power usage cost analysis device of embodiment 4 performs a weather data acquisition step (q) (S1101) and a conversion rule storage step (r) (S1102), performs one or more of a maximum demand power information storage step (a) (S1104), a maximum electricity usage information storage step (b) (S1106), a monthly electricity usage information storage step (c) (S1108), and a total monthly electricity usage information storage step (d) (S1110), performs a total monthly electricity charge information storage step (e) (S1111), a comparison step (h) (S1112), a superiority / inferiority judgment substep (j) (S1113) for each predetermined demand time period within the comparison step (h) (S1112), and an information output step (f) (S1115).

[0178] Here, the method of operating the power usage cost analysis device, which is a computer and is an apparatus for analyzing the power usage costs of power consumers in a power supply and demand system based on a billing system in which the amount of charge to the power consumer is determined in advance in conjunction with the power trading market price that fluctuates according to the amount of available power supply that changes depending on the weather, is as follows: The meteorological data acquisition step (q) (S1101) performs a process of acquiring meteorological data, which is one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, at a predetermined time interval; The conversion rule storage step (r) (S1102) performs a process of storing a conversion rule that is a rule for converting the acquired weather data, which are temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine duration, into representative weather information that is information on representative weather of any one or more of the demand time slot, day, week, month, and quarter (demand time slot, day, week, month, and quarter are time lengths equal to or longer than the predetermined time interval; the same applies below) in which the weather data was observed, based on the acquired weather data; In (S1103), it is determined whether to execute the maximum demand power information storing step (a) (S1104), and if not, (S1104) is skipped and the process proceeds to before (S1105). The maximum demand power information holding step (a) (S1104) performs a process of holding maximum demand power information, which is information relating to the maximum demand power for the month, the demand time period during which the maximum demand power occurred, and information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) of the demand time period or / the day including the demand time period; In (S1105), it is determined whether to execute the maximum electricity usage information storage step (b) (S1106), and if not, (S1106) is skipped and the process proceeds to before (S1107). The maximum electricity usage information storage step (b) (S1106) performs a process of storing maximum electricity usage information, which is information that associates the maximum electricity usage of one day included in the month with information on the weather of that day or / and the week that includes that day (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours); In (S1107), it is determined whether to execute the monthly electricity usage information storage step (c) (S1108), and if not, (S1108) is skipped and the process proceeds to before (S1109). A monthly electricity usage information storage step (c) (S1108) performs a process of storing monthly electricity usage information that associates the monthly electricity usage with information on the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including that month; In (S1109), it is determined whether to execute the total monthly electricity usage information storage step (d) (S1110), and if not, (S1110) is skipped and the process proceeds to before (S1111). The total monthly electricity usage information holding step (d) (S1110) performs processing to hold total monthly electricity usage information, which is information relating one or more of the total electricity usage during a predetermined active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays, and information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including that month; A total monthly electricity charge information holding step (e) (S1111) performs a process of holding total monthly electricity charge information indicating a total electricity charge for the month, A comparison step (h) (S1112) performs a process of comparing one or more of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information for a different day, month, year, or different year corresponding to the information; A sub-step (j) (S1113) of judging the superiority or inferiority of each predetermined demand time period in the comparison step (h) (S1112) performs a process of judging the superiority or inferiority of each predetermined demand time period (compared to the previous day, the previous week, the previous month, the previous year, etc.) from the viewpoint of power consumption efficiency for each power consumer, In (S1114), it is determined whether to output one or more of maximum demand power information, maximum electricity usage information, monthly electricity usage information, total monthly electricity usage information, and total monthly electricity charge information. If not, the process proceeds to before (S1101). The information output step (f) (S1115) performs a process of outputting one or more of the above-mentioned pieces of information, which are selected pieces of information. This is an operating method for causing an electric power usage cost analysis device, which is a computer, to execute such a series of processes.

[0179] <Embodiment 4: Hardware Configuration> The hardware configuration of the electricity usage cost analysis device in the fourth embodiment will be described with reference to FIG.

[0180] Fig. 12 is a diagram showing the hardware configuration of an electricity usage cost analysis device in embodiment 4 based on embodiment 3. As shown in this diagram, the electricity usage cost analysis device in this embodiment includes a "CPU (Central Processing Unit)" that performs various calculation processes, a "chipset", a "main memory", a "graphics card", a "non-volatile memory" that holds various programs and data (information), an "I / O controller", a "USB, SATA, LAN terminal, etc.", a "BIOS (UEFI)", a "PCI Express slot", and a "real-time clock". These are then interconnected by a data communication path such as a "system bus" to transmit and receive information and perform processing.

[0181] The various programs and data (information) stored in the non-volatile memory are expanded into the main memory when the device is started up, and upon receiving an execution command, the CPU sequentially executes the programs to perform calculations using the data.

[0182] When the device is started, the various programs and data (information) stored in the "non-volatile memory" are read, expanded, and stored in the "main memory," which also provides a work area for those programs. By receiving execution commands, the "CPU" sequentially executes the programs using the data to perform calculations. Note that multiple addresses are assigned to the "main memory" and "non-volatile memory," and programs executed by the "CPU" can identify and access those addresses to exchange data with each other and perform processing.

[0183] In this embodiment, the programs stored in the "main memory" are a weather data acquisition program (q), a conversion rule storage program (r), one or more of a maximum demand power information storage program (a), a maximum electricity usage information storage program (b), a monthly electricity usage information storage program (c), and a total monthly electricity usage information storage program (d), a total monthly electricity charge information storage program (e), an information output program (f), a comparison program (h), and a subprogram (j) for determining superiority or inferiority for each predetermined demand time period. In addition, the "main memory" and the "non-volatile memory" store weather data, conversion rules, one or more of maximum demand power information, maximum electricity usage information, monthly electricity usage information, and total monthly electricity usage information, and total monthly electricity charge information. FIG. 12 shows a case where all the above programs and all the information are stored in the "main memory" and the "non-volatile memory". The following operation of the programs will be described for a case where all the programs and all the information are stored and functioned as described above. The same effect can be obtained even if the programs and information described as "any one or more" refer to one or more but not all four.

[0184] "CPU" is The weather data acquisition program (q) stored in the "main memory" is executed to acquire weather data, such as one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, at a predetermined time interval via the Internet line via "USB, SATA, LAN terminal, etc." The conversion rule storage program (r) stored in the "main memory" is executed to store conversion rules, which are rules for converting the acquired weather data, such as temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, based on the acquired weather data, into representative weather information, which is information regarding representative weather for one or more of the demand time period, day, week, month, and quarter (demand time period, day, week, month, and quarter are time lengths equal to or longer than the specified time interval; the same applies below) in which the weather data was observed. The maximum demand power information holding program (a) stored in the "main memory" is executed to hold maximum demand power information, which is information obtained by acquiring and correlating the maximum demand power for the month, the demand time period in which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the demand time period or / the day in which the demand time period is included. A maximum electricity usage information retention program (b) stored in the "main memory" is executed to acquire representative weather information regarding the maximum electricity usage for a day included in the above-mentioned month and the weather (one or more of temperature, humidity, wind speed, sunny, cloudy, rainy, and sunshine hours) for that day and / or the week that includes that day based on the acquired weather data and the stored conversion rule, and then retain maximum electricity usage information which is information associated with this. A monthly electricity usage information retention program (c) stored in the "main memory" is executed to acquire representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including that month based on the electricity usage for the month, the acquired weather data, and the stored conversion rules, and then retain monthly electricity usage information which is information associated with this. A total monthly electricity usage information retention program (d) stored in the "main memory" is executed to retain total monthly electricity usage information, which is information obtained by correlating one or more of the total electricity usage during a specified active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays with representative weather information regarding the weather for the month or the quarter including that month (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and hours of sunshine) obtained based on the obtained weather data and the stored conversion rule. A total monthly electricity charge information holding program (e) stored in the "main memory" is executed to hold total monthly electricity charge information showing the total electricity charge for the month. A comparison program (h) stored in the "main memory" is executed to compare one or more of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information for a different period of a day, month, year, or year. A subprogram (j) for determining superiority / inferiority for each specified demand time period stored in the "main memory" is executed to perform a superiority / inferiority determination, which is a determination showing superiority / inferiority for each specified demand time period (compared to the previous day, the previous week, the previous month, last year, etc.) from the perspective of power consumption efficiency for each power consumer. An information output program (f) stored in the "main memory" is executed to output one or more of the above information via an Internet line through "USB, SATA, LAN terminal, etc.", or via an "I / O controller" or "graphics card" for display on a display, or via "USB, SATA, LAN terminal, etc." for printing on a printer.

[0185] <Effects of the fourth embodiment> In addition to the effects of the third embodiment, the power usage cost analysis device of the fourth embodiment judges the superiority or inferiority of the power consumption efficiency for each power consumer for the same predetermined demand time period (compared to the previous day, week, month, last year, etc.) from the viewpoint of power consumption efficiency, thereby making the power consumer aware of the superiority or inferiority of the power consumption efficiency in the same demand time period, and by making the reason for the superiority or inferiority judgment clear, it is possible to reduce the power demand and reduce the electricity bill. By reducing the amount of electricity usage, it is possible to reduce the electricity bill (charged amount), which is the power usage cost of the power consumer, and also to improve environmental friendliness.

[0186] <Overview of embodiment 5> Mainly claims 5, 14, and 23 The electricity usage cost analysis device of embodiment 5, which is based on either embodiment 3 or embodiment 4, is configured in the comparison unit (H) to further have an electricity consumer superiority / inferiority determination means (K) for making a superiority / inferiority determination, which is a determination showing superiority / inferiority between different electricity consumer from the standpoint of electricity consumption efficiency for each specified demand time period.

[0187] <Functional configuration of embodiment 5> Fig. 13 shows a functional block diagram of an electric power usage cost analysis device of embodiment 5 based on embodiment 3. The electric power usage cost analysis device of embodiment 5 based on embodiment 3 further has an electric power consumer superiority / inferiority determination means (K) (1310) in the comparison unit (H) (1308). Since everything except the electric power consumer superiority / inferiority determination means (K) (1310) is the same as embodiment 3, only the electric power consumer superiority / inferiority determination means (K) (1310) will be explained. Note that the same effect can be obtained even if embodiment 4 is used as a base.

[0188] <Description of the configuration of embodiment 5> <Fifth embodiment: Means for determining superiority or inferiority among electric power consumers (K) (1310)> The "means for determining superiority / inferiority between power consumers (K)" (1310) is configured within the comparison unit (H) (1308) so as to make a superiority / inferiority determination, which is a determination showing superiority / inferiority between different power consumers from the standpoint of power consumption efficiency for each specified demand time period.

[0189] In the fifth embodiment, unlike the configuration of the fourth embodiment, a plurality of different power consumers are compared from the viewpoint of power consumption efficiency for a predetermined demand time period. The amount of electricity used during a demand time period of a specific predetermined length (which may be one unit length or may be multiple consecutive unit lengths) is compared. For example, the amount of electricity used during the demand time period from 14:00 to 14:30 last Monday is used as the power consumption rate, and the different power consumers are compared to determine which is better. The number of different power consumers to be compared may be two or more, and is not limited to two.

[0190] For electricity consumers, comparing their power consumption efficiency with that of other different electricity consumers and judging which is better or worse provides an opportunity to reflect on their own power consumption efficiency. If their own power consumption efficiency is poor, they can look for ways to improve it from information about other electricity consumers. Conversely, if their own power consumption efficiency is good, they can look for reasons why other electricity consumers were poor and use them as examples to prevent their own power consumption efficiency from deteriorating and get a clue for improvement. If power consumption efficiency can be improved in this way and electricity consumption can be reduced, it is possible to reduce the electricity bill (charge), which is the cost of electricity usage for electricity consumers, and it is also possible to improve environmental friendliness.

