Information processing device, information processing method and program

Abstract

The objective of the present invention is to optimize the timing of power consumption / power generation for an entire building by forecasting the amount of electricity generated by means of renewable energy and performing optimal control of storage batteries, for example.　A server 1 comprises: a power generation forecasting unit 71 that forecasts the amount of power generated by solar power generating equipment SGS and outputs the forecast power generation amount; a demand forecasting unit 72 that forecasts the amount of power consumed in a building T1 and outputs the forecast power consumption amount; an optimal solution determining unit 53 that determines a power supply / demand gap on the basis of the forecast values; a storage battery control unit 84 that controls a storage battery TS; and a power control unit 54 that controls the amount of power generated, the amount of power consumed in the building, and a charge / discharge amount of the storage battery on the basis of the determination result. This makes it possible to balance the power supply and demand of the entire building efficiently, make effective use of surplus power, suppress power peaks, respond to demand, and respond to sudden power demands.

Description

Information processing device, information processing method, and program

[0001] The present invention relates to an information processing device, an information processing method, and a program.

[0002] Conventionally, energy management systems for buildings such as buildings, factories, and commercial facilities have been known as EMS (Energy Management Systems) (see, for example, Patent Document 1). Generally, this type of system adjusts the ON / OFF and settings of air conditioning equipment and lighting equipment in order to reduce power consumption.

[0003] Patent No. 6954832

[0004] However, while conventional technologies can certainly reduce power consumption in recent years, with the recent spread of renewable energy, solar power generation equipment is being installed on the roofs of buildings, solar carport power plants are being installed in parking lots, EV charging devices are being installed, and storage batteries are being installed. This means that there is a demand for solutions to problems such as the need to go beyond controlling power demand within buildings and to integrate the monitoring, control, and optimization of energy resources including the surrounding areas of buildings (roofs, parking lots, etc.), but conventional technologies, including the technology in Patent Document 1, are not able to adequately meet these demands.

[0005] The present invention was made in consideration of these circumstances, and aims to optimize the timing of power consumption / generation for the entire building by predicting not only the power demand for air conditioning equipment, lighting equipment, etc., but also the amount of power generated by renewable energy, optimal control of storage batteries, optimal control of EV charging equipment, etc.

[0006] In order to achieve the above-mentioned object, one embodiment of the information processing device of the present invention is an information processing device that has at least one of a storage battery and / or a power generation facility and optimally controls the amount of power interchange for a building that uses power supplied from at least one of the storage battery and / or the power generation facility, and is equipped with at least one of a power generation amount prediction means that predicts the amount of power generated by the power generation facility and outputs the result of the prediction as a predicted power generation amount, and a battery control means that controls the storage battery, a power consumption prediction means that predicts the amount of power consumed by the building and outputs the result of the prediction as a predicted power consumption amount, and a power control means that controls the power generation facility, the amount of power consumed by the building, and / or the amount of charge / discharge of the storage battery based on the predicted power generation amount and / or the state of the storage battery, and the predicted power consumption amount.

[0007] Each of the information processing devices according to an aspect of the present invention is also an information processing method and a program according to an aspect of the present invention.

[0008] According to the present invention, it is possible to realize optimal control of the power consumption and power interchange amount of the entire building through not only prediction of the power demand for air conditioning equipment, lighting equipment, etc., but also prediction of the amount of power generated by renewable energy, optimal control of storage batteries, optimal control of EV charging equipment, etc.

[0009] 5 is a diagram showing an overview of the present service that can be realized by an information processing system to which a server according to an embodiment of the information processing device of the present invention is applied. FIG. 6 is a diagram showing an example of the detailed configuration of the building of FIG. 1. FIG. 7 is a diagram showing an example of the configuration of an information processing system to which a server according to an embodiment of the information processing device of the present invention is applied. FIG. 8 is a block diagram showing an example of the hardware configuration of a server in the information processing system of FIG. 2. FIG. 9 is a functional block diagram showing an example of the functional configuration of a server of the hardware configuration of FIG. 4 that constitutes the information processing system of FIG. 2. FIG. 10 is a flowchart showing the operation of the servers of FIGS. 4 and 5.

[0010] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0011] First, an overview of a service (hereinafter referred to as "this service") that can be realized by an information processing system (see FIG. 3 described later) to which a server (see FIG. 4 and FIG. 5 described later) according to an embodiment of the information processing device of the present invention is applied will be described with reference to FIG. 1 and FIG. 2. FIG. 1 is a diagram showing an overview of this service that can be realized by an information processing system to which a server according to an embodiment of the information processing device of the present invention is applied. FIG. 2 is a diagram showing an example of the detailed configuration of the building of FIG. 1.

[0012] This service not only predicts the electricity demand for air conditioning equipment, lighting equipment, etc., but also provides optimal control of the electricity consumption and power interchange amount for buildings T1 to Tn as a whole through predicting the amount of electricity generated by renewable energy, optimal control of storage batteries, and optimal control of EV charging equipment.

[0013] Specifically, for example, in Figure 1, an integrated management system (IMS) is connected to a retail electricity supplier (KDC), a power trading market (DTM), and a power generation company (HC). The integrated management system (IMS) is also connected to multiple management systems (MS1, MS2, ... MSn). The management system (MS1) is connected to building T1, the management system (MS2) is connected to building T2, and the management system (MSn) is connected to building Tn, and they manage each building.

