Power saving management system, power saving management method, and power saving management program

Abstract

To provide a power saving management system, method, and program that set a power saving level suitable for each consumer and an incentive for the same and achieve power saving that matches a use state peculiar to each consumer.SOLUTION: A method comprises: constantly measuring power generated, stored, or consumed in a system on the consumer side S101; analyzing temporal fluctuations in total power consumption measured for each consumer, identifying electrical equipment operating on the consumer side, and estimating a type of the electrical equipment, time period, and individual power consumption for the same S102; and transmitting performance data for the same to a management server S103. The management server collects the performance data S201, calculates the transition of the total power consumption in a forecast period S202, generates a target demand curve and generates value information and presentation information S204, transmits the presentation information and power control information to the consumer side, and executes power control as necessary S205.SELECTED DRAWING: Figure 6

Description

[Technical Field]

[0001] The present invention relates to a power management system, a power management method, and a power management program that can promote power saving by managing power in a plurality of user systems provided for each power consumption unit. [Background technology]

[0002] In recent years, in addition to conventional power transmission networks, smart grids (next-generation power transmission networks) and smart communities, which are systems that can control and optimize the flow of power from both the supply and demand sides, are becoming more common as power transmission systems. A known energy trading system allows multiple users to share surplus power at each consumer through such smart grids (see, for example, Patent Document 1). In such smart grids, smart meters that measure power consumption and power generation at each consumer are used to automate monthly meter reading and manage electricity usage in systems such as HEMS (Home Energy Management Systems).

[0003] In the conventional power transmission systems and smart grids described above, systems are being developed that predict future power consumption in homes and commercial facilities, visualize the predicted power consumption on a monitor, and encourage power consumers to save energy, or automatically control electrical appliances such as home appliances to optimize their usage. Predicting future power consumption enables so-called peak shaving, which prevents momentary or localized increases in power consumption. Meanwhile, a method of adjusting power supply and demand that combines distributed power sources, primarily thermal power plants, with renewable energy sources such as solar and wind power, is becoming increasingly popular. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2018-130021 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the system disclosed in the above-mentioned Patent Document 1 collects and analyzes changes in the state of the power grid for multiple consumers and outputs an operation schedule (control information) for each consumer, making it difficult to set an individual power saving level for each consumer.Since the power saving levels possible for each consumer and the factors that provide incentives for them differ, it is difficult to achieve effective power saving effects with a power saving level or incentive method that is common to multiple consumers.

[0006] Therefore, in view of the problems with the conventional technology, the object of the present invention is to provide a power saving management system, a power saving management method, and a power saving management program that can achieve power saving that matches the specific usage conditions of each consumer by setting a power saving level and incentives appropriate for each consumer when controlling power. [Means for solving the problem]

[0007] In order to solve the above-mentioned problems, the present invention provides a power saving management system for managing power saving within a consumer, which is a unit of power consumption, and includes: a performance data generation unit provided within the consumer, which measures the amount of power generated or consumed within the consumer and generates performance data; an individual power calculation unit which calculates a transition of individual power consumption over a predetermined period in the past using the performance data collected from the performance data generation unit; Based on the trends in the demand, the usage patterns of the customer are analyzed, a standard demand curve showing the standard usage tendency is calculated, and multiple energy saving levels corresponding to the energy saving range according to the degree of difficulty of achieving the standard demand curve are calculated. a demand curve generating unit for generating a target demand curve; Among these, a curve corresponding to the power saving level selected by the user of the consumer is an achieved power amount calculation unit that compares the actual performance data and calculates the length of time that the curve is above or below the actual performance data and the power amount related to that length of time as the achieved power amount; 、and an achievement recording unit that records a history of the achieved power amount in the past, and the achieved power amount calculation unit calculates, based on the history recorded by the achievement recording unit, a degree of agreement between a target demand curve corresponding to the power saving level selected by each consumer and actual performance data, Target Demand Curve The length of time during which the power consumption exceeds or falls below the threshold and the amount of power consumed during that length of time are calculated as the achieved power consumption.

[0008] The present invention also provides a power saving management method for managing power saving within a consumer, which is a unit of power consumption, comprising: (1) a performance data generating step in which a performance data generating unit is provided in a consumer facility, and measures an amount of power generated or consumed in the consumer facility to generate performance data; (2) an individual power consumption calculation step in which the individual power consumption calculation unit calculates a transition of individual power consumption over a predetermined period in the past using the performance data collected from the performance data generation unit; (3) The demand curve generating unit calculates the individual power consumption calculated by the individual power calculation step. Based on the trends in the demand, the usage patterns of the customer are analyzed, a standard demand curve showing the standard usage tendency is calculated, and multiple energy saving levels corresponding to the energy saving range according to the degree of difficulty of achieving the standard demand curve are calculated. a demand curve generation step of generating a target demand curve; (4) The target demand curve is calculated by the calculation unit for the achieved power consumption. The curve corresponding to the power saving level selected by the user of the consumer an achieved energy amount calculation step of comparing the calculated values ​​with actual performance data to calculate the length of time during which the demand curves were exceeded or fell below the respective values ​​and the amount of energy pertaining to the respective lengths of time as the achieved energy amount; (5) an achievement recording step in which the achievement recording unit records the history of the past achieved power amounts; Including, In the achieved power amount calculation step, the achieved power amount calculation unit calculates the achieved power amount in accordance with the degree of agreement between a target demand curve corresponding to the power saving level selected by each consumer and actual performance data based on the history recorded by the achievement recording unit. Target Demand Curve The length of time that the target value was exceeded or fell short and the amount of power consumed for that length of time are calculated as the achieved power amount. It is characterized by:

[0010] In the above invention, an information collection unit collects external information including time zones, seasons, or climates; and an external information analysis unit extracts characteristics of frequency components of power consumption and power fluctuation patterns of each consumer from the external information collected by the information collection unit, thereby estimating individual power consumption, which is the power consumption of each device, and analyzing trends in power demand. User selected It is preferable that the system further includes a correlation calculation unit that calculates the correlation between the target demand curve and the actual performance data through machine learning based on the degree of coincidence between the target demand curve and the actual performance data and the trend in electricity demand analyzed by the external information analysis unit, and a demand forecasting unit that predicts the degree of coincidence between the target demand curve and the performance data based on the trend in electricity demand analyzed by the external information analysis unit and the correlation calculated by the correlation calculation unit, and the demand curve generation unit generates a target demand curve according to the degree of coincidence predicted by the demand forecasting unit.