[0191] <Fifth embodiment: Means for determining superiority or inferiority between power consumers (K): Power consumer comparison attributes> For this purpose, it is advisable to select the different electricity consumers to be compared based on comparison attributes that are likely to have similar electricity consumption, such as similar industries, similar business scales, similar numbers of employees, similar regions (temperature, wind power, hours of sunlight, etc.), and for ordinary households, similar house structures (detached houses, condominiums, apartments), family structures, addresses, occupations, etc. For example, it is natural that the demand power and electricity consumption efficiency for each demand period will be different between a factory that operates 24 hours a day and an ordinary household.

[0192] <Embodiment 5: Operation Method> Fig. 14 is a flowchart of an operation method of the power usage cost analysis device of embodiment 5 based on embodiment 3. As shown in this figure, the operation method of the power usage cost analysis device of embodiment 5 performs a weather data acquisition step (q) (S1401) and a conversion rule storage step (r) (S1402), performs one or more of a maximum demand power information storage step (a) (S1404), a maximum electricity usage information storage step (b) (S1406), a monthly electricity usage information storage step (c) (S1408), and a total monthly electricity usage information storage step (d) (S1410), performs a total monthly electricity charge information storage step (e) (S1411), a comparison step (h) (S1412), a substep (k) (S1413) of determining superiority or inferiority among power consumers in the comparison step (h) (S1412), and an information output step (f) (S1415). The same effect can be obtained even if the fourth embodiment is used as a base.

[0193] Here, the method of operating the power usage cost analysis device, which is a computer and is an apparatus for analyzing the power usage costs of power consumers in a power supply and demand system based on a billing system in which the amount of charge to the power consumer is determined in advance in conjunction with the power trading market price that fluctuates according to the amount of available power supply that changes depending on the weather, is as follows: The meteorological data acquisition step (q) (S1401) performs a process of acquiring meteorological data, which is one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, at a predetermined time interval; The conversion rule storage step (r) (S1402) performs a process of storing a conversion rule that is a rule for converting the acquired weather data, such as temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine duration, into representative weather information that is information on representative weather of any one or more of the demand time slot, day, week, month, and quarter (demand time slot, day, week, month, and quarter are time lengths equal to or longer than the predetermined time interval; the same applies below) in which the weather data was observed, based on the acquired weather data; In step S1403, it is determined whether to execute the maximum demand power information storing step (a) (S1404). If not, step S1404 is skipped and the process proceeds to step S1405. The maximum demand power information holding step (a) (S1404) performs a process of holding maximum demand power information, which is information obtained by acquiring the maximum demand power for the month, a demand time period in which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather of the demand time period or / the day including the demand time period (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours), and associating the information with the maximum demand power information; In (S1405), it is determined whether or not to execute the maximum electricity usage information storage step (b) (S1406). If not, (S1406) is skipped and the process proceeds to before (S1407). The maximum electricity usage information storage step (b) (S1406) performs a process of acquiring representative weather information on the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for a day or / a week including the day based on the maximum electricity usage included in the month, the acquired weather data, and the stored conversion rule, and then storing the maximum electricity usage information associated with the representative weather information; In (S1407), it is determined whether to execute the monthly electricity usage information storage step (c) (S1408), and if not, (S1408) is skipped and the process proceeds to before (S1409). A monthly electricity usage information storage step (c) (S1408) performs a process of acquiring representative weather information on the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including the month based on the monthly electricity usage, the acquired weather data, and the stored conversion rule, and storing monthly electricity usage information which is information associated with the representative weather information; In (S1409), it is determined whether or not to execute the step (d) (S1410) of storing the total monthly electricity usage information. If not, (S1410) is skipped and the process proceeds to before (S1411). The total monthly electricity usage information storage step (d) (S1410) performs a process of storing total monthly electricity usage information, which is information obtained by acquiring representative weather information (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including the month based on one or more of the total electricity usage during a predetermined active time period, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays for the month, and the acquired weather data and the stored conversion rule, and associating the representative weather information with the representative weather information; A total monthly electricity charge information holding step (e) (S1411) performs a process of holding total monthly electricity charge information indicating a total electricity charge for the month, A comparison step (h) (S1412) performs a process of comparing one or more of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information for a different day, month, year, or different year corresponding to the information; The sub-step (k) (S1413) of determining superiority or inferiority between power demanders in the comparison step (h) (S1412) performs a process of determining superiority or inferiority between different power demanders in terms of power consumption efficiency for each predetermined demand time period, In (S1414), it is determined whether to output one or more of maximum demand power information, maximum electricity usage information, monthly electricity usage information, total monthly electricity usage information, and total monthly electricity charge information. If not, the process proceeds to before (S1401). The information output step (f) (S1415) performs a process of outputting one or more of the above-mentioned pieces of information, which are selected pieces of information. This is an operating method for causing an electric power usage cost analysis device, which is a computer, to execute such a series of processes.

[0194] <Fifth embodiment: Hardware configuration> The hardware configuration of the electricity usage cost analysis device in the fifth embodiment will be described with reference to FIG.

[0195] FIG. 15 is a diagram showing the hardware configuration of an electric power usage cost analysis device in the present embodiment 5 based on the embodiment 3. As shown in this figure, the electric power usage cost analysis device in this embodiment includes a "CPU (Central Processing Unit)" that performs various arithmetic processing, a "chipset", a "main memory", a "graphics card", a "non-volatile memory" that stores various programs and data (information), an "I / O controller", a "USB, SATA, LAN terminal, etc.", a "BIOS (UEFI)", a "PCI Express slot", and a "real-time clock". These are connected to each other by a data communication path such as a "system bus" to transmit and receive information and perform processing. The same effect can be obtained even if the embodiment 4 is used as a base.

[0196] The various programs and data (information) stored in the non-volatile memory are expanded into the main memory when the device is started up, and upon receiving an execution command, the CPU sequentially executes the programs to perform calculations using the data.

[0197] When the device is started, the various programs and data (information) stored in the "non-volatile memory" are read, expanded, and stored in the "main memory," which also provides a work area for those programs. By receiving execution commands, the "CPU" sequentially executes the programs using the data to perform calculations. Note that multiple addresses are assigned to the "main memory" and "non-volatile memory," and programs executed by the "CPU" can identify and access those addresses to exchange data with each other and perform processing.

[0198] In this embodiment, the programs stored in the "main memory" are a weather data acquisition program (q), a conversion rule storage program (r), one or more of the maximum demand power information storage program (a), the maximum electricity usage information storage program (b), the monthly electricity usage information storage program (c), and the total monthly electricity usage information storage program (d), a total monthly electricity charge information storage program (e), an information output program (f), a comparison program (h), and a subprogram (k) for determining superiority or inferiority among electricity consumers. In addition, the "main memory" and the "non-volatile memory" store weather data, conversion rules, one or more of the maximum demand power information, the maximum electricity usage information, the monthly electricity usage information, and the total monthly electricity usage information, and total monthly electricity charge information. FIG. 15 shows a case where all the above programs and all the information are stored in the "main memory" and the "non-volatile memory". The following operation of the programs will be described for a case where all the programs and all the information are stored and functioned as described above. The same effect can be obtained even if the programs and information described as "any one or more" refer to one or more but not all four.

[0199] "CPU" is The weather data acquisition program (q) stored in the "main memory" is executed to acquire weather data, such as one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, at a predetermined time interval via the Internet line via "USB, SATA, LAN terminal, etc." The conversion rule storage program (r) stored in the "main memory" is executed to store conversion rules, which are rules for converting the acquired weather data, such as temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, based on the acquired weather data, into representative weather information, which is information regarding representative weather for one or more of the demand time period, day, week, month, and quarter (demand time period, day, week, month, and quarter are time lengths equal to or longer than the specified time interval; the same applies below) in which the weather data was observed. The maximum demand power information holding program (a) stored in the "main memory" is executed to hold maximum demand power information, which is information obtained by acquiring and correlating the maximum demand power for the month, the demand time period in which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the demand time period or / the day in which the demand time period is included. A maximum electricity usage information retention program (b) stored in the "main memory" is executed to acquire representative weather information regarding the maximum electricity usage for a day included in the above-mentioned month and the weather (one or more of temperature, humidity, wind speed, sunny, cloudy, rainy, and sunshine hours) for that day and / or the week that includes that day based on the acquired weather data and the stored conversion rule, and then retain maximum electricity usage information which is information associated with this. A monthly electricity usage information retention program (c) stored in the "main memory" is executed to acquire representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including that month based on the electricity usage for the month, the acquired weather data, and the stored conversion rules, and then retain monthly electricity usage information which is information associated with this. A total monthly electricity usage information retention program (d) stored in the "main memory" is executed to retain total monthly electricity usage information, which is information obtained by correlating one or more of the total electricity usage during a specified active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays with representative weather information regarding the weather for the month or the quarter including that month (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and hours of sunshine) obtained based on the obtained weather data and the stored conversion rule. A total monthly electricity charge information holding program (e) stored in the "main memory" is executed to hold total monthly electricity charge information showing the total electricity charge for the month. A comparison program (h) stored in the "main memory" is executed to compare one or more of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information for a different period of a day, month, year, or year. A subprogram (k) for determining superiority / inferiority between electricity consumers stored in the "main memory" is executed to perform a superiority / inferiority determination, which is a determination showing superiority / inferiority between different electricity consumers in terms of power consumption efficiency for each specified demand time period. An information output program (f) stored in the "main memory" is executed to output one or more of the above information via an Internet line through "USB, SATA, LAN terminal, etc.", or via an "I / O controller" or "graphics card" for display on a display, or via "USB, SATA, LAN terminal, etc." for printing on a printer.

[0200] <Effects of the fifth embodiment> In addition to the effects of the third embodiment, the power usage cost analysis device of the fifth embodiment can determine the relative merits of different power consumers from the viewpoint of power consumption efficiency for each predetermined demand time period, thereby providing clues for improving power consumption efficiency. If the power consumption efficiency can be improved in this way and the amount of electricity used can be reduced, the power bill (charged amount), which is the power usage cost of the power consumer, can be reduced, and environmental friendliness can also be improved.

[0201] <Overview of embodiment 6> Mainly claims 6, 15, and 24 The electricity usage cost analysis device of embodiment 6, which is based on any one of embodiments 1 to 5, is further configured to have an electricity consumption tendency information storage unit (L) that stores electricity consumption tendency information, which is information indicating the electricity consumption tendency of each electricity consumer, when the electricity consumption tendency of the electricity consumer changes depending on the weather.

[0202] <Functional configuration of embodiment 6> Fig. 16 shows a functional block diagram of an electric power usage cost analysis device of embodiment 6 based on embodiment 1. The electric power usage cost analysis device of embodiment 6 based on embodiment 1 further includes an electric power consumption tendency information storage unit (L) (1611). Since the components other than the electric power consumption tendency information storage unit (L) (1611) are the same as those of embodiment 1, only the electric power consumption tendency information storage unit (L) (1611) will be described. Note that the same effect can be obtained even if any one of embodiments 2 to 5 is used as a base.

[0203] <Description of the configuration of embodiment 6> <Sixth embodiment: Power consumption tendency information storage unit (L) (1611)> The “power consumption tendency information storage unit (L)” (1611) is configured to store power consumption tendency information, which is information indicating the power consumption tendency of each power consumer when the power consumption tendency of the power consumer changes depending on the weather.

[0204] <Embodiment 6: Power consumption tendency information storage unit (L): Power consumption tendency: General household> As an example of "electricity consumption propensity," we will explain the case where the electricity consumer is an ordinary household. The largest amount of electricity used by an ordinary household is air conditioning equipment such as air conditioners, followed by lighting. Air conditioning equipment is heavily influenced by the weather (temperature), as its operating status changes depending on the outside temperature. Lighting is also influenced by the weather (sunny, cloudy, rainy, or sunshine hours), such that if the weather is cloudy or rainy, rather than sunny, the room becomes dim, so the lights are turned on, and the sunshine hours are shorter in winter than in summer, so the lights are turned on for longer periods of time. Such propensities are examples of electricity consumption propensity. For example, if an electricity consumer has a solar power generation facility, the electricity consumption propensity is to reduce the amount of electricity purchased from the electricity retailer on a sunny day in order to cover at least a part of the daytime electricity used by the electricity consumer itself, and to be unable to reduce the amount of electricity purchased from the electricity retailer on a cloudy or rainy day when the weather is such that the daytime electricity used by the electricity consumer itself cannot be covered by solar power generation. This is another example of electricity consumption propensity. On a sunny day, if the solar power generation equipment owned by the power consumer generates more power than it consumes, it can sell the surplus to the power retailer, and the propensity to sell such power may also be included in the power consumption propensity. In addition, if the power consumer has a wind power generation equipment, it is affected by weather such as wind speed, not by weather such as sunny, cloudy, or rainy.