[0014] As shown in Fig. 2, each of buildings T1 to Tn is equipped with a solar power generation facility SGS, a solar carport power generation facility SCGS, a power storage device TS, and multiple EV charging facilities EVCS1, EVCS2, ... EVCSn, etc. Also installed within the building in which the solar power generation facility SGS is installed are air conditioning facilities KT1, KT2, ... KTn, lighting facilities SS1, SS2, ... SSn, mechanical devices KS1, KS2, ... KSn, other facilities OS1, OS2, ... OSn, sensors S1, S2, ... Sn, etc. Under and / or near the solar carport power generation facility SCGS, a space is provided in which multiple EVs EV1, EV2, ... EVn can be parked.

[0015] In this way, the power generation amount of the power generation equipment (solar power generation equipment SGS, solar carport power generation equipment SCGS) that supplies power to each of the buildings T1 to Tn is predicted, and the prediction result is output as predicted power generation amount. The power consumption of the buildings T1 to Tn is predicted, and the prediction result is output as predicted power consumption amount. Based on the predicted power generation amount and predicted power consumption amount, the total amount of power supplied to the buildings T1 to Tn from the power generation equipment and the power storage device TS (storage battery), the power consumption of the building Tn, and at least one of the power consumption of the buildings T1 to Tn and the charge / discharge amount of the storage battery can be controlled, including the purchase and sale of electricity from the power grid depending on the supply and demand surplus / deficiency. Note that the above configuration is merely an example, and there are multiple combinations of patterns, such as when the building does not have a solar power generation equipment SGS, does not have a solar carport power generation equipment SCGS, does not have a power storage device TS, or does not have an EV charging equipment EVCS, and naturally, it also includes cases where at least one of the power consumption amount of the building and the charge / discharge amount of the storage battery can be controlled in each of these various patterns.

[0016] In this service, although not shown in Figures 1 and 2, when the predicted power generation amount is greater than the predicted power consumption amount, the power control means can control the amount of surplus power generated by the power generation facility that exceeds the building's power consumption to be charged to the power storage device TS (storage battery). That is, the server 1 can control the amount of surplus power generated by the power generation facility that exceeds the building's power consumption to be charged to the storage battery. This makes it possible to maximize the use of generated renewable energy and use the stored electricity as nighttime power, thereby reducing the electricity bill for that day. Alternatively, the surplus power may be sold to the power trading market, a retail electricity supplier, or the like through the power grid without being charged to the storage battery.

[0017] Although not shown in FIG. 1 , this service may include a charging start detection unit (e.g., one or both of the EV charging facility information acquisition unit 65 and the EV charging facility status prediction unit 75 in FIG. 5 ) that detects the timing to start charging EVs EV1, EV2, ..., EVn (electric vehicles). That is, the server 1 can detect the timing to start charging EVs EV1, EV2, ..., EVn (electric vehicles). This allows the server 1 to use a sensor to detect the entry of multiple EVs EV1, EV2, ..., EVn into the charging facility's usage area. If each vehicle starts operating its quick charger at the same time, a temporary surge in power demand may occur, potentially exceeding the expected design capacity of the substation or increasing the contracted capacity under the power contract. In this situation, the service can effectively utilize pre-charged storage batteries to prevent the design capacity of the substation or the peak demand value of the entire facility from being exceeded.

[0018] Although not shown in FIG. 1 , this service may also include an adjustment request receiving means (e.g., the DR receiving unit 56 in FIG. 5 ) that receives an adjustment request from the outside requesting a reduction or increase in the amount of power consumption of the building Tn. That is, the server 1 can acquire an adjustment request from the outside requesting a reduction or increase in the amount of power consumption of the building Tn. This allows the service to receive incentives from the power company when the power company issues a demand response (DR) request within the service area in a situation where a large earthquake has recently occurred and simultaneous inspections of thermal power plants and nuclear power plants within the service area are expected, and also allows the service to contribute to avoiding power outages due to tight power supply and demand within the service area.

[0019] Although not shown in Fig. 1, this service may store in a storage device a reduction ranking set for each power load in a building, the past actual power consumption for each power load, and a power consumption plan for each power load. That is, the server 1 can store a reduction ranking set for each power load in buildings T1 to Tn, the past actual power consumption for each power load, and the power consumption plan for each power load. This makes it possible to control the power consumption of a building based on at least one of the reduction ranking, the actual power consumption, and the power consumption plan, thereby reducing surplus power and contributing to avoiding power outages due to tight power supply and demand in the area.

[0020] Next, the configuration of an information processing system that realizes the provision of this service will be described with reference to Fig. 3. Fig. 3 is a diagram showing an example of the configuration of an information processing system to which a server according to an embodiment of the information processing device of the present invention is applied.

[0021] 3 is configured to include a server 1, an electricity market server 2a, an electric power company server 3a, a user terminal 4a, and a building facility 6a. The server 1, the electricity market server 2a, the electric power company server 3a, the user terminal 4a, and the building facility 6a are connected to each other via a network NW such as the Internet.

[0022] The server 1 is an information processing device managed by the service provider of this service (FIG. 1). The server 1 executes various processes for realizing this service while appropriately communicating with the electricity market server 2a, the electric power company server 3a, the user terminal 4a, and the building facilities 6a.

[0023] The electricity market server 2a is an information processing device managed by the operator of the electricity trading market (DTM) shown in Fig. 1, and provides price information and trading information for the electricity trading market. By communicating with the electricity market server 2a, the server 1 can obtain information for predicting market prices and determining the optimal timing for buying and selling electricity.

[0024] The electric power company server 3a is an information processing device managed by the electric power retailer (KDC) or the electric power generation company (HC) shown in Fig. 1, and provides information on the electric power supply situation and the adjustment of electric power supply and demand. In particular, it is used to transmit requests for adjusting the balance of electric power supply and demand, such as requests for demand response (DR), as well as the amount of electric power generated.