[0011] In the above invention, the degree of coincidence predicted by the demand forecasting unit , and the user selected The target demand curve is output as recommendation information or alert information on the consumer side, and the desired The range of energy savings possible is determined according to the difficulty of achieving the goal. It is preferable that the power saving device further includes an information output unit that allows a user to select a power saving level, and the achieved power amount calculation unit further includes an information output unit that calculates the achieved power amount in accordance with the power saving level selected by the information output unit. Also, in the above invention, it is preferable that the power saving device further includes a value information calculation unit that calculates value information including the price of the power fee equivalent to the amount of power saved or stored in accordance with the achieved power amount calculated by the achieved power amount calculation unit.

[0012] The power-saving management system and method according to the present invention can be realized by executing a power-saving management program written in a predetermined language on a computer. That is, by installing the program of the present invention in an IC chip or memory device of a portable terminal device, a smartphone, a wearable terminal, a mobile PC or other information processing terminal, or a general-purpose computer such as a personal computer or a server computer and executing the program on the CPU, a system having the above-mentioned functions can be constructed and the method according to the present invention can be implemented.

[0013] The power-saving management program of the present invention can be distributed, for example, via a communication line. It can also be transferred as a packaged application that runs on a standalone computer by recording it on a computer-readable recording medium. This recording medium can be recorded on a variety of recording media, including magnetic recording media such as flexible disks and cassette tapes, optical disks such as CD-ROMs and DVD-ROMs, and RAM cards. The computer-readable recording medium on which this program is recorded makes it possible to easily implement the above-described system and method using a general-purpose computer or a dedicated computer, and also makes it easy to store, transport, and install the program. [Effects of the Invention]

[0014] According to the present invention, by comparing the standard demand curve and the target demand curve with actual performance data, and calculating the length of time during which each demand curve is exceeded or fallen below, and the amount of power associated with that length of time, as the achieved amount of power, it is possible to set a power saving level and incentives appropriate for each consumer when controlling power.

[0015] Examples of such incentives include presenting a target demand curve generated according to the degree of coincidence predicted by the demand forecasting unit and outputting recommendation information or alert information on the consumer side, calculating value information according to the achieved power amount, and awarding points, virtual currency, or the like as a bonus according to the calculated value information, etc. As a result, according to the present invention, it is possible to achieve power saving that matches the usage conditions specific to each consumer. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing the overall configuration of a power saving management system according to an embodiment; [Figure 2] 1 is a block diagram showing the device configuration of a user system according to an embodiment; [Figure 3] FIG. 2 is a block diagram showing the internal configuration of a power control terminal according to the embodiment. [Figure 4] 3 is a block diagram showing modules relating to power saving management built in a power control terminal according to the embodiment; FIG. [Figure 5] FIG. 2 is a block diagram showing the internal configuration of a management server according to the embodiment. [Figure 6] FIG. 3 is a flowchart showing the operation of the power saving management system according to the embodiment. [Figure 7] FIG. 10 is a flowchart showing the operation of a demand curve generation process in the power saving management system according to the embodiment. [Figure 8] FIG. 2 is an explanatory diagram of a demand curve in the power saving management system according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0017] An embodiment of the power saving management system according to the present invention will be described in detail below with reference to the accompanying drawings. Note that the embodiment shown below exemplifies an apparatus for embodying the technical concept of the present invention, and the technical concept of the present invention does not limit the material, shape, structure, arrangement, etc. of each component to those described below. The technical concept of the present invention can be modified in various ways within the scope of the claims.

[0018] (Outline of the energy saving management system) 1 is a diagram showing the network configuration of an energy-saving management system 1 according to this embodiment. The energy-saving management system according to this embodiment is a system that manages the power of a plurality of user systems 4, 4... that control and manage power for each unit of power consumption, and is generally composed of a smart meter 41 that serves as a performance data generator installed in each of the user systems 4, 4..., and a management server 2 connected to the smart meter 41 via the Internet, a telephone line, a dedicated line, or the like.

[0019] As shown in Fig. 1, in this embodiment, the power management results of each user system 4, 4... are made available on the management server 2 side. In the power saving management system 1, the management server 2 and power control units 40 provided in each facility (power plant, PPS, consumer, power prosumer, etc.) are interconnected via a communication network 3. A smart meter 41 of each user system 4 is connected to an external power grid at each consumer. Each smart meter 41 measures the amount of power generated or consumed during each power usage period in each user system for each consumer, generates performance data D1, and transmits this data to the management server 2 side via the communication network 3 and the power control unit 40. The management server 2 then manages the power consumption in the user systems 4, 4... based on the performance data D1.

[0020] The power control terminal 40 is configured, for example, as an information processing terminal equipped with a CPU, and is a device that comprehensively controls power equipment at each facility, such as each consumer, as well as at power plants, PPSs, power prosumers, aggregators, etc. It is installed closer to the electrical equipment (load) side of the smart meter 41, which is the performance data generator, within the user system, and is connected to both the smart meter 41 and a distribution board 45 within the user system. The equipment controlled by this power control terminal 40 includes devices that manage power generation, storage, and consumption, such as the smart meter 41, storage battery 42, and PV (Photovoltaics: solar power generation) 43, which are included in the user system 4 installed within the facilities of consumers, power prosumers, etc.

[0021] It should be noted that the various devices controlled by the power control terminal 40 can be omitted as necessary. For example, in the user systems 4, 4..., their power consumption is measured by a smart meter 41, but some consumers have power generation equipment and power storage equipment, some have either power generation equipment or power storage equipment, and some have neither power generation nor power storage equipment and are only equipped with a smart meter 41 and only consume power. Also, power prosumers are in a position to consume power, but can also be equipped with solar power generation and storage batteries and be positioned as power suppliers.

[0022] The communication network 3 is an IP network using the communication protocol TCP / IP such as the Internet, and is a distributed communication network constructed by interconnecting various communication lines (public lines such as telephone lines, ISDN lines, ADSL lines, and optical lines, dedicated lines, third-generation (3G) communication methods such as WCDMA (registered trademark) and CDMA2000, fourth-generation (4G) communication methods such as LTE, and fifth-generation (5G) and later communication methods, as well as wireless communication networks such as Wifi (registered trademark) and Bluetooth (registered trademark). This IP network also includes LANs such as intranets (corporate networks) and home networks using 10BASE-T, 100BASE-TX, etc.

[0023] (Configuration of each device) Next, the configuration of each device will be explained. Note that the term "module" used in the explanation refers to a functional unit that is configured from hardware such as a device or equipment, software with the corresponding function, or a combination of these, and that performs a predetermined operation.