[0205] <Embodiment 6: Power consumption tendency information storage unit (L): Power consumption tendency: Factories and stores> According to the Ministry of Economy, Trade and Industry's "Winter Energy Saving and Power Saving Menu" published in November 2022, when the electricity consumer is a factory (manufacturing industry), 83% of the electricity is used to operate production equipment. The remaining 17% is mainly used for the atmosphere of the production site, such as air conditioning and lighting (which can include the temperature and humidity of the work environment, illuminance, and the temperature and humidity of the water, chemicals, and air used in production). Since the temperature and humidity of the work environment is affected by the outside temperature and humidity, it can be said that the operation status of the air conditioning equipment in factories is affected by the weather, just like in ordinary homes. For example, in food and pharmaceutical production, which is kept in a constant temperature and humidity environment separated from the outside, and in clean rooms, in order to eliminate the difference between the outside temperature and the indoor set temperature, the air conditioner is operated at a high level in the summer and the heater is operated at a high level in the winter.

[0206] In addition, when water and chemicals used at production sites are temperature-controlled, they must be heated to an appropriate temperature at least in winter (chemicals with a liquid temperature lower than the designated optimum temperature will react slower, hindering production), so in addition to air conditioning equipment, they are also affected by the weather. In the case of retail stores (the percentages in parentheses are the proportion of electricity usage), the main uses of electricity are air conditioning equipment (22.2%) to maintain the atmosphere (temperature and humidity) of the sales floor, lighting for the sales floor (23.8%), showcases (6.1%), and refrigeration and freezing equipment (5.8%). Of these, air conditioning equipment and refrigeration and freezing equipment are affected by the weather (outside temperature). In summer, more electricity is used to operate air conditioning and refrigeration and freezing equipment, and in winter, more electricity is used for heating. It is thought that electricity usage for refrigeration and freezing equipment is less in winter than in summer. In this way, even if electricity users are not ordinary households, such as factories and stores, they have electricity consumption tendencies that are affected by the weather. In addition, even if a factory or store has solar or wind power generation equipment, the amount of electricity generated is affected by the weather (weather: sunny, cloudy, rainy, and wind speed), and this affects the amount of electricity purchased from electricity retailers, resulting in an electricity consumption tendency.

[0207] If power consumers can know their own power consumption tendency that changes according to the weather, they can make an effort to use electricity more efficiently and reduce electricity usage based on future weather forecasts and their own power consumption tendency. By reducing electricity usage, it is possible to reduce the electricity bill (charge), which is the power usage cost for the power consumers, and also to improve the environmental friendliness.

[0208] <Embodiment 6: Operation Method> Fig. 17 is a flowchart of the operation method of the power usage cost analysis device of the sixth embodiment based on the first embodiment. As shown in this figure, the operation method of the power usage cost analysis device of the sixth embodiment performs a weather data acquisition step (q) (S1701) and a conversion rule storage step (r) (S1702), performs one or more of a maximum demand power information storage step (a) (S1704), a maximum electricity usage information storage step (b) (S1706), a monthly electricity usage information storage step (c) (S1708), and a total monthly electricity usage information storage step (d) (S1710), performs a total monthly electricity charge information storage step (e) (S1711), a power consumption tendency information storage step (l) (S1712), and an information output step (f) (S1714). The same effect can be obtained even if any one of the second to fifth embodiments is used as a base.

[0209] Here, the method of operating the power usage cost analysis device, which is a computer and is an apparatus for analyzing the power usage costs of power consumers in a power supply and demand system based on a billing system in which the amount of charge to the power consumer is determined in advance in conjunction with the power trading market price that fluctuates according to the amount of available power supply that changes depending on the weather, is as follows: The meteorological data acquisition step (q) (S1701) performs a process of acquiring meteorological data, which is one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, at a predetermined time interval; The conversion rule storage step (r) (S1702) performs a process of storing a conversion rule that is a rule for converting the acquired weather data, such as temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine duration, into representative weather information that is information on representative weather of any one or more of the demand time slot, day, week, month, and quarter (demand time slot, day, week, month, and quarter are time lengths equal to or longer than the predetermined time interval; the same applies below) in which the weather data was observed, based on the acquired weather data; In (S1703), it is determined whether to execute the maximum demand power information storing step (a) (S1704), and if not, (S1704) is skipped and the process proceeds to before (S1705). The maximum demand power information holding step (a) (S1704) performs a process of holding maximum demand power information, which is information obtained by acquiring the maximum demand power for the month, a demand time period in which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather of the demand time period or / the day including the demand time period (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours), and associating the information with the maximum demand power information; In (S1705), it is determined whether or not to execute the maximum electricity usage information storage step (b) (S1706). If not, (S1706) is skipped and the process proceeds to before (S1707). The maximum electricity usage information storage step (b) (S1706) performs a process of storing maximum electricity usage information associated with the maximum electricity usage for one day included in the month, representative weather information regarding the weather of the day or / the week including the day (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) based on the acquired weather data and the stored conversion rule, and storing the maximum electricity usage information; In (S1707), it is determined whether to execute the monthly electricity usage information storage step (c) (S1708), and if not, (S1708) is skipped and the process proceeds to before (S1709). A monthly electricity usage information storage step (c) (S1708) performs a process of acquiring representative weather information on the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including the month based on the monthly electricity usage, the acquired weather data, and the stored conversion rule, and then storing monthly electricity usage information which is information associated with the representative weather information; In (S1709), it is determined whether to execute the total monthly electricity usage information storage step (d) (S1710). If not, (S1710) is skipped and the process proceeds to before (S1711). The total monthly electricity usage information storage step (d) (S1710) performs a process of storing total monthly electricity usage information, which is information obtained by acquiring representative weather information (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including the month based on one or more of the total electricity usage during a predetermined active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays, based on the acquired weather data and the stored conversion rule, and associating the representative weather information with the weather information; A total monthly electricity charge information holding step (e) (S1711) performs a process of holding total monthly electricity charge information indicating a total electricity charge for the month, The power consumption tendency information holding step (l) (S1712) performs a process of holding power consumption tendency information, which is information indicating the power consumption tendency of each power consumer, when the power consumption tendency of the power consumer changes depending on the weather, and In (S1713), it is determined whether to output one or more of maximum demand power information, maximum electricity usage information, monthly electricity usage information, total monthly electricity usage information, and total monthly electricity charge information. If not, the process proceeds to before (S1701). The information output step (f) (S1714) performs a process of outputting one or more of the above-mentioned pieces of information, which are selected pieces of information. This is an operating method for causing an electric power usage cost analysis device, which is a computer, to execute such a series of processes.

[0210] <Embodiment 6: Hardware Configuration> The hardware configuration of the electricity usage cost analysis device in the sixth embodiment will be described with reference to FIG.

[0211] FIG. 18 is a diagram showing the hardware configuration of an electric power usage cost analysis device in the sixth embodiment based on the first embodiment. As shown in this figure, the electric power usage cost analysis device in this embodiment includes a "CPU (Central Processing Unit)" that performs various arithmetic processing, a "chipset", a "main memory", a "graphics card", a "non-volatile memory" that stores various programs and data (information), an "I / O controller", a "USB, SATA, LAN terminal, etc.", a "BIOS (UEFI)", a "PCI Express slot", and a "real-time clock". These are connected to each other by a data communication path such as a "system bus" to transmit and receive information and perform processing. The same effect can be obtained even if any one of the second to fifth embodiments is used as a base.

[0212] The various programs and data (information) stored in the non-volatile memory are expanded into the main memory when the device is started up, and upon receiving an execution command, the CPU sequentially executes the programs to perform calculations using the data.

[0213] When the device is started, the various programs and data (information) stored in the "non-volatile memory" are read, expanded, and stored in the "main memory," which also provides a work area for those programs. By receiving execution commands, the "CPU" sequentially executes the programs using the data to perform calculations. Note that multiple addresses are assigned to the "main memory" and "non-volatile memory," and programs executed by the "CPU" can identify and access those addresses to exchange data with each other and perform processing.

[0214] In this embodiment, the programs stored in the "main memory" are a weather data acquisition program (q), a conversion rule storage program (r), one or more of a maximum demand power information storage program (a), a maximum electricity usage information storage program (b), a monthly electricity usage information storage program (c), and a total monthly electricity usage information storage program (d), a total monthly electricity charge information storage program (e), an information output program (f), and a power consumption tendency information storage program (l). In addition, the "main memory" and the "non-volatile memory" store weather data, conversion rules, one or more of maximum demand power information, maximum electricity usage information, monthly electricity usage information, and total monthly electricity usage information, total monthly electricity charge information, and power consumption tendency information. FIG. 18 shows a case where all the above programs and all the information are stored in the "main memory" and the "non-volatile memory". The following operation of the programs will be described for a case where all the programs and all the information are stored and functioned as described above. The same effect can be obtained even if the programs and information described as "any one or more" refer to one or more but not all four.

[0215] "CPU" is The weather data acquisition program (q) stored in the "main memory" is executed to acquire weather data, such as one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, at a predetermined time interval via the Internet line via "USB, SATA, LAN terminal, etc." The conversion rule storage program (r) stored in the "main memory" is executed to store conversion rules, which are rules for converting the acquired weather data, such as temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, based on the acquired weather data, into representative weather information, which is information regarding representative weather for one or more of the demand time period, day, week, month, and quarter (demand time period, day, week, month, and quarter are time lengths equal to or longer than the specified time interval; the same applies below) in which the weather data was observed. The maximum demand power information holding program (a) stored in the "main memory" is executed to hold maximum demand power information, which is information obtained by acquiring and correlating the maximum demand power for the month, the demand time period in which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the demand time period or / the day in which the demand time period is included. A maximum electricity usage information retention program (b) stored in the "main memory" is executed to acquire representative weather information regarding the maximum electricity usage for a day included in the above-mentioned month and the weather (one or more of temperature, humidity, wind speed, sunny, cloudy, rainy, and sunshine hours) for that day and / or the week that includes that day based on the acquired weather data and the stored conversion rule, and then retain maximum electricity usage information which is information associated with this. A monthly electricity usage information retention program (c) stored in the "main memory" is executed to acquire representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including that month based on the electricity usage for the month, the acquired weather data, and the stored conversion rules, and then retain monthly electricity usage information which is information associated with this. A total monthly electricity usage information retention program (d) stored in the "main memory" is executed to retain total monthly electricity usage information, which is information obtained by correlating one or more of the total electricity usage during a specified active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays with representative weather information regarding the weather for the month or the quarter including that month (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and hours of sunshine) obtained based on the obtained weather data and the stored conversion rule. A total monthly electricity charge information holding program (e) stored in the "main memory" is executed to hold total monthly electricity charge information showing the total electricity charge for the month. The power consumption tendency information retention program (l) stored in the "main memory" is executed to retain power consumption tendency information, which is information indicating the power consumption tendency of each power consumer when the power consumption tendency of the power consumer changes depending on the weather. An information output program (f) stored in the "main memory" is executed to output one or more of the above information via an Internet line through "USB, SATA, LAN terminal, etc.", or via an "I / O controller" or "graphics card" for display on a display, or via "USB, SATA, LAN terminal, etc." for printing on a printer.