[0025] The user terminal 4a is an information processing device operated by a building manager or facility manager who uses and manages the system, and is composed of a smartphone, tablet, personal computer, centralized facility status monitoring device, etc. Through the user terminal 4a, the manager can monitor the status of the energy management system and change settings or perform operations as necessary. The building facility 6a includes the power storage device TS and solar power generation facility SGS shown in FIG. 2 and is controlled by the server 1. Note that the building facility 6a may include all or any of the solar power generation facility SGS, solar carport power generation facility SCGS, power storage device TS, etc.

[0026] FIG. 4 is a block diagram showing an example of a hardware configuration of a server in the information processing system shown in FIG.

[0027] The server 1 includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, a bus 14, an input / output interface 15, an input unit 16, an output unit 17, a memory unit 18, a communication unit 19, and a drive 20.

[0028] The CPU 11 executes various processes according to programs recorded in the ROM 12 or programs loaded from the storage unit 18 into the RAM 13. The RAM 13 also stores data and the like necessary for the CPU 11 to execute various processes.

[0029] The CPU 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output interface 15 is also connected to this bus 14. An input unit 16, an output unit 17, a storage unit 18, a communication unit 19, and a drive 20 are connected to the input / output interface 15.

[0030] The input unit 16 is configured with, for example, a keyboard and is used to input various types of information. The output unit 17 is configured with, for example, a display such as an LCD, a speaker and the like and outputs various types of information as images and sounds. The storage unit 18 is configured with, for example, a DRAM (Dynamic Random Access Memory) and is used to store various types of data. The communication unit 19 communicates with other devices (for example, the electricity market server 2a, the electric power company server 3a, the user terminal 4a, and the building facilities 6a in FIG. 3 ) via a network NW including the Internet.

[0031] Removable media 30, such as a magnetic disk, optical disk, magneto-optical disk, or semiconductor memory, is appropriately attached to the drive 20. Programs read from the removable media 30 by the drive 20 are installed in the storage unit 18 as needed. The removable media 30 can also store various data stored in the storage unit 18 in the same way as the storage unit 18.

[0032] Although not shown, the electricity market server 2a, the electric power company server 3a, and the user terminal 4a in Fig. 3 can also have basically the same hardware configuration as that shown in Fig. 4. Therefore, a description of the hardware configuration of the electricity market server 2a, the electric power company server 3a, and the user terminal 4a will be omitted.

[0033] The various hardware and software components constituting the information processing system of FIG. 3, including the server 1 of FIG. 4, work together to execute various processes for providing the present service of FIG.

[0034] FIG. 5 is a functional block diagram showing an example of the functional configuration of a server having the hardware configuration of FIG. 4 in the information processing system of FIG.

[0035] 5 , the server 1 includes a communication unit 19, a CPU 11, and a storage unit 18. When executing processing, the CPU 11 functions as an information acquisition unit 51, a prediction unit 52, an optimal solution determination unit 53, a power control unit 54, a setting unit 55, a DR acceptance unit 56, and a storage control unit 57. The information acquisition unit 51 includes a power generation information acquisition unit 61, a demand information acquisition unit 62, a power price information acquisition unit 63, a storage battery information acquisition unit 64, an EV charging equipment information acquisition unit 65, an other equipment information acquisition unit 66, and a sensor information acquisition unit 67. The prediction unit 52 includes a power generation prediction unit 71, a demand prediction unit 72, a power price prediction unit 73, a storage battery state prediction unit 74, an EV charging equipment state prediction unit 75, an other equipment state prediction unit 76, and a sensor state prediction unit 77. The power control unit 54 includes a power generation control unit 81 , a demand control unit 82 , a power buying and selling control unit 83 , a storage battery control unit 84 , and an other equipment control unit 85 .

[0036] Among these, the power generation prediction unit 71 functions as a power generation amount prediction means, the demand prediction unit 72 functions as a power consumption amount prediction means, the optimal solution determination unit 53 functions as a means for determining an optimal solution based on the power supply and demand gap and the cost required for power interchange, etc., the power control unit 54 functions as a power control means, the storage battery control unit 84 functions as a storage battery control means, either or both of the EV charging equipment information acquisition unit 65 and the EV charging equipment status prediction unit 75 function as a charging start detection means, and the power price prediction unit 73 functions as a price prediction means.

[0037] In addition, one area of ​​the memory unit 18 of the server 1 is provided with databases such as a power generation information DB91, a demand information DB92, an electricity price and trading information DB93, a battery operation information DB94, an EV charging equipment operation information DB95, other equipment information DB96, a sensor information DB97, a user information DB98, and an equipment information DB99.

[0038] The information acquisition unit 51 acquires various information such as power generation information, demand information, electricity price information, storage battery information, EV charging facility information, other facility information, sensor information, etc., and stores the information in corresponding databases (DBs 91 to 99). The information stored in the databases (DBs 91 to 99) is read out by the following units as needed.

[0039] Specifically, the information acquisition unit 51 acquires information such as actual information on the amount of power generated by renewable energy (per power plant, per area), actual information on power demand (per facility, per base, per area), actual information on power market prices (spot market price, hourly market price, imbalance price, etc.), information on power contracts with retail electricity suppliers (contract terms such as contract unit price and contract capacity), status and operation plan information for storage batteries (per storage battery), status and operation plan information for EV charging devices (per charging device, per charging station), status and operation plan information for machinery, air conditioning equipment, lighting equipment, etc. of factories / buildings / commercial facilities, environmental information (temperature, humidity) within factories / buildings / commercial facilities, initial setting information (drawings, equipment layout, etc.), target information (ideal setting values: set temperature, set humidity, etc.), etc., as well as information on the above operating status, failure status, maintenance plans, etc.