[0024] (1) User System 4 The user system 4 is the general power equipment owned by consumers and power prosumers, and is also a unit of power consumption. A consumer is a contract unit for power equipment that receives and uses power supply, and includes high-voltage large-volume consumers with contracted power of 500 kW or more, high-voltage small-volume consumers with contracted power of 50 kW or more but less than 500 kW, and low-voltage consumers with contracted power of less than 50 kW, such as ordinary households. The user system 4 may also be equipped with power generation and storage facilities. Examples of power generation facilities include solar power generation and wind power generation. The user system 4 includes a power control terminal 40 and a smart meter 41 as a performance data generation unit. The power consuming facilities include not only various home appliances, factory equipment, and office equipment, but also general control devices such as power control devices (IoT devices).

[0025] The power control terminal 40 installed at each consumer is located closer to the electrical appliances (storage battery 42, PV 43, and other loads 441-44n) than the smart meter 41, which serves as the performance data generator, within the consumer's user system 4. It is connected to a distribution board 45 and is capable of acquiring information such as the current, voltage, power waveform, and frequency of the power distributed within the user system 4. It also controls the power generation and charging / discharging of the PV 43 and storage battery 42 installed in each electrical appliance and the user system 4 (consumer). Specifically, the power control terminal 40 is an information processing terminal equipped with a communication function and a CPU. Various functions can be implemented by installing an OS, firmware, and various application software. In this embodiment, the power control terminal 40 functions as a power management unit by installing and executing applications. This information processing terminal can be implemented by a personal computer, a smartphone, or a dedicated device with specialized functions, including a tablet PC, a mobile computer, or a mobile phone.

[0026] The smart meter 41 is a performance data generator that comprehensively manages power generation, storage, and consumption within a user system, which is a unit of demand. Within the user system 4, the smart meter 41 measures power consumption at each consumer and also controls and manages other facilities within the user system, such as storage and generation of power by batteries and solar power generation. The smart meter 41 measures the amount of power generated, stored, or consumed by the consumer during each power usage period, generates performance data D1, and periodically transmits the data to the management server 2 via the power control terminal 40. This performance data D1 is transmitted to the management server 2 via the communication network 3, a telephone line, a dedicated line, or the like. While the present embodiment uses the smart meter 41 as the performance data generator, the present invention is not limited thereto. For example, the smart meter 41 may include the power control terminal 40, and various home appliances, factory equipment, office equipment, and other electronic devices installed within the consumer, which are equipped with a control device such as a power control device (IoT device) and have the function of transmitting their own status information to a communication network as performance data.

[0027] (2) Management Server 2 Configuration The management server 2 is a server device managed and operated by a provider of power saving management services, and as shown in Figure 5, it comprises a user management unit 22, a communication interface 23, a data management unit 24, a demand management unit 25, an external information management unit 26, and an individual service execution unit 27.

[0028] The communication interface 23 is a module that transmits and receives data with other communication devices through the communication network 3, and in this embodiment, is connected to each power control terminal 40, smart meter 41, and external information source 5 to provide this service.

[0029] The user management unit 22 is a group of modules that manage information about users who use the energy-saving service provided by this system, and in this embodiment, it includes a user database 21b, an authentication unit 22a, and a member registration unit 22b. The user database 21b is a storage device that accumulates information about each consumer user and businesses such as aggregators. The authentication unit 22a is a computer or software with that function that verifies the legitimacy of an accessor related to energy-saving management, and performs authentication processing based on a user ID that identifies the user. In this embodiment, the user ID and password are obtained from the accessor's terminal device via the communication network 3, and are compared with the user database 21b to confirm whether the accessor has the right to access the service and whether the accessor is a subscriber.

[0030] Furthermore, member registration unit 22b is a module that accepts member registration for a user based on input operations on a user interface such as a web page for member registration, and acquires user information such as the user's name, address, telephone number, and payment information, as well as an ID and password required for authentication processing in authentication unit 22a. The user information accepted by member registration unit 22b is then stored in user database 21b.

[0031] The external information management unit 26 is a group of modules that collect information from each external information source 5 distributed over the communication network 3. Specifically, the external information management unit 26 includes an external information database 21a, a data accumulation control unit 26a, an external information analysis unit 26b, and an information collection unit 26c.

[0032] The external information database 21a is a storage device that classifies and stores collected external information, and stores each piece of external information in association with additional information such as its type, time information, keywords, and the like.

[0033] The information collection unit 26c is a module that collects external information (such as price fluctuations in the electricity market, weather information, climate information, and other external environmental information) from external information sources 5 distributed over the communication network 3. This information collection unit 26c patrols the external information sources on the communication network 3 by a so-called crawling process to periodically collect predetermined information, and also has the function of searching information sources on the communication network using related keywords, collecting sudden news and weather fluctuations, and storing this information as big data. The information collected by this information collection unit 26c is stored in the external information database 21a via the data storage control unit 26a.

[0034] The data storage control unit 26a is a module that classifies the data collected by the information collection unit 26c and the information analyzed by the external information analysis unit 26b and stores them in the external information database 21a. The data storage control unit 26a associates each piece of collected external information with additional information such as its type, time information, and keywords and stores them in the external information database 21a. The data storage control unit 26a also has a function of searching the external information database 21a in response to a search request from another module such as the demand management unit 25 and returning the detected information. For example, in response to a search request from the demand forecasting unit 25b of the demand management unit 25, the data storage control unit 26a searches for information related to the request and returns it. The information returned to the demand forecasting unit 25b is used for demand forecasting.

[0035] The data management unit 24 is a module that collects and analyzes performance data D1 from each consumer, and includes a performance management database 21c, a performance data collection unit 24b, and an operating electrical appliance specification unit 24a.

[0036] The performance management database 21c is a storage device that collects, stores, and manages performance data from parties involved in the exchange of electricity, such as power plants, consumers, aggregators, etc. Each performance data received from each smart meter is stored in this performance management database and is used for calculating individual power consumption in the individual service execution unit 27 and for calculating correlations in the demand management unit 25.

[0037] The performance data collection unit 24b is a module that collects performance data D1 from the smart meter 41, which is a performance data generation unit, via the power control unit 40, and the collected performance data D1 is stored in the performance management database 21c.

[0038] The operating electric appliance specifying unit 24a is a module that analyzes performance data D1 measured for each consumer by the smart meter 41, and estimates the individual appliances operating within the consumer and their individual power consumption. The operating electric appliance specifying unit 24a also stores estimation history information D2, which is a history of the generated estimation results, in the performance management database 21c in association with information indicating a specific period.

[0039] Here, the hypothetical individual devices may be each of the electrical devices actually present in the home, or may be hypothetical electrical devices corresponding to the magnitude of their estimated resolved power. For example, if the total power consumption measured by the total power measuring device 300 increases by 50 W in a certain period, it is analyzed that an electrical device (the specific device does not need to be specified) consuming 50 W of power has been operated. Also, if the total power consumption measured by the smart meter 41 decreases by 100 W in a certain period, it is analyzed that an electrical device consuming 100 W of power has been stopped. In other words, the hypothetical individual devices in this case refer to an electrical device with an estimated resolved power of 50 W and an electrical device with an estimated resolved power of 100 W (hereinafter, these will be referred to as individual device [50 W], individual device [100 W], etc.).