[0216] <Effects of the Sixth Embodiment> In addition to the effects of the first embodiment, the power usage cost analysis device of the sixth embodiment can also hold and output power consumption propensity information, which is information indicating the power consumption propensity of each power consumer, when the power consumption propensity of the power consumer changes according to the weather. If the power consumer can know his / her own power consumption propensity that changes according to the weather, he / she can make an effort to use electricity more efficiently and reduce electricity usage based on future weather forecasts and his / her own power consumption propensity. By reducing electricity usage, it is possible to reduce the electricity bill (charge), which is the power usage cost of the power consumer, and also to improve environmental friendliness.

[0217] <Overview of embodiment 7> Mainly claims 7, 16, and 25 The electricity usage cost analysis device of embodiment 7 is configured such that the comparison unit (H) further includes a maximum demand electricity occurrence frequency acquisition means (M) for each demand time slot, which acquires the frequency at which maximum demand electricity occurs in a day for each demand time slot.

[0218] <Functional configuration of embodiment 7> Fig. 19 shows a functional block diagram of an electric power usage cost analysis device of embodiment 7 based on embodiment 3. In addition to the configuration of embodiment 3, the electric power usage cost analysis device of embodiment 7 further has a means (M) (1912) for acquiring maximum demand power occurrence frequency for each demand time slot in the comparison unit (H) (1908). Since the components other than the means (M) (1912) for acquiring maximum demand power occurrence frequency for each demand time slot are the same as those of embodiment 3, only the means (M) (1912) for acquiring maximum demand power occurrence frequency for each demand time slot will be described. The same effects can be obtained even if the electric power usage cost analysis device is based on any one of embodiment 4 or 5, or embodiment 6 based on any one of embodiment 3 to embodiment 5.

[0219] <Description of the configuration of embodiment 7> <Seventh embodiment: Means for acquiring maximum demand power occurrence frequency for each demand time period (M) (1912)> The 'means (M) for acquiring the frequency of occurrence of maximum demand power for each demand time slot' (1912) is configured in the comparison unit (H) (1908) so as to acquire the frequency of occurrence of maximum demand power in a day for each demand time slot.

[0220] "Obtaining the frequency of occurrence of maximum demand power in one day for each demand time slot" means, for example, investigating the demand time slot in which the maximum demand power occurred for each day of the last month, and obtaining the number of occurrences (frequency) for each demand time slot. If the above example is for Japan in 2023, a day (from 0:00 am to 23:60 pm) is divided into 48 slots, with each slot being 30 minutes. For each of the 48 slots, the maximum demand power occurred from 1:00 pm to 1:30 pm on the 1st of last month, and from 2:00 pm to 2:30 pm on the 2nd, and so on. Thus, the maximum demand power occurrence frequency is obtained for each of the 48 slots of the demand time slot in one day. If one month is 30 days, the total frequency of each of the 48 slots after the frequency for one month is obtained is 30. The period for obtaining the frequency is one day, one month, one year, or a period equivalent to a different year, as in the third embodiment (corresponding to claim 3) on which the seventh embodiment is based.

[0221] If the frequency of occurrence of maximum demand power seems to be concentrated in a specific demand period, it becomes an opportunity for the relevant power consumer to investigate the reason why the power consumption during that period is high. Reducing the amount of electricity consumption during the specific period of time where the frequency is high can lead to a reduction in electricity bills. If the specific period of time where the frequency is high is a period of time when the power market price is high, electricity bills can also be reduced by allocating electricity consumption to a period of time when the power market price is low. For example, if the demand period from 14:00 to 14:30 during a midsummer month is the demand period during which the frequency of occurrence of maximum demand power is the highest, and the outside temperature at that time is 35°C, measures to reduce electricity consumption can be taken, such as raising the cooling setting temperature of the air conditioning equipment by one degree from 25°C to 26°C and using a circulator to circulate the cold air. Reducing electricity consumption can reduce the electricity bill (charge), which is the power usage cost of the power consumer, and also improve environmental friendliness.

[0222] The system may be configured to obtain the frequency of maximum demand power during a day for different power consumers for each demand time period. By comparing the frequency distributions in consideration of the power consumption tendencies of different power consumers, each power consumer can be prompted to reconsider how they use electricity. The different power consumers from which the frequency is obtained may be selected together with comparison attributes that are considered to have similar power consumption, such as similar industries, similar business scales, similar numbers of employees, similar regions (temperature, wind power, sunshine hours, etc.), and in the case of general households, similar house structures (single-family homes, condominiums, apartments), family structures, addresses, occupations, etc. This is because it is natural that the demand time periods during which maximum demand power occurs and its frequency will be different between a factory that operates 24 hours a day and a general household.

[0223] The above example can be achieved by further comprising an electricity consumer identification information holding unit which holds electricity consumer identification information that identifies electricity consumers, and an electricity consumer attribute information holding unit which holds electricity consumer attribute information, which is information indicating the attributes of electricity consumers (one or more of industry, business size, location, number of employees, temperature, wind speed, and sunshine hours at the location), in association with the electricity consumer identification information, and the maximum demand power occurrence frequency acquisition means (M) for each demand time period is configured to acquire the frequency at which maximum demand power occurred in a day for each electricity consumer identified by one electricity consumer identification information and for each electricity consumer identified by other electricity consumer identification information having similar electricity consumer attribute information.

[0224] <Embodiment 7: Operation Method> Fig. 20 is a flowchart of the operation method of the power usage cost analysis device of the seventh embodiment based on the third embodiment. As shown in this figure, the operation method of the power usage cost analysis device of the seventh embodiment performs a weather data acquisition step (q) (S2001) and a conversion rule storage step (r) (S2002), performs one or more of a maximum demand power information storage step (a) (S2002), a maximum electricity usage information storage step (b) (S2004), a monthly electricity usage information storage step (c) (S2006), and a total monthly electricity usage information storage step (d) (S2008), performs a total monthly electricity charge information storage step (e) (S2009), a comparison step (h) (S2010), and a maximum demand power occurrence frequency acquisition substep (m) (S2011) and an information output step (f) (S2013) in the comparison step (h) (S2010). The same effect can be obtained based on either embodiment 4 or 5, or embodiment 6 based on any one of embodiments 3 to 5.

[0225] Here, the method of operating the power usage cost analysis device, which is a computer and is an apparatus for analyzing the power usage costs of power consumers in a power supply and demand system based on a billing system in which the amount of charge to the power consumer is determined in advance in conjunction with the power trading market price that fluctuates according to the amount of available power supply that changes depending on the weather, is as follows: The meteorological data acquisition step (q) (S2001) performs a process of acquiring meteorological data, which is one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, at a predetermined time interval; A conversion rule storage step (r) (S2002) performs a process of storing a conversion rule that is a rule for converting the acquired weather data, such as temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine duration, into representative weather information that is information on representative weather of any one or more of the demand time slots, days, weeks, months, and quarters (demand time slots, days, weeks, months, and quarters are time lengths equal to or longer than the predetermined time intervals; the same applies below) in which the weather data was observed, based on the acquired weather data; In (S2003), it is determined whether to execute the maximum demand power information holding step (a) (S2004), and if not, (S2004) is skipped and the process proceeds to before (S2005). The maximum power demand information holding step (a) (S2004) performs a process of holding maximum power demand information, which is information obtained by acquiring the maximum power demand for the month, a demand time period in which the maximum power demand occurred based on the acquired weather data and the stored conversion rule, and representative weather information on the weather of the demand time period or / the day including the demand time period (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) and associating the information with the maximum power demand information; In (S2005), it is determined whether or not to execute the maximum electricity usage information storage step (b) (S2006). If not, (S2006) is skipped and the process proceeds to before (S2007). The maximum electricity usage information storage step (b) (S2006) performs a process of acquiring representative weather information on the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for a day or / a week including the day based on the maximum electricity usage included in the month, the acquired weather data, and the stored conversion rule, and then storing the maximum electricity usage information associated with the representative weather information; In (S2007), it is determined whether to execute the monthly electricity usage information storage step (c) (S2008), and if not, (S2008) is skipped and the process proceeds to before (S2009). A monthly electricity usage information storage step (c) (S2008) performs a process of acquiring representative weather information on the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including the month based on the monthly electricity usage, the acquired weather data, and the stored conversion rule, and storing monthly electricity usage information which is information associated with the representative weather information; In (S2009), it is determined whether to execute the step (d) (S2010) of storing the total monthly electricity usage information. If not, (S2010) is skipped and the process proceeds to before (S2011). The total monthly electricity usage information storage step (d) (S2010) performs a process of storing total monthly electricity usage information, which is information obtained by acquiring representative weather information (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including the month based on one or more of the total electricity usage during a predetermined active time period, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays for the month, and the acquired weather data and the stored conversion rule, and associating the representative weather information with the representative weather information; A total monthly electricity charge information holding step (e) (S2011) performs a process of holding total monthly electricity charge information indicating a total electricity charge for the month, The comparison step (h) (S2012) performs a process of comparing one or more of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information for a different day, month, year, or different year corresponding to the information; The sub-step (m) (S2013) of acquiring the frequency of occurrence of maximum demand power for each demand time slot in the comparison step (h) (S2012) performs a process of acquiring the frequency of occurrence of maximum demand power in one day for each demand time slot, In (S2014), it is determined whether to output one or more of maximum demand power information, maximum electricity usage information, monthly electricity usage information, total monthly electricity usage information, and total monthly electricity charge information. If not, the process proceeds to before (S2001). The information output step (f) (S2015) performs a process of outputting one or more of the above-mentioned pieces of information, which are selected pieces of information. This is an operating method for causing an electric power usage cost analysis device, which is a computer, to execute such a series of processes.

[0226] <Seventh embodiment: Hardware configuration> The hardware configuration of the electricity usage cost analysis device in the seventh embodiment will be described with reference to FIG.

[0227] FIG. 21 is a diagram showing the hardware configuration of the power usage cost analysis device in the present embodiment 7 based on the embodiment 3. As shown in this figure, the power usage cost analysis device in this embodiment includes a "CPU (Central Processing Unit)" that performs various arithmetic processing, a "chipset", a "main memory", a "graphics card", a "non-volatile memory" that holds various programs and data (information), an "I / O controller", a "USB, SATA, LAN terminal, etc.", a "BIOS (UEFI)", a "PCI Express slot", and a "real-time clock". These are connected to each other by a data communication path such as a "system bus" to transmit and receive information and perform processing. The same effect can be obtained based on any one of the embodiments 4 or 5, or any one of the embodiments 6 based on any one of the embodiments 3 to 5.

[0228] The various programs and data (information) stored in the non-volatile memory are expanded into the main memory when the device is started up, and upon receiving an execution command, the CPU sequentially executes the programs to perform calculations using the data.

[0229] When the device is started, the various programs and data (information) stored in the "non-volatile memory" are read, expanded, and stored in the "main memory," which also provides a work area for those programs. By receiving execution commands, the "CPU" sequentially executes the programs using the data to perform calculations. Note that multiple addresses are assigned to the "main memory" and "non-volatile memory," and programs executed by the "CPU" can identify and access those addresses to exchange data with each other and perform processing.

[0230] In this embodiment, the programs stored in the "main memory" are a weather data acquisition program (q), a conversion rule storage program (r), one or more of a maximum demand power information storage program (a), a maximum electricity usage information storage program (b), a monthly electricity usage information storage program (c), and a total monthly electricity usage information storage program (d), a total monthly electricity charge information storage program (e), an information output program (f), a comparison program (h), and a demand time zone maximum demand power occurrence frequency acquisition subprogram (m). In addition, the "main memory" and the "non-volatile memory" store weather data, conversion rules, one or more of maximum demand power information, maximum electricity usage information, monthly electricity usage information, and total monthly electricity usage information, total monthly electricity charge information, and frequency. FIG. 21 shows a case where all the above programs and all the information are stored in the "main memory" and the "non-volatile memory". The following program operation description will be given for a case where all the programs and all the information are stored and functioned as described above. The same effect can be obtained even if the programs and information described as "any one or more" refer to one or more but not all four.