[0040] The power generation information acquisition unit 61 of the information acquisition unit 51 acquires, as power generation information, actual information on the amount of power generated by renewable energy (per power plant, per area). The granularity of the acquired information may vary depending on the granularity of the required information, such as in units of one second, one minute, one half hour, or one hour. The frequency of the acquired information may also vary depending on the frequency of the required information, such as virtually in real time, such as every few seconds, or every few minutes, 30 minutes, one hour, several hours, or even days. The information may also include information such as the operating status of the power generation equipment (number of years since operation began, power generation efficiency, degree of deterioration, presence or absence of breakdowns), a maintenance plan, etc.

[0041] The demand information acquisition unit 62 acquires actual power demand information (by facility, by base, or by area). The granularity of the acquired information may vary depending on the granularity of the required information, such as every second, every minute, every 30 minutes, or every hour. The frequency of the acquired information may also vary depending on the frequency of the required information, such as every few seconds in practical real time, or every minute, every 30 minutes, every hour, every few hours, or every day.

[0042] The power price information acquisition unit 63 acquires power price information from an external source. Specifically, it acquires actual information on the prices of power traded in the power trading market (spot market price, hourly market price, imbalance price, etc.). The acquired power price information may also include information such as the contract terms and supply unit price of the power supply contract with the retail electricity supplier with which the relevant building has a power receiving contract.

[0043] The battery information acquisition unit 64 acquires status and operation plan information (for each battery) indicating the charge / discharge status of the power storage device TS (battery). The status includes at least one of the following information: the battery's state of charge (SOC), state of health (SOH), battery temperature, current, voltage, resistance, etc. The granularity of the acquired information may vary depending on the granularity of the required information, such as every second, every minute, every 30 minutes, or every hour. The frequency of the acquired information may also vary depending on the frequency of the required information, such as every few seconds in practical real time, or every minute, every 30 minutes, every hour, every few hours, or every day.

[0044] The EV charging facility information acquisition unit 65 acquires the status of the EV charging device and operation plan information (for each charging device and each charging station). The EV charging facility information acquisition unit 65 also detects the timing to start charging an EV vehicle. The EV charging facility information acquisition unit 65 sends the detected charging start signal to the power control unit 54. The granularity of the acquired information may vary depending on the granularity of the required information, such as every second, every minute, every 30 minutes, or every hour. The frequency of the acquired information may also vary depending on the frequency of the required information, such as every few seconds in practical real time, or every minute, every 30 minutes, every hour, every few hours, or every day.

[0045] The other equipment information acquisition unit 66 acquires status and operation plan information for machinery, air conditioning equipment, lighting equipment, etc. of a factory / building / commercial facility, initial setting information (drawings, equipment layout, etc.), and target information (ideal setting values: set temperature, set humidity, etc.). The granularity of the acquired information may vary depending on the granularity of the required information, such as in units of one second, one minute, one half hour, or one hour. The frequency of the acquired information may also vary depending on the frequency of the required information, such as virtually in real time, such as every few seconds, or in units of one minute, one half hour, one hour, several hours, or one day.

[0046] The sensor information acquisition unit 67 acquires environmental information (temperature, humidity), the presence or absence of people, etc. from various sensors installed in a factory / building / commercial facility. The granularity of the acquired information may vary depending on the granularity of the required information, such as in units of one second, one minute, one half hour, or one hour. The frequency of the acquired information may also vary depending on the frequency of the required information, such as virtually in real time, such as every few seconds, or in units of one minute, one half hour, one hour, several hours, or one day.

[0047] The prediction unit 52 predicts the amount of power generated by power generation facilities such as renewable energy sources, predicts power demand, predicts the power price (power market price) in the power trading market, etc. For example, the prediction unit 52 predicts future power market prices based on past performance information and outputs the predicted prices to the optimal solution determination unit 53. The prediction unit 52 also predicts the degree of surplus or shortage of future power generation and demand, and outputs the predicted prices to the optimal solution determination unit 53 as weather forecast information.

[0048] Specifically, the power generation prediction unit 71 of the prediction unit 52 uses information on weather forecasts and power generation capacities to predict the amount of power generated by the solar power generation facilities SGS and solar carport power generation facilities SCGS that supply power to each of the buildings T1 to Tn, and outputs the prediction result as a predicted power generation amount. The power generation prediction unit 71 sends the predicted power generation amount to the optimal solution determination unit 53.

[0049] The demand forecasting unit 72 uses information on the actual power consumption and the power consumption plan to forecast the power consumption of the building and outputs the forecast result as the forecast power consumption. The demand forecasting unit 72 sends the forecast power consumption to the optimal solution determining unit 53.

[0050] The power price prediction unit 73 predicts the power market price and sends the predicted market price to the power control unit 54.

[0051] The battery state prediction unit 74 predicts the charge / discharge status of the power storage device TS (storage battery). The battery state prediction unit 74 sends the predicted charge / discharge status of the power storage device TS to the power control unit 54. Specifically, the battery state prediction unit 74 predicts a future increase or decrease in the charge amount of the power storage device TS based on the history of the daily charge / discharge status of the power storage device TS, the state of charge (SOC), the state of health (SOH), the battery temperature, the weather, and other conditions.