[0040] The specific period to be analyzed is a period that covers the usage patterns of electrical devices in an individual home (daily usage patterns, weekly usage patterns, etc.), and may be, for example, a 3- to 7-day cycle for each season. The predetermined time unit for calculating the power state parameters is a division of a day into multiple time periods, and may be, for example, four time periods: morning, afternoon, evening, and night, taking into account the daily power usage pattern in the home. Note that this is merely an example. For example, the predetermined time unit may be one hour, or a shorter time unit. Alternatively, the predetermined time unit may be a unit longer than one day, such as several days. The key is to determine the predetermined time unit depending on the granularity at which future total power consumption is desired to be predicted.

[0041] Furthermore, the operating electric appliance specifying unit 24a estimates the power-on state of each individual appliance using the appliance list T1 for the total power consumption calculated from the performance data D1. The operating electric appliance specifying unit 24a also estimates the number of individual appliances operating at the start of the prediction from the real-time total power consumption by applying the appliance list to the total power consumption obtained for each consumer.

[0042] The demand management unit 25 is a group of modules that analyzes trends in power demand from external information collected by the information collection unit 26c, and includes a correlation calculation unit 25a and a demand prediction unit 25b.

[0043] The correlation calculation unit 25a is a module that calculates the correlation between the degree of agreement between the target demand curve and the actual performance data, and the tendency of the power demand analyzed by the external information analysis unit 26b.

[0044] The demand forecasting unit 25b is a module that forecasts the future degree of coincidence between the target demand curve and the performance data based on the tendency of the power demand analyzed by the external information analysis unit 26b and the correlation calculated by the correlation calculation unit 25a.

[0045] The individual service execution unit 27 is a group of modules that individually implements power saving services for each consumer, and in this embodiment, it includes an achievement record database 21e, an individual power calculation unit 27a, a demand curve generation unit 28, a presentation information generation unit 27b, an information output control unit 27c, an achieved power amount calculation unit 27d, and a value information calculation unit 27e.

[0046] The achievement record database 21e is a storage device that records the history of the achieved power amount in the past. The individual power calculation unit 27a is a module that calculates the transition of individual power consumption for each consumer over a predetermined period in the past, using the achievement data D1 collected from the achievement data generation unit.

[0047] The demand curve generation unit 28 is a module that calculates a standard demand curve, which is the trend in standard power consumption over a specified period, based on the trend in individual power consumption over a specified period calculated by the individual power calculation unit, and generates a target demand curve with a power saving level different from the standard demand curve based on the standard demand curve.In this embodiment, the demand prediction unit 25b generates a target demand curve according to the degree of coincidence predicted.

[0048] The presentation information generation unit 27b is a module that generates presentation information to be presented to the user, and the presentation information generated here is transmitted to the consumer side through the information output control unit 27c and displayed or output through an output device such as a display provided on the consumer side.

[0049] The information presented here includes the target demand curve, recommendation information, and alerts that are output and displayed to help achieve the target demand curve, as well as battery control information for consumers equipped with storage batteries. Examples of recommendation information or alerts include messages requesting power saving and information on specific home appliance operation (on or off). For example, messages such as "achievable with normal usage," "achievable without difficulty," or "achievable with some effort" may be presented according to the power saving level in accordance with the consumer's contract or user settings. Furthermore, if the demand curve is formed in accordance with the power saving request, information indicating that the value information calculated in the value information calculation step will be awarded as a bonus, or special information such as free or discounted electricity charges equivalent to the amount of energy charged to the storage battery, or reward points, may be displayed to stimulate incentives.

[0050] The information output control unit 27c is a module that presents a target demand curve generated according to the degree of coincidence predicted by the demand forecasting unit, and outputs recommendation information or alert information on the consumer side. The information output control unit 27c also has a function of receiving an input signal for selecting a power saving level desired by the user of the consumer for the output recommendation information or alert information. In this embodiment, three power saving levels can be selected: "soft," which is a level similar to normal; "middle," which is a level that can be achieved without difficulty; and "hard," which is a level that can be achieved with some effort.

[0051] The achieved energy calculation unit 27d is a module that compares the standard demand curve and the target demand curve with actual performance data, and calculates the length of time during which the demand curve is exceeded or fallen short, and the energy amount associated with that length of time, as the achieved energy amount. In this embodiment, the achieved energy amount is calculated based on the history recorded in the achievement record database 21e, according to the degree of agreement between the target demand curve corresponding to the power saving level selected by each consumer and the actual performance data. Specifically, the information output control unit 27c receives the power saving level selected by the user of the consumer, sets a target demand curve according to the received power saving level, and calculates the achieved energy amount according to the degree of agreement between the set target demand curve and the actual performance data.

[0052] The value information calculation unit 27e is a module that calculates value information corresponding to the achieved power amount calculated by the achieved power amount calculation unit. This value information includes, for example, the cost of electricity equivalent to the amount of power saved by forming a demand curve according to the power saving request from the management server side, the cost of electricity equivalent to the amount of power charged to the storage battery, etc. In accordance with this calculated value information, an incentive is given, such as a bonus of free of charge, a discount, or points. This bonus can be provided, for example, when a demand curve is formed according to the target demand curve at the timing requested by the PPS or aggregator, or when a demand curve is formed at the timing requested by the PPS or aggregator and in accordance with the power saving request. For example, the amount required to charge the storage battery can be deducted from the monthly electricity bill, or a gift certificate or points can be given as an incentive each month.

[0053] (3) Power control terminal 40 3, the power control terminal 40 includes a CPU 402, a memory 403, an input interface 404, a storage 401, an output interface 405, and a communication interface 406. In this embodiment, these devices are connected via a CPU bus 400, enabling data to be exchanged between them.

[0054] The memory 403 and storage 401 are storage devices that store data in recording media and read out the stored data in response to a request from each device, and can be configured, for example, with a hard disk drive (HDD), a solid state drive (SSD), a memory card, etc. In particular, in this embodiment, the storage 401 functions as a data recording unit that records estimation history information D2 that chronologically records the power supply states of individual devices based on the estimation results by the operating electrical device specifying unit 402d, which is an individual device estimation unit, and also functions as an actual power consumption accumulation unit that accumulates actual power consumption information D5 related to the power actually consumed within the consumer.