[0231] "CPU" is The weather data acquisition program (q) stored in the "main memory" is executed to acquire weather data, such as one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, at a predetermined time interval via the Internet line via "USB, SATA, LAN terminal, etc." The conversion rule storage program (r) stored in the "main memory" is executed to store conversion rules, which are rules for converting the acquired weather data, such as temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, based on the acquired weather data, into representative weather information, which is information regarding representative weather for one or more of the demand time period, day, week, month, and quarter (demand time period, day, week, month, and quarter are time lengths equal to or longer than the specified time interval; the same applies below) in which the weather data was observed. The maximum demand power information holding program (a) stored in the "main memory" is executed to hold maximum demand power information, which is information obtained by acquiring and correlating the maximum demand power for the month, the demand time period in which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the demand time period or / the day in which the demand time period is included. A maximum electricity usage information retention program (b) stored in the "main memory" is executed to acquire representative weather information regarding the maximum electricity usage for a day included in the above-mentioned month and the weather (one or more of temperature, humidity, wind speed, sunny, cloudy, rainy, and sunshine hours) for that day and / or the week that includes that day based on the acquired weather data and the stored conversion rule, and then retain maximum electricity usage information which is information associated with this. A monthly electricity usage information retention program (c) stored in the "main memory" is executed to acquire representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including that month based on the electricity usage for the month, the acquired weather data, and the stored conversion rules, and then retain monthly electricity usage information which is information associated with this. A total monthly electricity usage information retention program (d) stored in the "main memory" is executed to retain total monthly electricity usage information, which is information obtained by correlating one or more of the total electricity usage during a specified active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays with representative weather information regarding the weather for the month or the quarter including that month (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and hours of sunshine) obtained based on the obtained weather data and the stored conversion rule. A total monthly electricity charge information holding program (e) stored in the "main memory" is executed to hold total monthly electricity charge information showing the total electricity charge for the month. A comparison program (h) stored in the "main memory" is executed to compare one or more of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information for a different period of a day, month, year, or year. The frequency at which maximum demand power occurs during a day is obtained for each demand time slot by executing the subprogram (m) for obtaining the frequency at which maximum demand power occurs during each demand time slot, which is stored in the "main memory." An information output program (f) stored in the "main memory" is executed to output one or more of the above information via an Internet line through "USB, SATA, LAN terminal, etc.", or via an "I / O controller" or "graphics card" for display on a display, or via "USB, SATA, LAN terminal, etc." for printing on a printer.

[0232] <Effects of the Seventh Embodiment> In addition to the effects of the third embodiment, the power usage cost analysis device of the seventh embodiment can obtain the frequency of occurrence of maximum power demand in a day for each demand time period, allowing the power consumer to grasp the tendency of his / her own power usage and reduce the maximum power demand, and thus the power bill. By reducing the amount of electricity usage, the power consumer's power bill (charged amount), which is the power usage cost, can be reduced, and environmental friendliness can also be improved.

[0233] <Overview of embodiment 8> Mainly claims 8, 17, and 26 The power usage cost analysis device of embodiment 8 is configured so that the comparison unit (H) further includes a maximum power demand by temperature acquisition means (N) for acquiring a maximum power demand by temperature, which is the maximum power demand per demand time slot for each temperature.

[0234] <Functional configuration of embodiment 8> Fig. 22 shows a functional block diagram of an electric power usage cost analysis device of embodiment 8 based on embodiment 3. The electric power usage cost analysis device of embodiment 8 based on embodiment 3 further has a maximum power demand per temperature acquisition means (N) (2213) in the comparison unit (H) (2208). Since everything other than the maximum power demand per temperature acquisition means (N) (2213) is the same as embodiment 3, only the maximum power demand per temperature acquisition means (N) (2213) will be explained. The same effect can be obtained even if the electric power usage cost analysis device is based on embodiment 4, 5 or 7, or any one of embodiment 6 based on any one of embodiments 3 to 5.

[0235] <Description of Configuration of Embodiment 8> <Embodiment 8: Means for acquiring maximum power demand per temperature (N) (2213)> The 'means (N) for acquiring maximum power demand by temperature' (2213) is configured in the comparison unit (H) (2208) so as to acquire the maximum power demand by temperature, which is the maximum power demand per demand time slot for each temperature.

[0236] The maximum power demand per demand time slot is calculated for each temperature. For example, in the third embodiment (corresponding to claim 3) on which the eighth embodiment is based, the temperature is associated with the power demand per demand time slot for one day, one month, one year, and corresponding periods in different years. Therefore, for example, within a one-month period, the maximum power demand for the demand time slot corresponding to each temperature is checked, such as the maximum power demand at 34°C and the maximum power demand at 35°C, and the maximum power demand for each temperature is obtained as the maximum power demand for each temperature.

[0237] For example, if the maximum power demand for each temperature is obtained for an electricity consumer living in Tokyo, when the temperature reaches 30°C or above on a midsummer day or extremely hot day (e.g., July or August) or when the temperature reaches 0°C or below on a winter or midwinter day (e.g., January or February), a larger maximum power demand is likely to occur compared to a temperature range of around 25°C where air conditioning is not required. By obtaining future weather forecasts and knowing temperature information, electricity consumers can predict their future electricity usage. They can also consider reducing predicted electricity usage. Reducing electricity usage can reduce electricity charges (charges), which are the electricity usage costs for electricity consumers, and also improve environmental friendliness.

[0238] The maximum power demand by temperature acquisition means (N) can be configured to acquire the maximum power demand by different power consumers. By comparing the maximum power demand by temperature between different power consumers, the difference in the maximum power demand by temperature can be understood, which can be used to help consider reducing electricity usage.

[0239] <Embodiment 8: Means for acquiring maximum power demand by temperature (N): Power consumer comparison attribute> The power consumers to be compared should be selected based on attributes that are likely to have similar power consumption, such as similar industry, similar business scale, similar region (temperature, wind power, sunshine hours, etc.), and for general households, similar house structure (single-family house, condominium, apartment), family structure, address, occupation, etc. For example, even if they are general households, it is difficult to use a comparison between a power consumer living in Okinawa and a power consumer living in Asahikawa, Hokkaido, as their weather and house structure are too different. However, for example, a power consumer living in Tokyo can use the maximum power demand per temperature in winter of another power consumer living in Hokkaido as a reference for reducing electricity consumption. If the power consumer living in Hokkaido uses less electricity in winter at lower outdoor temperatures than the power consumer living in Tokyo, the power consumer living in Tokyo can notice that the power consumer living in Hokkaido is taking effective measures to reduce electricity consumption, and if possible, can adopt those measures to help reduce electricity bills.

[0240] The above example can be achieved by further comprising an electricity consumer identification information holding unit which holds electricity consumer identification information for identifying an electricity consumer, and an electricity consumer attribute information holding unit which holds electricity consumer attribute information, which is information indicating the attributes of an electricity consumer (one or more of industry, business size, location, number of employees, temperature at the location, wind speed, and sunshine hours), in association with the electricity consumer identification information, and the maximum demand power by temperature acquisition means (N) is configured to acquire maximum demand power by temperature, which is the maximum demand power per temperature per demand time period for each electricity consumer identified by one electricity consumer identification information and another electricity consumer identified by other electricity consumer identification information having similar electricity consumer attribute information.

[0241] The system may be configured to acquire the power demand for the demand time slot corresponding to each temperature in association with time information. It is considered that there are multiple (or only one) demand time slots corresponding to each temperature. It may also be configured to acquire an average power demand value for each temperature, which is the average value of power demand, for each temperature. The time information associated with the average power demand value for each temperature may be configured to use time information (from 00:00 to 23:60 within a day) indicating the most frequent demand time slot at a certain temperature (e.g., 25°C) within a specified survey period. Alternatively, information indicating the distribution of the frequency of the corresponding demand time slot may be associated with each temperature.

[0242] <Embodiment 8: Operation Method> Fig. 23 is a flowchart of an operation method of the power usage cost analysis device of embodiment 8 based on embodiment 3. As shown in this figure, the operation method of the power usage cost analysis device of embodiment 8 performs a weather data acquisition step (q) (S2301) and a conversion rule storage step (r) (S2302), performs one or more of a maximum demand power information storage step (a) (S2304), a maximum electricity usage information storage step (b) (S2306), a monthly electricity usage information storage step (c) (S2308), and a total monthly electricity usage information storage step (d) (S2310), performs a total monthly electricity charge information storage step (e) (S2311), a comparison step (h) (S2312), a maximum demand power acquisition substep (n) (S2313) for each temperature in the comparison step (h) (S2312), and an information output step (f) (S2315). The same effect can be obtained based on any one of the embodiments 4, 5 or 7, or on any one of the embodiments 6 based on any one of the embodiments 3 to 5.

[0243] Here, the method of operating the power usage cost analysis device, which is a computer and is an apparatus for analyzing the power usage costs of power consumers in a power supply and demand system based on a billing system in which the amount of charge to the power consumer is determined in advance in conjunction with the power trading market price that fluctuates according to the amount of available power supply that changes depending on the weather, is as follows: The meteorological data acquisition step (q) (S2301) performs a process of acquiring meteorological data, which is one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, at a predetermined time interval; The conversion rule storage step (r) (S2302) performs a process of storing a conversion rule that is a rule for converting the acquired weather data, such as temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine duration, into representative weather information that is information on representative weather of any one or more of the demand time slot, day, week, month, and quarter (demand time slot, day, week, month, and quarter are time lengths equal to or longer than the predetermined time interval; the same applies below) in which the weather data was observed, based on the acquired weather data; In (S2303), it is determined whether to execute the maximum demand power information storing step (a) (S2304), and if not, (S2304) is skipped and the process proceeds to before (S2305). The maximum demand power information holding step (a) (S2304) performs a process of holding maximum demand power information, which is information obtained by acquiring the maximum demand power for the month, a demand time period in which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather of the demand time period or / the day including the demand time period (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) and associating the information with the maximum demand power information; In (S2305), it is determined whether to execute the maximum electricity usage information storage step (b) (S2306), and if not, (S2306) is skipped and the process proceeds to before (S2307). The maximum electricity usage information storage step (b) (S2306) performs a process of acquiring representative weather information on the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for a day or / a week including the day based on the maximum electricity usage included in the month, the acquired weather data, and the stored conversion rule, and then storing the maximum electricity usage information associated with the representative weather information; In (S2307), it is determined whether to execute the monthly electricity usage information storage step (c) (S2308), and if not, (S2308) is skipped and the process proceeds to before (S2309). A monthly electricity usage information storage step (c) (S2308) performs a process of acquiring representative weather information on the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including the month based on the monthly electricity usage, the acquired weather data, and the stored conversion rule, and then storing monthly electricity usage information which is information associated with the representative weather information; In (S2309), it is determined whether to execute the total monthly electricity usage information storage step (d) (S2310). If not, (S2310) is skipped and the process proceeds to before (S2311). The total monthly electricity usage information storage step (d) (S2310) performs a process of storing total monthly electricity usage information, which is information obtained by acquiring representative weather information (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including the month based on one or more of the total electricity usage during a predetermined active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays, based on the acquired weather data and the stored conversion rule, and associating the representative weather information with the weather information; A total monthly electricity charge information holding step (e) (S2311) performs a process of holding total monthly electricity charge information indicating a total electricity charge for the month, A comparison step (h) (S2312) performs a process of comparing one or more of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information for a different day, month, year, or different year corresponding to the information; The sub-step (n) (S2313) of acquiring maximum demand power for each temperature in the comparison step (h) (S2312) acquires the maximum demand power for each temperature (maximum demand power for each temperature), which is the maximum demand power for each demand time period for each temperature. In (S2314), it is determined whether to output one or more of maximum demand power information, maximum electricity usage information, monthly electricity usage information, total monthly electricity usage information, and total monthly electricity charge information. If not, the process proceeds to before (S2301). The information output step (f) (S2315) performs a process of outputting one or more of the above-mentioned pieces of information, which are selected pieces of information. This is an operating method for causing an electric power usage cost analysis device, which is a computer, to execute such a series of processes.