[0052] The EV charging equipment state prediction unit 75 predicts the state of each of the EV charging equipment EVCS1 to EVCSn that charges the EV vehicles EV1 to EVn, respectively. The EV charging equipment state prediction unit 75 sends the predicted state (predicted operating status) of each of the EV charging equipment EVCS1 to EVCSn to the power control unit 54. Specifically, based on the daily history of the charging status of each of the EV vehicles EV1 to EVn and weather conditions, the EV charging equipment state prediction unit 75 predicts a future increase or decrease in the amount of charge to be provided to the EV vehicles EV1 to EVn. The EV charging equipment state prediction unit 75 sends the predicted state of each of the EV charging equipment EVCS1 to EVCSn to the optimal solution determination unit 53.

[0053] The other equipment status prediction unit 76 predicts the status and target information (ideal setting values: set temperature, set humidity, etc.) of machinery, air conditioning equipment, lighting equipment, etc. in a factory / building / commercial facility. The other equipment status prediction unit 76 sends the predicted status and target information to the optimal solution determination unit 53.

[0054] The sensor state prediction unit 77 predicts future (predetermined time period) environmental information (temperature, humidity), the presence or absence of people, etc. from environmental information (temperature, humidity) and the presence or absence of people obtained from various sensors installed in the factory / building / commercial facility. The sensor state prediction unit 77 sends the predicted environmental information (temperature, humidity), the presence or absence of people, etc. to the optimal solution determination unit 53.

[0055] The optimal solution determination unit 53 calculates the difference between the total amount of power supplied to the building from the power generation equipment and the storage battery and the total amount of power consumed by the building and the total amount of power charged to the storage battery based on the predicted power generation amount from the power generation prediction unit 71 and the predicted power consumption amount from the demand prediction unit 72. The optimal solution determination unit 53 then calculates the balance of power supply and demand by combining this with the amount of power procured from the grid, and derives an optimal power interchange and power control method (control program). In this case, the optimal solution determination unit 53 determines the optimal solution using an evaluation function that takes into account not only the balance of power supply and demand, but also multiple indicators including at least one of power cost, environmental contribution, and equipment life. This enables optimal energy management from multiple perspectives, such as economic efficiency, environmental friendliness, and long equipment life. The optimal solution determination unit 53 sends the derived control method to the power control unit 54. The control method is retrieved from a group of control methods (control programs) pre-stored in the storage unit 18, based on the determination result. Other derivation methods are also possible. The control method may be a control program or parameters, etc.

[0056] The power control unit 54 controls the suppression of power consumption by the power load of the building, adjusts the output of generated power, and controls the charging and discharging of the power storage device TS, based on the control method from the optimal solution determination unit 53. In other words, the power control unit 54 controls the generation of power, the consumption of power, the charging of power, the discharging of power, etc.

[0057] Specifically, the power generation control unit 81 of the power control unit 54 controls the amount of power generated by the power generation facilities (the solar power generation facility SGS and the solar carport power generation facility SCGS) and the destination of the power supply. For example, in a situation where reverse power flow is likely to occur, the power generation control unit 81 controls the power generation facilities so that part of the generated power is charged to the storage battery, and also adjusts the output on the power generation side so that reverse power flow does not occur.

[0058] The demand control unit 82 controls the targets of power demand within buildings T1 to Tn. For example, to suppress power demand during peak hours, the demand control unit 82 temporarily reduces the power supply to non-critical loads and shifts the start times of equipment operation. When suppressing power consumption in buildings T1 to Tn, the demand control unit 82 also classifies the multiple power loads within the buildings into essential loads and non-essential loads, and controls the suppression of power supply to non-essential loads first. This step-by-step power suppression control based on the importance of the loads makes it possible to achieve efficient power reduction while maintaining the basic functions of buildings T1 to Tn.

[0059] The power trading control unit 83 controls the buying and selling of power with the power market. For example, it controls the selling of part of the power generated by the power generation facility (the solar power generation facility SGS or the solar carport power generation facility SCGS) to the market or a retail electricity supplier, the discharging of power from the storage battery and selling it during times when the market price is high, and the purchasing of power and charging the storage battery during times when the market price is low.

[0060] The battery control unit 84 monitors the charge / discharge state of the battery, and performs control to adjust the charge / discharge amount of the battery based on the predicted power generation amount and predicted power consumption amount, etc.

[0061] The other equipment control unit 85 controls other power equipment, such as controlling the illuminance of lighting equipment and controlling the temperature setting of air conditioning equipment.

[0062] The setting unit 55 manages the setting parameters for the entire system, such as weighting each index in optimization for power supply and demand balance control, and setting the priority of load reduction.

[0063] The DR reception unit 56 receives an external request for adjusting the amount of power consumption of each of the buildings T1 to Tn. The DR reception unit 56 sends the received adjustment request to the power control unit 54. Based on the adjustment request received by the DR reception unit 56, the power control unit 54 increases or decreases the amount of power consumption of each of the buildings T1 to Tn, or increases or decreases the total amount of power supplied from the power generation equipment to each of the buildings T1 to Tn and / or charged / discharged to the storage batteries so as to increase or decrease the amount of power procured from the grid.

[0064] The memory control unit 57 stores the reduction ranking set for each power load in each of the buildings T1 to Tn, the past actual power consumption for each power load, and the power consumption plan for each power load in the memory unit 18. The power control unit 54 controls the power consumption of each of the buildings T1 to Tn based on at least one of the reduction ranking, the actual power consumption, and the power consumption plan.

[0065] Next, the processing operation of the server of the embodiment will be described with reference to the flowchart of Fig. 6. Fig. 6 is a flowchart showing the operation of the server of Figs.

[0066] First, in step S11, the information acquisition unit 51 acquires various information such as power generation information, demand information, electricity price information, storage battery information, EV charging facility information, other facility information, and sensor information.

[0067] Next, in step S12, the power generation prediction unit 71 predicts the amount of power generated by the power generation facility and outputs the result of the prediction as the predicted amount of power generation.