[0055] The input interface 404 is a module that receives control signals from each piece of equipment installed in the user system. The received control signals are transmitted to the CPU 402 and processed by the OS and each application. On the other hand, the output interface 405 is a module that outputs control signals to each piece of equipment installed in the user system. Each piece of equipment installed in such a user system varies depending on the type of consumer or prosumer. For example, at a consumer, power consumption is measured by a smart meter 41, and with regard to power generation and storage, some have both solar power generation and storage equipment, some have either solar power generation or storage battery equipment, and some have neither power generation nor storage equipment. At a prosumer, power consumption is measured by a smart meter 41, and control signals for a solar power generation (PV) 42 and a storage battery 42 are input and output.

[0056] The communication interface 406 is a module that transmits and receives data to and from other communication devices, and communication methods include, for example, public lines such as telephone lines, ISDN lines, ADSL lines, and optical lines, dedicated lines, third-generation (3G) communication methods such as WCDMA (registered trademark) and CDMA2000, fourth-generation (4G) communication methods such as LTE, and fifth-generation (5G) and later communication methods, as well as wireless communication networks such as Wifi (registered trademark) and Bluetooth (registered trademark).

[0057] The CPU 402 is a device that performs various arithmetic processing required to control each unit, and by executing various programs, various modules are virtually constructed on the CPU 402. An OS (Operating System) is started and executed on the CPU 402, and this OS manages and controls the basic functions of each power control terminal 40. In addition, various applications can be executed on this OS, and by executing the OS program on the CPU 402, various functional modules are virtually constructed on the CPU.

[0058] In this embodiment, by executing browser software on CPU 402, it is possible to view and input information on the system through this browser software. More specifically, this browser software is a module for viewing web pages, downloading HTML (HyperText Markup Language) files, image files, music files, etc. from management server 2 via communication network 3, analyzing the layout, and displaying and playing them. This browser software also allows users to use forms to send data to a web server and run application software written in JavaScript (registered trademark), Flash, Java (registered trademark), etc., and each user can use this browser software to access the power-saving management service provided by management server 2.

[0059] As shown in Fig. 4, the CPU 402 includes a total power consumption acquisition unit 402a, a power waveform information acquisition unit 402b, and a time variation calculation unit 402c as actual power consumption management modules for detecting the operating status of loads 441 to 44n within the consumer via an input interface 404. The CPU 402 also includes an operating electrical appliance identification unit 402d, a likelihood estimation unit 402e, and a power prediction unit 402f as modules for identifying electrical appliances in operation within the consumer and predicting power consumption. The CPU 402 also includes a learning unit 402g as a module for causing the power prediction unit 402f to perform machine learning. The CPU 402 also includes a charge / discharge control unit 402h as a module for actually controlling the power generation and charging / discharging of the PV 43 and storage battery 42 installed within the consumer.

[0060] The total power consumption acquisition unit 402a is a module that is connected to the distribution board 45 via the input interface 404 and measures and acquires the current, voltage, etc. of power related to the power distributed within the user system 4, and the power waveform information acquisition unit 402b is a module that measures and acquires the waveform and frequency of power related to the power distributed within the user system 4 through the distribution board 45. The time variation calculation unit 402c is a module that calculates the time variation of the total power consumption measured by the total power consumption acquisition unit 402a. The total power consumption acquisition unit 402a, the power waveform information acquisition unit 402b, and the time variation calculation unit 402c constitute an actual power consumption management module that is an actual power consumption accumulation unit, and various information obtained by the total power consumption acquisition unit 402a, the power waveform information acquisition unit 402b, and the time variation calculation unit 402c is accumulated in the storage 401 as actual power consumption information D5 related to the power actually consumed. This actual power consumption information D5, together with the estimated history information D2, is used as training data for training the artificial intelligence of the power prediction unit 402f.

[0061] The operating electric appliance identifying unit 402d is installed in the consumer on the electric appliance (load) side of the smart meter 41, which is the performance data generating unit, and is a module that functions as an individual appliance estimation unit that analyzes the temporal fluctuation of the total power consumption measured for each consumer by the smart meter 41 and calculated by the temporal fluctuation calculating unit 402c, and estimates the individual appliances operating in the consumer and their individual power consumption, which is the power consumed by those appliances. The operating electric appliance identifying unit 402d also stores estimation history information D2, which is a history of the generated estimation results, in the storage 401 in association with information indicating a specific period. The likelihood of the estimation by this operating electric appliance identifying unit 402d is verified by the likelihood estimating unit 402e.

[0062] Here, the hypothetical individual devices may be each of the electrical devices actually present in the home, or may be hypothetical electrical devices corresponding to the magnitude of their estimated resolved power. For example, if the total power consumption measured by the total power measuring device 300 increases by 50 W in a certain period, it is analyzed that an electrical device (the specific device does not need to be specified) consuming 50 W of power has been operated. Also, if the total power consumption measured by the smart meter 41 decreases by 100 W in a certain period, it is analyzed that an electrical device consuming 100 W of power has been stopped. In other words, the hypothetical individual devices in this case refer to an electrical device with an estimated resolved power of 50 W and an electrical device with an estimated resolved power of 100 W (hereinafter, these will be referred to as individual device [50 W], individual device [100 W], etc.).

[0063] The specific period to be analyzed is a period that covers the usage patterns of electrical devices in an individual home (daily usage patterns, weekly usage patterns, etc.), and may be, for example, a 3- to 7-day cycle for each season. The predetermined time unit for calculating the power state parameters is a division of a day into multiple time periods, and may be, for example, four time periods: morning, afternoon, evening, and night, taking into account the daily power usage pattern in the home. Note that this is merely an example. For example, the predetermined time unit may be one hour, or a shorter time unit. Alternatively, the predetermined time unit may be a unit longer than one day, such as several days. The key is to determine the predetermined time unit depending on the granularity at which future total power consumption is desired to be predicted.

[0064] Furthermore, the operating electric appliance identifying unit 402d estimates the power-on state of each individual appliance based on the total power consumption acquired by the total power consumption acquiring unit 402a, using the appliance list T1 stored in the storage 401. The operating electric appliance identifying unit 402d also estimates the number of individual appliances operating at the start of the prediction from the real-time total power consumption by applying the appliance list to the total power consumption acquired by the total power consumption acquiring unit 402a.

[0065] The power prediction unit 402f is a module that predicts the power consumption of an individual device (hereinafter referred to as individual power consumption) in a future period for which prediction is desired (prediction period) using the learning data generated by the learning unit 402g.

[0066] In more detail, the power prediction unit 402f obtains a device list T1 by estimating hypothetical individual devices and their individual power consumption, and uses this device list T1 to estimate the number of individual devices in operation. Based on this estimation result, the power prediction unit 402f calculates power state parameters that represent the power state of the individual devices in predetermined time units, thereby generating learning data related to the power consumption of the individual devices. The power prediction unit 402f also functions as an individual power prediction unit that estimates the number of individual devices in operation at the start of prediction from the total power consumption measured in real time using the estimation history information D2 recorded in the storage 401, and predicts the transition of individual power consumption over the prediction period from the start of prediction using the power state parameters for the period corresponding to the prediction period.