[0244] <Embodiment 8: Hardware Configuration> The hardware configuration of the electricity usage cost analysis device in the eighth embodiment will be described with reference to FIG.

[0245] FIG. 24 is a diagram showing the hardware configuration of the power usage cost analysis device in the present embodiment 8 based on the embodiment 3. As shown in this figure, the power usage cost analysis device in this embodiment includes a "CPU (Central Processing Unit)" that performs various arithmetic processing, a "chipset", a "main memory", a "graphics card", a "non-volatile memory" that holds various programs and data (information), an "I / O controller", a "USB, SATA, LAN terminal, etc.", a "BIOS (UEFI)", a "PCI Express slot", and a "real-time clock". These are connected to each other by a data communication path such as a "system bus", and perform transmission and reception of information and processing. The same effect can be obtained based on any one of the embodiments 4, 5, or 7, or the embodiment 6 based on any one of the embodiments 3 to 5.

[0246] The various programs and data (information) stored in the non-volatile memory are expanded into the main memory when the device is started up, and upon receiving an execution command, the CPU sequentially executes the programs to perform calculations using the data.

[0247] When the device is started, the various programs and data (information) stored in the "non-volatile memory" are read, expanded, and stored in the "main memory," which also provides a work area for those programs. By receiving execution commands, the "CPU" sequentially executes the programs using the data to perform calculations. Note that multiple addresses are assigned to the "main memory" and "non-volatile memory," and programs executed by the "CPU" can identify and access those addresses to exchange data with each other and perform processing.

[0248] In this embodiment, the programs stored in the "main memory" are a weather data acquisition program (q), a conversion rule storage program (r), one or more of a maximum power demand information storage program (a), a maximum electricity usage information storage program (b), a monthly electricity usage information storage program (c), and a total monthly electricity usage information storage program (d), a total monthly electricity charge information storage program (e), an information output program (f), a comparison program (h), and a maximum power demand acquisition subprogram for each temperature (n). In addition, the "main memory" and the "non-volatile memory" store weather data, conversion rules, one or more of maximum power demand information, maximum electricity usage information, monthly electricity usage information, and total monthly electricity usage information, total monthly electricity charge information, and maximum power demand for each temperature. FIG. 21 shows a case where all the above programs and all the information are stored in the "main memory" and the "non-volatile memory". The following operation of the programs will be described for a case where all the programs and all the information are stored and functioned as described above. The same effect can be obtained even if the programs and information described as "any one or more" refer to one or more but not all four.

[0249] "CPU" is The weather data acquisition program (q) stored in the "main memory" is executed to acquire weather data, such as one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, at a predetermined time interval via the Internet line via "USB, SATA, LAN terminal, etc." The conversion rule storage program (r) stored in the "main memory" is executed to store conversion rules, which are rules for converting the acquired weather data, such as temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, based on the acquired weather data, into representative weather information, which is information regarding representative weather for one or more of the demand time period, day, week, month, and quarter (demand time period, day, week, month, and quarter are time lengths equal to or longer than the specified time interval; the same applies below) in which the weather data was observed. The maximum demand power information holding program (a) stored in the "main memory" is executed to hold maximum demand power information, which is information obtained by acquiring and correlating the maximum demand power for the month, the demand time period in which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the demand time period or / the day in which the demand time period is included. A maximum electricity usage information retention program (b) stored in the "main memory" is executed to acquire representative weather information regarding the maximum electricity usage for a day included in the above-mentioned month and the weather (one or more of temperature, humidity, wind speed, sunny, cloudy, rainy, and sunshine hours) for that day and / or the week that includes that day based on the acquired weather data and the stored conversion rule, and then retain maximum electricity usage information which is information associated with this. A monthly electricity usage information retention program (c) stored in the "main memory" is executed to acquire representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including that month based on the electricity usage for the month, the acquired weather data, and the stored conversion rules, and then retain monthly electricity usage information which is information associated with this. A total monthly electricity usage information retention program (d) stored in the "main memory" is executed to retain total monthly electricity usage information, which is information obtained by correlating one or more of the total electricity usage during a specified active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays with representative weather information regarding the weather for the month or the quarter including that month (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and hours of sunshine) obtained based on the obtained weather data and the stored conversion rule. A total monthly electricity charge information holding program (e) stored in the "main memory" is executed to hold total monthly electricity charge information showing the total electricity charge for the month. A comparison program (h) stored in the "main memory" is executed to compare one or more of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information for a different period of a day, month, year, or year. The maximum demand power by temperature acquisition subprogram (n) stored in the "main memory" is executed to acquire the maximum demand power by temperature (maximum demand power by temperature), which is the maximum demand power per demand time period for each temperature. An information output program (f) stored in the "main memory" is executed to output one or more of the above information via an Internet line through "USB, SATA, LAN terminal, etc.", or via an "I / O controller" or "graphics card" for display on a display, or via "USB, SATA, LAN terminal, etc." for printing on a printer.

[0250] <Effects of the eighth embodiment> In addition to the effects of the third embodiment, the power usage cost analysis device of the eighth embodiment can obtain maximum power demand for each temperature, which is the maximum power demand per demand time period for each temperature. If temperature information can be known as a future weather forecast, it is possible to consider reducing the amount of electricity usage. If the amount of electricity usage can be reduced, it is possible to reduce the electricity bill (charged amount), which is the power usage cost of the power consumer, and also to improve environmental friendliness.

[0251] <Overview of embodiment 9> Mainly claims 9, 18, and 27 The electricity usage cost analysis device of embodiment 9, which is based on any one of embodiments 1 to 8, is further configured to have a future weather information acquisition unit (O) that acquires future weather information, which is information indicating future weather including at least temperature, and a future maximum electricity demand forecast value acquisition unit (P) that acquires a future maximum electricity demand forecast value, which is a forecast value of maximum electricity demand at a future time, from the temperature included in the acquired future weather information.

[0252] <Functional Configuration of Embodiment 9> Fig. 25 shows a functional block diagram of an electric power usage cost analysis device of embodiment 9 based on embodiment 8. In addition to the configuration of embodiment 8, the electric power usage cost analysis device of embodiment 9 further includes a future weather information acquisition unit (O) (2514) and a future maximum electric power demand forecast value acquisition unit (P) (2515). Since the electric power usage cost analysis device of embodiment 9 is similar to embodiment 8 except for the future weather information acquisition unit (O) (2514) and the future maximum electric power demand forecast value acquisition unit (P) (2515), only the future weather information acquisition unit (O) (2514) and the future maximum electric power demand forecast value acquisition unit (P) (2515) will be described. The same effect can be obtained even if any one of embodiments 1 to 7 is used as a base.

[0253] <Description of Configuration of Embodiment 9> <Ninth embodiment: Future weather information acquisition unit (O) (2514)> The 'future weather information acquisition unit (O)' (2514) is configured to acquire future weather information, which is information indicating future weather including at least temperature. It is more preferable to acquire the future weather information in association with time information, which is information indicating a corresponding time.

[0254] The weather forecast information including at least temperature can be obtained from the Japan Meteorological Agency, a weather forecasting company, etc. It is preferable to further include a future weather information storage unit that stores the obtained future weather information, which is information indicating future weather including at least temperature. More preferably, the future weather information is stored in association with time information indicating a time corresponding to the future weather information.

[0255] The weather information to be acquired may include, in addition to temperature, weather conditions such as sunny, cloudy, rainy, snowy, frosty, fog, humidity, sunshine hours, wind speed, wind direction, etc. The future weather information may be future daily weather information, but is preferably weather information for the daytime and after sunset, or weather information for more detailed time periods such as every 3 hours or every hour. More preferably, it is weather information for each demand time period.

[0256] <Ninth embodiment: Future maximum power demand forecast value acquisition unit (P) (2515)> The "future maximum power demand forecast value acquisition unit (P)" (2515) is configured to acquire a future maximum power demand forecast value, which is a forecast value of the maximum power demand at a future point in time, from the temperature included in the acquired future weather information. The future maximum power demand forecast value can be configured to be acquired for each power consumer identified by the power consumer identification information.

[0257] A future maximum power demand prediction value can be obtained based on information including the temperature at a future time point and the maximum power demand for each temperature obtained from past electricity usage records. Electricity consumers can consider reducing the future maximum power demand prediction value at a future time point, and can reduce electricity usage. By reducing electricity usage, it is possible to reduce electricity charges (billing amount), which is the electricity usage cost for the electricity consumer, and also to improve environmental friendliness.

[0258] The configuration of the ninth embodiment may be as follows. The future maximum power demand forecast value acquisition unit (P) may be configured to acquire time information indicating the time (date and time) to which the acquired future weather information corresponds in association with the time information, and further to have a future maximum power demand forecast value information storage unit that stores the acquired future maximum power demand forecast value information in association with power consumer identification information that identifies the power consumer and future weather information including temperature, and a future maximum power demand forecast value output unit that outputs a future maximum power demand forecast value predicted for the power consumer. With such a configuration, it is possible to output and provide a future maximum power demand forecast value associated with future weather information including temperature for each power consumer. The power consumer from whom the future maximum power demand forecast value has been acquired can consider improving the power consumption propensity at the time of the future maximum power demand forecast value by referring to the power consumption propensity shown at the corresponding temperature in the past.

[0259] The system may further include a comparison verification unit that compares the maximum power demand at the target time when the future maximum power demand forecast value is predicted with the actual maximum power demand to verify the difference. The comparison verification unit may further include a future weather information comparison verification means that acquires the difference between the temperature or other weather information included in the future weather information and the actual weather information. This can be used as an opportunity to verify whether the maximum power demand forecast value was correct because the weather information forecast was correct, or if the weather information forecast was correct but the maximum power demand forecast value was incorrect. If the cause can be identified, it can be fed back to the future maximum power demand forecast value acquisition unit (P), improving the accuracy of the forecast.

[0260] <Embodiment 9: Operation Method> Fig. 26 is a flowchart of an operation method of the electric power usage cost analysis device of embodiment 9 based on embodiment 8. As shown in this figure, the operation method of the electric power usage cost analysis device of embodiment 9 performs a weather data acquisition step (q) (S2601) and a conversion rule storage step (r) (S2602), a maximum demand electric power information storage step (a) (S2604), a maximum electricity usage information storage step (b) (S2606), a monthly electricity usage information storage step (c) (S2608), and a total monthly electricity usage information storage step (d) (S2609). 10), and performs a total monthly electricity charge information storage step (e) (S2611), a comparison step (h) (S2612), a maximum power demand acquisition sub-step (n) (S2613) for each temperature in the comparison step (h) (S2612), a future weather information acquisition step (o) (S2614), a future maximum power demand forecast value acquisition step (p) (S2615), and an information output step (f) (S2617). Note that the same effect can be obtained even if any one of the embodiments 1 to 7 is used as a base.