[0068] Next, in step S13, the demand forecasting unit 72 forecasts the amount of power consumption of the building and outputs the result of the forecast as the amount of forecasted power consumption.

[0069] Next, in step S14, the optimal solution determination unit 53 calculates the power supply-demand gap for each specific time period based on the predicted power generation amount and the predicted power consumption amount. In detail, the optimal solution determination unit 53 controls at least one of the power consumption amount of the building and the charge / discharge amount of the storage battery so that the difference between the total power supply amount to the building from the power generation equipment and the storage battery and the power consumption amount of the building falls within a predetermined range.

[0070] Next, in step S15, the optimum solution determination unit 53 calculates the amount of power to be procured from the power grid that is required to fill the power supply-demand gap calculated in step S14.

[0071] Next, in step S16, if the optimal solution determination unit 53 can acquire all or any of the information on the sensor state prediction results by the sensor state prediction unit 77, such as the predicted operation status of the EV charging equipment by the EV charging equipment state prediction unit 75, the predicted operation status of other equipment by the other equipment state prediction unit 76, etc., the optimal solution determination unit 53 recalculates and corrects, based on the information, the power supply and demand gap calculated in step S14 and the amount of power to be procured from the power grid that is calculated in step S15 to fill the supply and demand gap.

[0072] Next, in step S17, the power price prediction unit 73 predicts the power price and outputs the prediction result as a predicted market price.

[0073] Next, in step S18, the battery state predicting unit 74 predicts and outputs the battery state based on the latest information about the battery.

[0074] Next, in step S19, the optimal solution determination unit 53 determines the amount of power to be exchanged so as to minimize the overall power procurement price, for example, based on the predicted market price and the information on the power contract concluded with the electricity retailer. However, the determination of the amount of power to be exchanged may be based on or include a viewpoint other than cost.

[0075] Next, in step S20, the power control unit 54 controls at least one of the amount of power generation, the amount of power consumption, and the amount of charge / discharge of the storage battery based on the determined power interchange fee. In other words, at least one of the amount of power generation, the amount of power consumption of the building, and the amount of charge / discharge of the storage battery is controlled so that the total amount of power supplied to the building from the power generation equipment and the storage battery is balanced with the amount of power consumed by the building and the amount of power charged to the storage battery. Note that some buildings have both power generation equipment and storage batteries, while others have only one of these, or neither. In such cases, the amount of power interchange for that part may be considered to be zero, and the amount of power interchange for the other parts may be determined and controlled.

[0076] In this way, according to the operation of the server 1 of the embodiment, the amount of power generated by the power generation equipment supplying power to the buildings T1 to Tn is predicted, and the amount of power consumed by the buildings T1 to Tn is predicted. Based on the predicted amount of power generated and the predicted amount of power consumed, at least one of the amount of power generated, the amount of power consumed, and the amount of charge / discharge of the storage batteries of the buildings T1 to Tn can be controlled so that the total amount of power supplied to the buildings from the power generation equipment and the storage batteries is balanced with the amount of power consumed by the buildings T1 to Tn and the amount of power charged to the storage batteries.

[0077] Next, specific examples of the present invention will be described. [Example 1: Control of equipment operation (factory)] An example of energy management control in a factory at around 8:00 in the morning on a certain weekday will be described.

[0078] Since 8:00 is the start time for work at the factory, from around 8:00 onwards, the operation of machinery, air conditioning equipment, lighting equipment and the like within the factory increases, resulting in a significant increase in electricity demand.

[0079] Meanwhile, the solar power plant installed on the factory roof begins generating electricity at around 6:30 a.m. when the sun rises.

[0080] The power demand and power generation for the day were predicted based on power demand forecasts based on past power demand records for each device and weather information, and power generation forecasts based on past power generation records for each power generation facility and weather information. As a result, it was found that there was a high possibility that power demand would exceed power generation from renewable energy sources between 7:00 and 8:00.

[0081] If this continues, the renewable energy that has been generated will be cut off by a reverse power flow prevention device (RPR), which will put into effect a control system that will temporarily suspend power generation.

[0082] Therefore, some of the equipment that was previously scheduled to start operating from around 8:00 was started to operate in advance from around 7:00.

[0083] As a result, the amount of electricity demand between 7:00 and 8:00 and the amount of renewable energy generated became roughly the same, making it possible to make maximum use of the generated renewable energy.In addition, by operating various facilities all at once at 8:00, the expected peak value of electricity demand could be kept low, and electricity consumption for the day was also reduced.

[0084] Example 2: Control by adjusting power storage device (building) An example of energy management control in an office building during the daytime hours of 12:00 to 13:00 on a certain weekday will be described.

[0085] During the lunch break, the lights are turned off and all equipment is shut down, but this is also the time when the solar panels on the roof generate the most electricity.

[0086] The system predicts power demand based on past power demand data for each device and weather information, and power generation data based on past power generation data for each power generation facility and weather information, and predicts power demand and power generation for the relevant time period.

[0087] As a result, it was found that electricity demand is suppressed during that time period, and that there may be a moment when demand < power generation occurs.

[0088] If this continues, the renewable energy that has been generated will be cut off by a reverse power flow prevention device (RPR), which will put into effect a control system that will temporarily suspend power generation.

[0089] To avoid this, some of the electricity generated during that time period is charged into a storage battery, creating demand for electricity. This makes it possible to equalize the amount of electricity demand with the amount of renewable energy generated, making it possible to make maximum use of the generated renewable energy, and also allowing the stored electricity to be used as nighttime power, thereby reducing the electricity bill for that day.