[0067] Furthermore, the power prediction unit 402f causes the time variation calculation unit 402c to calculate the time variation of the total power consumption and power waveforms measured in real time by the total power consumption acquisition unit 402a and the power waveform information acquisition unit 402b.Then, by applying the device list T1 (virtualized individual devices and their individual power consumption) stored in the storage 401 for the period corresponding to the prediction period, the number of operating individual devices at the start of the prediction is estimated from the real-time total power consumption.The power prediction unit 402f then uses the power state parameters for the period corresponding to the prediction period to predict the transition of individual power consumption during the prediction period from the start of the prediction.

[0068] In this embodiment, the power prediction unit 402f predicts the transition of total power consumption during a prediction period based on the transition of individual power consumption during the prediction period predicted by the operating electric appliance identifying unit 402d. Specifically, the power prediction unit 402f predicts the transition of total power consumption during the prediction period by summing up the individual power consumptions at each time point during the prediction period predicted by the operating electric appliance identifying unit 402d.

[0069] The charge / discharge control unit 402h not only controls power generation and charging / discharging of the PV 43 and the storage battery 42 through the output interface 405, but also has a function of notifying the user of the total power consumption predicted by the power prediction unit 402f, for example. Alternatively, if the total power consumption predicted by the power prediction unit 402f exceeds a threshold, a warning message may be sent, including information on the time period and the extent to which the threshold is exceeded.

[0070] (Operation of the power saving management system) The power-saving management method of the present invention can be implemented by operating the power-saving management system described above. Fig. 6 is a flow chart showing the operation of the power-saving management system. Note that the processing procedure described below is merely an example, and each process may be modified as much as possible. Furthermore, steps in the processing procedure described below may be omitted, replaced, or added as appropriate depending on the embodiment.

[0071] As shown in Figure 6, the user system 4 on the consumer side constantly measures the power being generated, stored, or consumed within the system (S101). In this power measurement, the temporal fluctuation of the power waveform is also measured and recorded as needed. Meanwhile, the management server constantly collects and classifies external information in conjunction with the measurement of power consumption on the consumer side. Then, periodically, or as soon as a predetermined amount of information has been accumulated, the collected and classified external information is stored in the external information database 21a.

[0072] Next, the operating electric appliance identifying unit 402d analyzes the temporal fluctuations in the total power consumption measured on a consumer-by-consumer basis to identify the electric appliances operating in the user system 4, and estimates the type of the identified electric appliance, the time period (including the date, time, year, month, and day, etc.), and the individual power consumption of the identified electric appliance (S102). Using this estimation history information, the operating number of individual appliances at the start of the prediction is estimated from the total power consumption measured in real time. At this time, the operating electric appliance identifying unit 402d analyzes the power waveform measured by the smart meter 41 and its temporal changes, and extracts the characteristics of the frequency component and power fluctuation pattern to estimate the individual appliances operating, their individual power consumption, and its duration.

[0073] Then, the measurement results from the smart meter 41 and information about the identified electrical appliances are accumulated and generated as performance data D1, which is then transmitted from each user system to the management server 2 (S103) and collected by the management server 2 (S201).

[0074] Next, the transition of individual power consumption from the prediction start point to the prediction period is calculated using the power supply state parameters for the period corresponding to the prediction period, and the transition of total power consumption during the prediction period is calculated based on the transition of individual power consumption during the prediction period predicted by the operating electric appliance specifying unit 402d (S202). Furthermore, based on the calculation results by the operating electric appliance specifying unit 402d, a standard demand curve is calculated and a target demand curve is generated (S203).

[0075] Specifically, as shown in FIG. 8, a standard demand curve C0 is created based on the weather and day of the week of the day, based on normal electricity usage, and target demand curves C1 to C3 for different power-saving levels are generated based on this standard demand curve. For example, as shown in the figure, a range of possible power savings according to the power-saving level is assumed, and recommended power-saving levels are set and presented to the user for selection. In this embodiment, three power-saving levels are selectable: "soft," which is the same level as usual; "medium," which is a level that can be achieved without difficulty; and "hard," which is a level that may be achieved with some effort. Furthermore, if the target demand curve for the selected power-saving level is achieved (for example, within plus or minus 5%), a bonus or other benefit is provided.

[0076] To explain in detail how the standard demand curve is calculated and the target demand curve is generated, an information collection step of collecting and classifying external information is constantly performed in the management server (S301), as shown in Fig. 7. This collected external information is stored in the external information database 21a periodically or as soon as a predetermined amount of information is accumulated.

[0077] Next, an external information analysis step of analyzing the trend of power demand is executed (S302). In this external information analysis step, the external information analysis unit 26b analyzes the trend of power demand based on the external information collected in the information collection step. After that, the achieved power amount calculation unit 27d refers to the past standard demand curve and target demand curve calculated and recorded, compares the past standard demand curve and target demand curve with actual performance data, and acquires the length of time during which each demand curve was exceeded or fell short, and the power amount corresponding to that length of time, as the achieved power amount (S303).

[0078] Then, the correlation calculation unit 25a executes a correlation calculation step of calculating the correlation between the degree of coincidence between the target demand curve and actual performance data and the tendency of power demand analyzed in the external information analysis step (S304). In conjunction with this correlation calculation step, a demand forecasting step is executed (S305). In this demand forecasting step, the demand forecasting unit 25b predicts the degree of coincidence between the target demand curve and performance data based on the tendency of power demand analyzed in the external information analysis step and the correlation calculated by the correlation calculation unit. Thereafter, a demand curve generation step is executed (S306) of generating a target demand curve according to the degree of coincidence predicted by the demand forecasting unit 25b.

[0079] Based on the standard demand curve and target demand curve generated in this way, a value information calculation step and a presentation information generation step are executed (S204). Specifically, in the value information calculation step, the value information calculation unit 27e calculates value information according to the achieved power amount calculated in the achieved power amount calculation step, and in the presentation information generation step, the information output control unit 27c generates power saving recommendation information or alert information as presentation information in combination with the target demand curve generated according to the degree of coincidence predicted in the demand forecast prediction step. In addition, this presentation information may include value information such as the value of the virtual currency calculated in the value information calculation step.