[0261] Here, the method of operating the power usage cost analysis device, which is a computer and is an apparatus for analyzing the power usage costs of power consumers in a power supply and demand system based on a billing system in which the amount of charge to the power consumer is determined in advance in conjunction with the power trading market price that fluctuates according to the amount of available power supply that changes depending on the weather, is as follows: The meteorological data acquisition step (q) (S2601) performs a process of acquiring meteorological data, which is one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, at a predetermined time interval; The conversion rule storage step (r) (S2602) performs processing for storing conversion rules for converting the acquired weather data, i.e., temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine duration, into representative weather information, which is information on representative weather of any one or more of the demand time slots, days, weeks, months, and quarters (demand time slots, days, weeks, months, and quarters are time lengths equal to or longer than the predetermined time intervals; the same applies below) in which the weather data was observed, based on the acquired weather data; In (S2603), it is determined whether to execute the maximum demand power information storage step (a) (S2604), and if not, (S2604) is skipped and the process proceeds to before (S2605). The maximum demand power information holding step (a) (S2604) performs a process of holding maximum demand power information, which is information obtained by acquiring the maximum demand power for the month, a demand time period in which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather of the demand time period or / the day including the demand time period (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours), and associating the information with the maximum demand power information; In (S2605), it is determined whether or not to execute the maximum electricity usage information storage step (b) (S2606). If not, (S2606) is skipped and the process proceeds to before (S2607). The maximum electricity usage information storage step (b) (S2606) performs a process of acquiring representative weather information on the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for a day or / a week including the day based on the maximum electricity usage included in the month, the acquired weather data, and the stored conversion rule, and then storing the maximum electricity usage information associated with the representative weather information; In (S2607), it is determined whether to execute the monthly electricity usage information storage step (c) (S2608), and if not, (S2608) is skipped and the process proceeds to before (S2609). A monthly electricity usage information storage step (c) (S2608) performs a process of acquiring representative weather information on the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including the month based on the monthly electricity usage, the acquired weather data, and the stored conversion rule, and then storing monthly electricity usage information which is information associated with the representative weather information; In (S2609), it is determined whether or not to execute the total monthly electricity usage information storage step (d) (S2610). If not, (S2610) is skipped and the process proceeds to before (S2611). The total monthly electricity usage information storage step (d) (S2610) performs a process of storing total monthly electricity usage information, which is information obtained by acquiring representative weather information (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including the month based on one or more of the total electricity usage during a predetermined active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays, based on the acquired weather data and the stored conversion rule, and associating the representative weather information with the weather information; A total monthly electricity charge information holding step (e) (S2611) performs a process of holding total monthly electricity charge information indicating a total electricity charge for the month, A comparison step (h) (S2612) performs a process of comparing one or more of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information for a different day, month, year, or different year corresponding to the information, The sub-step (n) (S2313) of acquiring maximum demand power for each temperature in the comparison step (h) (S2612) acquires the maximum demand power for each temperature (maximum demand power for each temperature), which is the maximum demand power for each demand time period for each temperature. A future weather information acquisition step (o) (S2614) performs a process of acquiring future weather information, which is information indicating future weather including at least temperature, The future maximum power demand forecast value acquisition step (p) (S2615) performs a process of acquiring a future maximum power demand forecast value, which is a forecast value of a maximum power demand at a future time point, from the temperature included in the acquired future weather information; In (S2616), it is determined whether to output one or more of maximum demand power information, maximum electricity usage information, monthly electricity usage information, total monthly electricity usage information, and total monthly electricity charge information. If not, the process proceeds to before (S2601). The information output step (f) (S2617) performs a process of outputting one or more of the above-mentioned pieces of information, which are selected pieces of information. This is an operating method for causing an electric power usage cost analysis device, which is a computer, to execute such a series of processes.

[0262] <Ninth embodiment: Hardware configuration> The hardware configuration of the electricity usage cost analysis device in the ninth embodiment will be described with reference to FIG.

[0263] FIG. 27 is a diagram showing the hardware configuration of an electric power usage cost analysis device in the present embodiment 9 based on the embodiment 8. As shown in this figure, the electric power usage cost analysis device in this embodiment includes a "CPU (Central Processing Unit)" that performs various arithmetic processing, a "chipset", a "main memory", a "graphics card", a "non-volatile memory" that holds various programs and data (information), an "I / O controller", a "USB, SATA, LAN terminal, etc.", a "BIOS (UEFI)", a "PCI Express slot", and a "real-time clock". These are connected to each other by a data communication path such as a "system bus" to transmit and receive information and perform processing. The same effect can be obtained even if any one of the embodiments 1 to 7 is used as a base.

[0264] The various programs and data (information) stored in the non-volatile memory are expanded into the main memory when the device is started up, and upon receiving an execution command, the CPU sequentially executes the programs to perform calculations using the data.

[0265] When the device is started, the various programs and data (information) stored in the "non-volatile memory" are read, expanded, and stored in the "main memory," which also provides a work area for those programs. By receiving execution commands, the "CPU" sequentially executes the programs using the data to perform calculations. Note that multiple addresses are assigned to the "main memory" and "non-volatile memory," and programs executed by the "CPU" can identify and access those addresses to exchange data with each other and perform processing.

[0266] In this embodiment, the programs stored in the "main memory" are a weather data acquisition program (q), a conversion rule storage program (r), one or more of the maximum power demand information storage program (a), the maximum electricity usage information storage program (b), the monthly electricity usage information storage program (c), and the total monthly electricity usage information storage program (d), a total monthly electricity charge information storage program (e), an information output program (f), a comparison program (h), a maximum power demand acquisition subprogram for each temperature (n), a future weather information acquisition program (o), and a future maximum power demand forecast value acquisition program (p). In addition, the "main memory" and the "non-volatile memory" store weather data, conversion rules, one or more of the maximum power demand information, maximum electricity usage information, monthly electricity usage information, and total monthly electricity usage information, total monthly electricity charge information, maximum power demand for each temperature, weather information, and forecast values ​​of maximum power demand, etc. FIG. 27 shows a case where all of the above programs and all of the information are stored in the "main memory" and the "non-volatile memory". The following explanation of the operation of the program will be given for the case where all programs and all information are stored and functioned as described above. The same effect can be obtained even if the programs and information described as "any one or more" are stored in one or more, not all four.

[0267] "CPU" is The weather data acquisition program (q) stored in the "main memory" is executed to acquire weather data, such as one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, at a predetermined time interval via the Internet line via "USB, SATA, LAN terminal, etc." The conversion rule storage program (r) stored in the "main memory" is executed to store conversion rules, which are rules for converting the acquired weather data, such as temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, based on the acquired weather data, into representative weather information, which is information regarding representative weather for one or more of the demand time period, day, week, month, and quarter (demand time period, day, week, month, and quarter are time lengths equal to or longer than the specified time interval; the same applies below) in which the weather data was observed. The maximum demand power information holding program (a) stored in the "main memory" is executed to hold maximum demand power information, which is information obtained by acquiring and correlating the maximum demand power for the month, the demand time period in which the maximum demand power occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the demand time period or / the day in which the demand time period is included. A maximum electricity usage information retention program (b) stored in the "main memory" is executed to acquire representative weather information regarding the maximum electricity usage for a day included in the above-mentioned month and the weather (one or more of temperature, humidity, wind speed, sunny, cloudy, rainy, and sunshine hours) for that day and / or the week that includes that day based on the acquired weather data and the stored conversion rule, and then retain maximum electricity usage information which is information associated with this. A monthly electricity usage information retention program (c) stored in the "main memory" is executed to acquire representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or the quarter including that month based on the electricity usage for the month, the acquired weather data, and the stored conversion rules, and then retain monthly electricity usage information which is information associated with this. A total monthly electricity usage information retention program (d) stored in the "main memory" is executed to retain total monthly electricity usage information, which is information obtained by correlating one or more of the total electricity usage during a specified active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays with representative weather information regarding the weather for the month or the quarter including that month (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and hours of sunshine) obtained based on the obtained weather data and the stored conversion rule. A total monthly electricity charge information holding program (e) stored in the "main memory" is executed to hold total monthly electricity charge information showing the total electricity charge for the month. A comparison program (h) stored in the "main memory" is executed to compare one or more of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information for a different period of a day, month, year, or year. The maximum demand power by temperature acquisition subprogram (n) stored in the "main memory" is executed to acquire the maximum demand power by temperature (maximum demand power by temperature), which is the maximum demand power per demand time period for each temperature. The future weather information acquisition program (o) stored in the "main memory" is executed to acquire future weather information, which is information indicating future weather conditions including at least temperature, via the Internet through "USB, SATA, LAN terminal, etc." A future maximum power demand forecast value acquisition program (p) stored in the "main memory" is executed to acquire a future maximum power demand forecast value, which is a forecast value of the maximum power demand at a future point in time, from the temperature included in the acquired future weather information. An information output program (f) stored in the "main memory" is executed to output one or more of the above information via an Internet line through "USB, SATA, LAN terminal, etc.", or via an "I / O controller" or "graphics card" for display on a display, or via "USB, SATA, LAN terminal, etc." for printing on a printer.

[0268] <Effects of the 9th embodiment> In addition to the effects of the first embodiment, the power usage cost analysis device of the ninth embodiment can acquire a future maximum power demand forecast value, which is a forecast value of the maximum power demand at a future time point, from the temperature included in the acquired future weather information, which is information indicating the weather including at least the temperature in the future. Therefore, the power consumer can consider reducing the future maximum power demand forecast value at a future time point, and can reduce the amount of electricity usage. By reducing the amount of electricity usage, it is possible to reduce the electricity bill (charge amount), which is the power usage cost of the power consumer, and also to improve environmental friendliness.

[0269] <Other embodiments: embodiment 10 to embodiment 17> Below, we will explain embodiments other than the above-described embodiments 1 to 9. All of these inventions are useful for power consumers when they consider reducing their electricity usage through various analyses. All of these embodiments can reduce electricity usage, thereby reducing the electricity bill (charge), which is the power usage cost for power consumers, and also improving environmental friendliness.

[0270] <Overview of embodiment 10> The tenth embodiment based on the seventh embodiment is configured to predict a time period during which maximum power demand will occur for each power consumer in each demand time slot based on the frequency of occurrence of maximum power demand in each demand time slot in the past.

[0271] <Configuration of embodiment 10> a demand time slot maximum demand power occurrence frequency holding unit that holds the acquired demand time slot maximum demand power occurrence frequency, which is information indicating the frequency of demand time slots during which maximum demand power occurs in a day; a demand time slot maximum demand power occurrence probability acquisition rule storage unit that stores a demand time slot maximum demand power occurrence probability acquisition rule that acquires a probability of occurrence of maximum demand power in a specified day for each demand time slot based on the stored frequency of occurrence of maximum demand power for each demand time slot; a demand time slot maximum demand power occurrence probability acquisition unit that acquires the maximum demand power occurrence probability for each demand time slot based on the held demand time slot maximum demand power occurrence frequency and a demand time slot maximum demand power occurrence probability acquisition rule; The power usage cost analysis device according to claim 7 may further include a demand time slot maximum demand power occurrence probability output unit that outputs the maximum demand power occurrence probability for each demand time slot, and a demand time slot maximum demand power occurrence probability holding unit that holds the maximum demand power occurrence probability for each demand time slot in association with time information indicating the target day on which the probability was calculated.

[0272] The rule for acquiring the probability of occurrence of maximum demand power for each demand time slot may be configured to acquire a predetermined number (e.g., three) of demand time slots in descending order of probability, instead of acquiring all of the demand time slots in a day. The rule for acquiring the probabili...

Claims

1. An apparatus for analyzing the electricity usage costs of an electricity consumer in an electricity supply and demand system based on a billing system in which a charge amount for an electricity consumer is determined in advance in conjunction with an electricity trading market price that fluctuates according to an available amount of electricity that changes according to weather, the apparatus comprising: A weather data acquisition unit (Q) that acquires weather data at a predetermined time interval, the weather data being one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours; a conversion rule storage unit (R) for storing conversion rules for converting the acquired weather data, i.e., temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours, into representative weather information, which is information related to representative weather of any one or more of the demand time period, day, week, month, and quarter (demand time period, day, week, month, and quarter are time periods equal to or longer than the predetermined time interval; the same applies below) in which the weather data was observed, based on the acquired weather data; a maximum power demand information storage unit (A) for storing maximum power demand information which is information associating a maximum power demand for a month, a demand time period in which the maximum power demand occurred based on the acquired weather data and the stored conversion rule, and representative weather information regarding the weather of the demand time period or / a day including the demand time period (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours); a maximum electricity usage information storage unit (B) for storing maximum electricity usage information which is information associating the maximum electricity usage for one day included in the month with representative weather information on the weather of the day or / the week including the day (one or more of temperature, humidity, wind speed, sunny, cloudy, rainy, and sunshine hours) based on the acquired weather data and the stored conversion rule; a monthly electricity usage information storage unit (C) for storing monthly electricity usage information that is information that associates the monthly electricity usage with representative weather information regarding the weather of the month or a quarter including the month (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) based on the acquired weather data and the stored conversion rule; a total monthly electricity usage information storage unit (D) for storing total monthly electricity usage information that associates one or more of the total electricity usage during a predetermined active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays with representative weather information regarding the weather of the month or a quarter including the month (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) acquired based on the acquired weather data and the stored conversion rule; Any two or more of ((A), (B), (C), or (D)) A total monthly electricity charge information storage unit (E) for storing total monthly electricity charge information indicating the total electricity charge for the month, an information output unit (F) for simultaneously outputting two or more of maximum demand power information and associated representative weather information, maximum electricity usage information and associated representative weather information, monthly electricity usage information and associated representative weather information, total monthly electricity usage information, and total monthly electricity charge information; An electric power usage cost analysis device having the above-mentioned configuration.