[0090] Example 3: Control according to use of EV charging device (commercial facility) An example of energy management control in a commercial facility building at around 2:30 pm on a certain holiday will be described.

[0091] In response to the recent spread of EVs, the commercial facility has installed multiple EV quick chargers in its parking lot.

[0092] At around 2:30 p.m., a sensor detected several electric vehicles entering the area where the charging equipment was being used.

[0093] If each vehicle were to continue operating its rapid charging device at the same time, it was detected that there could be a temporary surge in power demand for 15 minutes between 14:30 and 14:45, which could exceed the design capacity of the expected power receiving and transforming equipment, or could increase the peak demand value for the entire facility, which could have a significant impact on electricity bills under the contract with the power company.

[0094] Therefore, we decided to make good use of pre-charged storage batteries and control the power so as not to exceed the design capacity of the substation equipment or increase the peak demand value for the entire facility.

[0095] In this case, in addition to controlling the charging and discharging of the storage battery, peak demand may be reduced by temporarily reducing the amount of power demand in other parts of the facility.

[0096] Example 4: Control in response to DR instructions from a power company (building) An example of energy management control in an office building from 1:00 pm to 2:00 pm on a certain weekday will be described.

[0097] A large earthquake had recently occurred on this day, and it was expected that all thermal and nuclear power plants in the area would undergo simultaneous inspections.

[0098] In addition, the weather was bad and there was no prospect of sufficient power generation from renewable energy sources, and as supply would not be able to keep up with demand in the area, a power supply and demand shortage warning was expected to be issued.

[0099] Based on this forecast, the electric power company decided to request demand response (DR) within the area.

[0100] In this building, power demand and power generation for a given time period were predicted based on power demand forecasts based on past power demand records for each device and weather information, and power generation forecasts based on past power generation records for each power generation facility and weather information. Based on these forecasts, the building was given control to temporarily reduce power demand, and power demand was supplemented using storage batteries to comply with DR.

[0101] To enable this control, the charging of the storage battery begins two days in advance, ensuring sufficient power supply during the relevant time period.

[0102] This control not only allows the company to receive incentives from the power company, but also contributes to avoiding power outages caused by tight power supply and demand in the area.

[0103] [Example 5: Optimization control over an entire area] Although the above examples 1 to 4 have been described with a single building, commercial facility, or factory in mind, the same concept can also be used for overall optimization across multiple locations or optimization control over an entire area.

[0104] That is, it is possible to control the multiple buildings T1, T2, ..., Tn so as to optimize the balance of power supply and demand for the entire multiple buildings based on the predicted power generation and predicted power consumption of each of them. In this case, it is also possible to control the supply of surplus power from one building to another building.

[0105] Although one embodiment of the present invention has been described above, the present invention is not limited to the above-described embodiment, and modifications, improvements, etc. within the scope of achieving the object of the present invention are considered to be included in the present invention.

[0106] Furthermore, the system configuration shown in FIG. 3 and the hardware configuration of the server 1 shown in FIG. 4 are merely examples for achieving the object of the present invention, and are not particularly limited.

[0107] Furthermore, the functional block diagram shown in Fig. 5 is merely an example and is not particularly limited. That is, it is sufficient if the information processing system in Fig. 3 is provided with a function that can execute the various processes described above as a whole, and the functional blocks and databases used to realize this function are not particularly limited to the example in Fig. 5.

[0108] Furthermore, the locations of the functional blocks and databases are not limited to those shown in Fig. 5 and may be arbitrary. For example, at least some of the functional blocks and databases arranged on the server 1 side may be provided on the electricity market server 2a side, the electric power company server 3a side, or another information processing device (not shown).

[0109] The above-described series of processes can be executed by hardware or software, and each functional block can be configured by hardware alone, software alone, or a combination of both.

[0110] When a series of processes is executed by software, the programs constituting the software are installed onto a computer or the like from a network or a recording medium. The computer may be a computer incorporated into dedicated hardware. The computer may also be a computer capable of executing various functions by installing various programs, such as a server, a general-purpose smartphone, or a personal computer.

[0111] The recording medium containing such a program may be composed not only of a removable medium (not shown) that is distributed separately from the device main body in order to provide the program to the user, but also of a recording medium that is provided to the user in a state that is pre-installed in the device main body.

[0112] In this specification, the steps describing the program to be recorded on the recording medium include not only processes that are performed in chronological order, but also processes that are not necessarily performed in chronological order but are performed in parallel or individually.

[0113] To summarize the above, an information processing device to which the present invention is applied is sufficient as long as it has the following configuration, and can take various forms. That is, an information processing device to which the present invention is applied (for example, the server 1 in FIGS. 3 to 5) is: (1) "An information processing device (for example, the server 1 in FIGS. 3 to 5) that includes at least one of a storage battery (for example, the power storage device TS in FIG. 2) and / or a power generation facility (for example, the solar power generation facility SGS or the solar carport power generation facility SCGS in FIG. 2), and optimally controls the amount of power interchange for a building (for example, each of the buildings T1 to Tn in FIG. 1) that uses power supplied from at least one of the storage battery and / or the power generation facility, and includes at least one of power generation amount prediction means (for example, the power generation prediction unit 71 in FIG. 5) that predicts the amount of power generated by the power generation facility and outputs the result of the prediction as a predicted power generation amount, and storage battery control means (for example, the storage battery control unit 84 in FIG. 5) that controls the storage battery (for example, the power storage device TS in FIG. 2), It is sufficient to provide a power consumption prediction means (for example, the demand prediction unit 72 in FIG. 5) that predicts the power consumption of the building (for example, each of the buildings T1 to Tn in FIG. 1) and outputs the result of the prediction as a predicted power consumption, and a power control means (for example, the power control unit 54 in FIG. 5) that controls the power generation facility, the power consumption of the building (for example, each of the buildings T1 to Tn in FIG. 1), and / or the charge / discharge amount of the storage battery based on the predicted power generation amount and / or the state of the storage battery, and the predicted power consumption.