[0080] The information generated includes the target demand curve, recommendation information, and alerts that are output and displayed to help consumers achieve the target demand curve, as well as battery control information for consumers equipped with storage batteries. Recommendation information and alerts include messages requesting power saving and information on specific home appliance operation (on or off). For example, messages such as "achievable with normal usage," "achievable without difficulty," or "achievable with some effort" are presented according to the power saving level in accordance with the contract with the consumer or the user's settings. Furthermore, if the demand curve is formed according to the power saving request, information that the value information calculated in the value information calculation step will be awarded as a bonus, or special information such as free or discounted electricity charges for the amount of power charged in the storage battery, or reward points, may be displayed to stimulate incentives. This bonus can be provided, for example, when the demand curve is formed according to the target demand curve at the timing requested by the PPS or aggregator, or when the demand curve is formed according to the timing requested by the PPS or aggregator and in accordance with the power saving request. Examples of such bonuses include a method of deducting the amount required to charge the storage battery from the monthly electricity bill, or a method of awarding gift certificates or points as an incentive each month.

[0081] Thereafter, the information output control unit 27c transmits the presentation information and power control information to the consumer side, and presents the target demand curve on the consumer side, outputs recommendation information or alert information, and executes power control as necessary (S205 and S104). In addition, in this information output step, value information such as the value of the virtual currency calculated in the value information calculation step may be presented. Next, the information output control unit 27c prompts the user of the consumer to select a desired power-saving level for the recommendation information or alert information output by the information output control unit 27c, and receives an input signal for the selection (S105). Then, an achieved power amount calculation step is executed to calculate an achieved power amount according to the selected power-saving level (S206). In this achieved power amount calculation step, a target demand curve is set according to the power-saving level selected by the user of the consumer, and the achieved power amount calculation unit 27d compares the past standard demand curve or the set target demand curve with actual performance data, and calculates, as the achieved power amount, the length of time during which the demand curve was above or below each curve and the power amount corresponding to that length of time, according to the degree of agreement between the set target demand curve and the actual performance data.

[0082] (Actions and Effects) According to the present embodiment described above, by comparing the standard demand curve and the target demand curve with actual performance data, and calculating the length of time during which each demand curve was exceeded or fell short, and the amount of power related to that length of time, as the achieved power amount, it is possible to set a power saving level and incentives appropriate for each consumer when controlling power.

[0083] In particular, in this embodiment, as an incentive, a target demand curve is presented, and for example, a message requesting power saving according to the power saving level, information on the specific operation (on or off) of the home appliance, a bonus when the demand curve is formed according to the power saving request, and information on benefits equivalent to the amount of charge are displayed. As a result, according to this embodiment, power saving that matches the usage status specific to each consumer can be achieved.

[0084] In this embodiment, the time variation of total power consumption and power waveform (frequency) are measured and analyzed, the individual devices operating in the user system and their power consumption are estimated, and the future total power consumption is predicted based on the characteristics of each individual device, to generate a target demand curve. As a result, according to this embodiment, power control using a smart grid and the accuracy of predictions of future power consumption by small-unit facilities such as individual homes or small buildings can be performed independently using a power control terminal on the local side, making it possible to implement power saving that covers the individual and short-term state changes unique to each consumer.

[0085] In addition, the estimated history of individual devices and the prediction of total power consumption are also analyzed for correlation with external information, and by extracting the characteristics of frequency components and power fluctuation patterns, the individual devices in operation and their individual power consumption, which is the amount of power consumed, are estimated.This is then reflected in the next prediction process through machine learning, making it possible to achieve individual power control according to the power consumption patterns unique to each consumer, further improving the accuracy of predictions. [Explanation of symbols]

[0086] D1...Actual data D2…Estimated history information D5...Actual power consumption information T1...Equipment List 1...Power saving management system 2...Administration Server 3. Communication network 4,4...User system 5…External information sources 11...CPU 21a…External information database 21b...User database 21c...Performance management database 21d… Supply and demand type database 21e...Achievement Record Database 22...User Management Department 22a...Authentication section 22b...Membership Registration Section 23...Communication interface 24...Data Management Department 24a...Operating Electrical Equipment Specific Section 24b...Performance data collection section 25…Demand Management Department 25a...Correlation calculation unit 25b...Demand Forecasting Department 26…External Information Management Department 26a...Data storage control unit 26b…External information analysis department 26c…Information Gathering Department 27...Individual Service Execution Department 27a...Individual power calculation section 27b…Presentation information generation unit 27c...Information output control section 27d…Achieved electric energy calculation section 27e...Value Information Calculation Department 28...Demand curve generator 40...Power control unit 41...Smart meter 42...Storage battery 43...PV 45...Distribution board 300...Total power measuring device 400...CPU bus 401...Storage 402...CPU 402a...Total power consumption acquisition unit 402b...Power waveform information acquisition unit 402c...Time variation calculation unit 402d...Operating Electrical Equipment Specific Section 402e...Likelihood estimation unit 402f…Power forecasting section 402g…Study section 402h: Charge / discharge control unit 403...Memory 404...input interface 405...Output interface 406...Communication interface 441~44n...Load

Claims

1. A power saving management system that manages power saving within a consumer, which is a unit of power consumption, a performance data generating unit provided in the customer facility and measuring the amount of power generated or consumed in the customer facility to generate performance data; an individual power consumption calculation unit that calculates a transition of individual power consumption over a predetermined period in the past using the performance data collected from the performance data generation unit; a demand curve generation unit that analyzes the usage pattern of the consumer based on the transition of the individual power consumption, calculates a standard demand curve that indicates a standard usage tendency, and generates, for the standard demand curve, a plurality of target demand curves corresponding to power saving levels that are power saving possible ranges according to the degree of difficulty of achieving the levels; an achieved power amount calculation unit that compares a curve corresponding to a power saving level selected by a user of the consumer among the target demand curves with actual performance data, and calculates the length of time during which the power consumption exceeds or falls below the curve and the amount of power consumption related to that length of time as the achieved power amount; an achievement recorder that records the history of the amount of power achieved in the past; Equipped with The achieved power amount calculation unit calculates, based on the history recorded by the achievement recording unit, the length of time during which the power consumption exceeded or fell below the target demand curve and the amount of power consumed for that length of time, in accordance with the degree of agreement between the target demand curve corresponding to the power saving level selected by each consumer and actual performance data, as the achieved power amount. The present invention relates to a power saving management system.

2. an information collection unit that collects external information including time zones, seasons, or climates; an external information analysis unit that extracts characteristics of frequency components of power consumption and power fluctuation patterns of each consumer from the external information collected by the information collection unit, thereby estimating individual power consumption, which is the power consumption of each individual device that is in operation, and analyzing trends in power demand; a correlation calculation unit that calculates a correlation between the target demand curve selected by the user and the actual performance data through machine learning based on the degree of agreement between the target demand curve selected by the user and the actual performance data, and the tendency of the power demand analyzed by the external information analysis unit; a demand forecasting unit that forecasts a degree of coincidence between the target demand curve and the actual data based on the tendency of the power demand analyzed by the external information analysis unit and the correlation calculated by the correlation calculation unit; Furthermore, The demand curve generation unit generates a target demand curve according to the degree of coincidence predicted by the demand forecasting unit. The power saving management system according to claim 1 .