2. The electricity usage cost analysis device of claim 1 further comprises a monthly adaptive electricity usage charge information storage unit (G) for storing adaptive electricity usage charge plan information, which is information indicating a charge plan for charges that change according to electricity usage, and monthly adaptive electricity usage charge information, which is information indicating the monthly adaptive electricity usage charge fee.

3. 2. The power usage cost analysis device according to claim 1, further comprising a comparison unit (H) that compares one or more of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information for a different period of a day, a month, a year, or a different year.

4. The power usage cost analysis device of claim 3, wherein the comparison unit (H) has a superiority / inferiority determination means (J) for each specified demand time period that makes a superiority / inferiority determination, which is a determination showing the superiority / inferiority of the same specified demand time period (compared to the previous day, the previous week, the previous month, last year, etc.) from the perspective of power consumption efficiency for each power consumer.

5. The power usage cost analysis device according to claim 3 or claim 4, wherein the comparison unit (H) has an electric power consumer superiority / inferiority determination means (K) for making a superiority / inferiority determination, which is a determination showing superiority / inferiority between different electric power consumer from the standpoint of power consumption efficiency for each specified demand time period.

6. The power usage cost analysis device according to any one of claims 1 to 3, further comprising a power consumption tendency information storage unit (L) for storing power consumption tendency information which is information indicating the power consumption tendency of each power consumer when the power consumption tendency of the power consumer changes depending on the weather.

7. The power usage cost analysis device according to claim 3, wherein the comparison unit (H) further includes a maximum demand power occurrence frequency acquisition means (M) for each demand time period, which acquires the frequency at which maximum demand power occurs in a day for each demand time period.

8. The power usage cost analysis device according to claim 3, wherein the comparison unit (H) further has a maximum demand power by temperature acquisition means (N) for acquiring a maximum demand power by temperature, which is the maximum demand power per demand time period for each temperature.

9. A future weather information acquisition unit (O) for acquiring future weather information, which is information indicating future weather including at least temperature; The electricity usage cost analysis device of claim 8, further comprising: a future maximum electricity demand forecast value acquisition unit (P) that acquires a future maximum electricity demand forecast value, which is a forecast value of maximum electricity demand at a future time, from the temperature included in the acquired future weather information.

10. A method for operating a computer device that analyzes the cost of electricity usage of an electricity consumer in an electricity supply and demand system based on a billing system in which a charge amount for an electricity consumer is determined in advance in conjunction with an electricity trading market price that fluctuates according to an available amount of electricity that changes according to weather, comprising: A meteorological data acquisition step (q) of acquiring at a predetermined time interval one or more of meteorological data including temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours; a conversion rule holding step (r) for holding a conversion rule which is a rule for converting the acquired weather data, i.e., temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine duration, into representative weather information which is information on representative weather of any one or more of the demand time slots, days, weeks, months, and quarters (demand time slots, days, weeks, months, and quarters are time lengths equal to or longer than the predetermined time intervals; the same applies below) in which the weather data was observed; a maximum demand power information holding step (a) for holding maximum demand power information which is information relating to a monthly maximum demand power, a demand time slot in which the maximum demand power occurred based on the acquired weather data and the held conversion rule, and representative weather information relating to the weather of the demand time slot or / a day including the demand time slot (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours); a maximum electricity usage information storage step (b) for storing maximum electricity usage information which is information associating the maximum electricity usage amount for one day included in the month with representative weather information on the weather of the day or / the week including the day (one or more of temperature, humidity, wind speed, sunny, cloudy, rainy, and sunshine hours) based on the acquired weather data and the stored conversion rule; a monthly electricity usage information storage step (c) for storing monthly electricity usage information that is information that associates the monthly electricity usage with representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or a quarter including the month based on the acquired weather data and the stored conversion rule; a total monthly electricity usage information holding step (d) for holding total monthly electricity usage information which is information relating to one or more of the total electricity usage during a predetermined active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays, and representative weather information relating to the weather of the month or a quarter including the month (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) acquired based on the acquired weather data and the stored conversion rule; Any two or more of (any two or more of (a), (b), (c), and (d)) and (e) a total monthly electricity charge information storage step of storing total monthly electricity charge information indicating the total electricity charge for the month, an information output step (f) for simultaneously outputting two or more of maximum demand power information and associated representative weather information, maximum electricity usage information and associated representative weather information, monthly electricity usage information and associated representative weather information, total monthly electricity usage information, and total monthly electricity charge information; A method for operating an electric power usage cost analysis device that is a computer.

11. The operating method of claim 10, further comprising a step (g) of retaining monthly adaptive electricity usage charge fee information, which retains adaptive electricity usage charge plan information, which is information indicating a charge plan for charges that change according to electricity usage, and monthly adaptive electricity usage charge fee information, which is information indicating the monthly adaptive electricity usage charge fee.

12. 11. The method of claim 10, further comprising a comparison step (h) of comparing one or more of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information with information corresponding to said information for a different day, month, year, or different yearly equivalent period.

13. The operating method of claim 12, wherein the comparison step (h) includes a sub-step (j) of determining superiority / inferiority for each specified demand time period, which is a determination indicating superiority / inferiority for the same specified demand time period (compared to the previous day, the previous week, the previous month, last year, etc.) from the standpoint of power consumption efficiency for each power consumer.

14. The operating method of claim 12 or 13, wherein the comparison step (h) includes a sub-step (k) of determining superiority / inferiority between power consumers, which is a determination indicating superiority / inferiority between different power consumers in terms of power consumption efficiency for each specified demand time period.

15. An operating method as described in any one of claims 10 to 12, further comprising a power consumption tendency information retaining step (l) of retaining power consumption tendency information which is information indicating the power consumption tendency of each power consumer when the power consumption tendency of the power consumer changes depending on the weather.

16. The operation method according to claim 12 , wherein the comparison step (h) further includes a sub-step (m) of acquiring a frequency of occurrence of maximum demand power per demand time slot, for acquiring a frequency of occurrence of maximum demand power in a day for each demand time slot.

17. The operation method according to claim 12 , wherein the comparison step (h) further includes a sub-step (n) of acquiring a maximum demand power for each temperature, which is a maximum demand power for each demand time period for each temperature.

18. A future weather information acquisition step (o) of acquiring future weather information which is information indicating future weather including at least temperature; The operating method according to claim 17, further comprising a future maximum power demand prediction value acquisition step (p) of acquiring a future maximum power demand prediction value, which is a prediction value of maximum power demand at a future time point, from the temperature included in the acquired future weather information.

19. A program to be executed by a computer device for analyzing the electricity usage costs of an electricity consumer in an electricity supply and demand system based on a billing system in which the amount of electricity charged to the electricity consumer is determined in advance in conjunction with the electricity trading market price that fluctuates according to the amount of electricity that can be supplied, which varies according to the weather, A meteorological data acquisition step (q) of acquiring at a predetermined time interval one or more of meteorological data including temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours; a conversion rule holding step (r) for holding a conversion rule which is a rule for converting the acquired weather data, i.e., temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine duration, into representative weather information which is information on representative weather of any one or more of the demand time slots, days, weeks, months, and quarters (demand time slots, days, weeks, months, and quarters are time lengths equal to or longer than the predetermined time intervals; the same applies below) in which the weather data was observed; a maximum demand power information holding step (a) for holding maximum demand power information which is information relating to a monthly maximum demand power, a demand time slot in which the maximum demand power occurred based on the acquired weather data and the held conversion rule, and representative weather information relating to the weather of the demand time slot or / a day including the demand time slot (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours); a maximum electricity usage information storage step (b) for storing maximum electricity usage information which is information associating the maximum electricity usage amount for one day included in the month with representative weather information on the weather of the day or / the week including the day (one or more of temperature, humidity, wind speed, sunny, cloudy, rainy, and sunshine hours) based on the acquired weather data and the stored conversion rule; a monthly electricity usage information storage step (c) for storing monthly electricity usage information that is information that associates the monthly electricity usage with representative weather information regarding the weather (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) for the month or a quarter including the month based on the acquired weather data and the stored conversion rule; a total monthly electricity usage information holding step (d) for holding total monthly electricity usage information which is information relating to one or more of the total electricity usage during a predetermined active time period of the month, the total electricity usage during a non-active time period, the total electricity usage on weekdays, and the total electricity usage on holidays, and representative weather information relating to the weather of the month or a quarter including the month (one or more of temperature, humidity, wind speed, sunny / cloudy / rainy, and sunshine hours) acquired based on the acquired weather data and the stored conversion rule; Any two or more of (any two or more of (a), (b), (c), and (d)) and (e) a total monthly electricity charge information storage step of storing total monthly electricity charge information indicating the total electricity charge for the month, an information output step (f) for simultaneously outputting two or more of maximum demand power information and associated representative weather information, maximum electricity usage information and associated representative weather information, monthly electricity usage information and associated representative weather information, total monthly electricity usage information, and total monthly electricity charge information; The program is executed by a power usage cost analysis device which is a computer.

20. The program according to claim 19, further comprising a step (g) of retaining monthly adaptive electricity usage charge information, which retains adaptive electricity usage charge plan information, which is information indicating a charge plan for charges that change according to electricity usage, and monthly adaptive electricity usage charge information, which is information indicating the monthly adaptive electricity usage charge fee.

21. 20. The program of claim 19, further comprising a comparison step (h) of comparing one or more of the stored maximum demand power information, maximum electricity usage information, and monthly electricity usage information with information corresponding to the information for a different day, month, year, or equivalent period of a different year.

22. The program described in claim 21, wherein the comparison step (h) further executes a sub-step (j) of determining superiority / inferiority for each specified demand time period, which is a determination indicating superiority / inferiority for the same specified demand time period (compared to the previous day, week, month, last year, etc.) from the perspective of power consumption efficiency for each power consumer.

23. The program described in any one of claims 21 and 22, wherein the comparison step (h) further executes a sub-step (k) of determining superiority / inferiority between power consumers, which is a determination indicating superiority / inferiority between different power consumers in terms of power consumption efficiency for each specified demand time period.

24. The program according to any one of claims 19 to 21, further comprising a power consumption tendency information retaining step (l) for retaining power consumption tendency information, which is information indicating the power consumption tendency of each power consumer, when the power consumption tendency of the power consumer changes depending on the weather.

25. The program according to claim 21 , wherein the comparison step (h) further causes the computer to execute a sub-step (m) of acquiring a frequency of occurrence of maximum demand power per demand time slot, the sub-step acquiring a frequency of occurrence of maximum demand power in a day for each demand time slot.

26. The program according to claim 21 , wherein the comparison step (h) further causes the computer to execute a sub-step (n) of acquiring a maximum demand power for each temperature, which is a maximum demand power for each demand time slot for each temperature.

27. A future weather information acquisition step (o) of acquiring future weather information which is information indicating future weather including at least temperature; The program according to claim 26, further comprising a future maximum power demand forecast value acquisition step (p) of acquiring a future maximum power demand forecast value, which is a forecast value of maximum power demand at a future time point, from the temperature included in the acquired future weather information.

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