3. The system further includes an information output unit that outputs the degree of coincidence predicted by the demand forecasting unit and the target demand curve selected by the user as recommendation information or alert information on the consumer side, and allows the user of the consumer to select a power saving level that is within a power saving range according to a desired degree of difficulty of achievement, The achievable power amount calculation unit calculates the achievable power amount according to the power saving level selected by the information output unit. The power saving management system according to claim 2 .

4. The energy saving management system according to claim 1, further comprising a value information calculation unit that calculates value information including the value of the electricity fee equivalent to the amount of energy saved or stored according to the achieved energy amount calculated by the achieved energy amount calculation unit.

5. A power saving management method for managing power saving within a consumer, which is a unit of power consumption, comprising: a performance data generating step in which a performance data generating unit is provided in the consumer facility, and measures an amount of power generated or consumed in the consumer facility to generate performance data; an individual power calculation step in which an individual power calculation unit calculates a transition of individual power consumption over a predetermined period in the past using the performance data collected from the performance data generation unit; a demand curve generation step in which a demand curve generation unit analyzes the usage pattern of the consumer based on the transition of the individual power consumption calculated in the individual power calculation step, calculates a standard demand curve showing a standard usage tendency, and generates, for the standard demand curve, a plurality of target demand curves corresponding to power saving levels that are power saving possible ranges according to the degree of difficulty of achieving the power saving levels; an achieved power amount calculation step in which an achieved power amount calculation unit compares a curve corresponding to a power saving level selected by a user of the consumer among the target demand curves with actual performance data, and calculates the length of time during which the demand curve is above or below each curve and the amount of power related to that length of time as the achieved power amount; an achievement recording step in which an achievement recording unit records a history of the amount of power achieved in the past; Including, In the achieved power amount calculation step, the achieved power amount calculation unit calculates, based on the history recorded by the achievement recording unit, the length of time during which the power consumption exceeded or fell below the target demand curve according to the degree of agreement between the target demand curve corresponding to the power saving level selected by each consumer and actual performance data, and the amount of power related to that length of time, as the achieved power amount. A power saving management method characterized by:

6. an information collecting step in which an information collecting unit collects external information including time zones, seasons, or climates; an external information analysis step in which an external information analysis unit extracts characteristics of frequency components of power consumption and power fluctuation patterns of each consumer from the external information collected in the information collection step, thereby estimating individual power consumption, which is the power consumption of each device that is in operation, and analyzing trends in power demand; a correlation calculation step in which a correlation calculation unit calculates a correlation between the target demand curve selected by the user and the actual performance data through machine learning based on the degree of agreement between the target demand curve selected by the user and the actual performance data, and the tendency of power demand analyzed by the external information analysis unit; a demand forecasting step in which a demand forecasting unit predicts a degree of coincidence between the target demand curve and the actual data based on the tendency of the power demand analyzed in the external information analysis step and the correlation calculated by the correlation calculation unit; further comprising In the demand curve generation step, a target demand curve is generated according to the degree of coincidence predicted by the demand forecasting unit.

6. The power saving management method according to claim 5.

7. The energy saving management method according to claim 6, further comprising an information output step in which the information output unit outputs the degree of coincidence predicted in the demand forecast prediction step and the target demand curve selected by the user as recommendation information or alert information on the consumer side, and allows the user of the consumer to select an energy saving level that is within the energy saving range according to the desired difficulty of achievement.

8. The power saving management method according to claim 5, further comprising a value information calculation step in which the value information calculation unit calculates value information including the price of the power fee equivalent to the amount of power saved or stored according to the achieved power amount calculated in the achieved power amount calculation step.

9. A power saving management program that manages power saving within a consumer, which is a unit of power consumption, a performance data generating unit provided in the customer facility and measuring the amount of power generated or consumed in the customer facility to generate performance data; an individual power consumption calculation unit that calculates a transition of individual power consumption over a predetermined period in the past using the performance data collected from the performance data generation unit; a demand curve generation unit that analyzes the usage pattern of the consumer based on the transition of the individual power consumption, calculates a standard demand curve that indicates a standard usage tendency, and generates, for the standard demand curve, a plurality of target demand curves corresponding to power saving levels that are power saving possible ranges according to the degree of difficulty of achieving the levels; an achieved power amount calculation unit that compares a curve corresponding to a power saving level selected by a user of the consumer among the target demand curves with actual performance data, and calculates the length of time during which the power consumption exceeds or falls below the curve and the amount of power consumption related to that length of time as the achieved power amount; Achievement record section that records the history of the amount of power achieved in the past It functions as The achieved power amount calculation unit calculates, based on the history recorded by the achievement recording unit, the length of time during which the power consumption exceeded or fell below the target demand curve according to the degree of agreement between the target demand curve corresponding to the power saving level selected by each consumer and actual performance data, and the amount of power related to that length of time, as the achieved power amount. A power saving management program.

10. The computer an information collection unit that collects external information including time zones, seasons, or climates; an external information analysis unit that extracts characteristics of frequency components of power consumption and power fluctuation patterns of each consumer from the external information collected by the information collection unit, thereby estimating individual power consumption, which is the power consumption of each individual device that is in operation, and analyzing trends in power demand; a correlation calculation unit that calculates a correlation between the target demand curve selected by the user and the actual performance data through machine learning based on the degree of agreement between the target demand curve selected by the user and the actual performance data, and the tendency of the power demand analyzed by the external information analysis unit; a demand forecasting unit that forecasts the degree of coincidence between the target demand curve and the actual data based on the tendency of the power demand analyzed by the external information analysis unit and the correlation calculated by the correlation calculation unit; It further functions as The demand curve generation unit generates a target demand curve according to the degree of coincidence predicted by the demand forecasting unit.

10. The power saving management program according to claim 9.

11. The computer is further made to function as an information output unit that outputs the degree of coincidence predicted by the demand forecasting unit and the target demand curve selected by the user as recommendation information or alert information on the consumer side, and allows the user of the consumer to select a power saving level that is within a range of possible power saving according to the desired difficulty of achievement, The achievable power amount calculation unit calculates the achievable power amount according to the power saving level selected by the information output unit.

11. The power saving management program according to claim 10.

12. The power saving management program of claim 9, further causing the computer to function as a value information calculation unit that calculates value information including the value of the electricity fee equivalent to the amount of electricity saved or stored according to the achieved power amount calculated by the achieved power amount calculation unit.

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