[0114] In this way, it becomes possible to optimize the timing of power consumption / power generation for the entire building through not only prediction of power demand for air conditioning equipment, lighting equipment, etc., but also prediction of renewable energy power generation, optimal control of storage batteries, optimal control of EV charging equipment, etc. In other words, it goes beyond power demand control within the building and enables integrated monitoring, integrated control, and optimization of energy resources including those around the building (roof, parking lot), preventing a decline in power generation efficiency and productivity of power generation equipment, a loss of environmental value, etc.

[0115] (2) In the information processing device (for example, the server 1 in Figures 3 to 5), the power control means (for example, the power control unit 54 in Figure 5) can further control the storage battery to charge the surplus power of the power generation facility that exceeds the power consumption of the building when the predicted power generation amount is greater than the predicted power consumption amount.

[0116] By charging the storage battery with surplus power based on this prediction, it is possible to prevent power generation cutoff by the RPR (reverse power relay), achieving both efficient operation of the power generation facility and preventing reverse power flow to the grid. This makes it possible to make maximum use of the generated renewable energy and use the stored electricity as nighttime power, thereby reducing the electricity bill for that day.

[0117] (3) In the information processing device (e.g., the server 1 in Figures 3 to 5), the power control means (e.g., the power control unit 54 in Figure 5) can monitor the charge / discharge state of the storage battery (e.g., the storage device TS in Figure 2, etc.) and adjust the charge / discharge amount of the storage battery based on the predicted power generation amount and the predicted power consumption amount.

[0118] By monitoring the charge / discharge state, temperature, and other conditions of a storage battery (such as the storage device TS in Figure 2) in real time in this way, optimal charge / discharge control according to the state of the storage battery becomes possible, thereby achieving both an extension of the storage battery's lifespan and efficient power utilization.

[0119] (4) The information processing device (e.g., server 1 in FIGS. 3 to 5) may further include a charging start detection means (e.g., EV charging facility information acquisition unit 65 in FIG. 5) that detects the timing of starting charging of electric vehicles (e.g., EV vehicles EV1 to EVn in FIG. 2), and the power control means (e.g., power control unit 54 in FIG. 5) may control at least one of the amount of power consumed by the building and the amount of charge / discharge of the storage battery based on the timing of starting charging detected by the charging start detection means (e.g., EV charging facility information acquisition unit 65 in FIG. 5).

[0120] As a result, when a sensor detects that multiple electric vehicles (e.g., EVs EV1 to EVn in FIG. 2 ) have entered the service area of ​​a charging device (e.g., EV charging facilities EVCS1 to EVCSn in FIG. 2 ) and each vehicle starts operating its quick charger at the same time, power demand may suddenly increase, potentially exceeding the expected design capacity of the power receiving and transforming equipment. In this situation, by effectively utilizing a storage battery (e.g., power storage device TS in FIG. 2 ) that has been charged in advance, control can be performed so as not to exceed the design capacity of the power receiving and transforming equipment or to prevent an increase in the peak demand value of the entire facility. Specifically, by performing appropriate control in response to the sudden increase in power demand when the electric vehicles (e.g., EVs EV1 to EVn in FIG. 2 ) start charging, it is possible to prevent the design capacity of the power receiving and transforming equipment from being exceeded and the peak demand value of the entire facility from increasing, thereby preventing a significant impact on the building's electricity bill.

[0121] (5) The information processing device (e.g., server 1 in Figures 3 to 5) further includes an adjustment request receiving means (e.g., DR receiving unit 56 in Figure 5) that receives an adjustment request from the outside requesting a reduction or increase in the amount of power consumed by the building, and the power control means (e.g., power control unit 54 in Figure 5) can increase or decrease the total amount of power supplied from the power generation facility to the building and / or charged / discharged to the storage battery, based on the adjustment request received by the adjustment request receiving means (e.g., DR receiving unit 56 in Figure 5), so as to increase or decrease the amount of power consumed by the building or increase or decrease the amount of power procured from the grid.

[0122] As a result, in a situation where a major earthquake has recently occurred and it is expected that all thermal power plants and nuclear power plants in the area will be inspected at the same time, when the electric power company issues a request for demand response (DR) within the area, it becomes possible to receive incentives from the electric power company and contribute to avoiding power outages due to tight power supply and demand in the area. In other words, by responding quickly to a power adjustment request from the electric power company, it is possible to receive incentives and contribute to avoiding power outages due to tight power supply and demand in the area.

[0123] (6) The information processing device (e.g., server 1 in Figures 3 to 5) may further include a storage control means (e.g., storage control unit 57 in Figure 5) for storing in a storage device (e.g., storage unit 18 in Figure 5) a reduction ranking set for each power load in the building, the past actual power consumption for each power load, and a power consumption plan for each power load, and the power control means (e.g., power control unit 54 in Figure 5) may control the power consumption of the building based on at least one of the reduction ranking, the actual power consumption, and the power consumption plan.

[0124] This allows the building's power consumption to be controlled based on at least one of the reduction order, actual power consumption, and power consumption plan, reducing excess power procurement and contributing to avoiding power outages due to tight power supply and demand within the area. As a result, control based on the priority of each power load becomes possible, improving the energy efficiency of the entire building while maintaining the functionality of the most important power loads.

[0125] (7) In the information processing device (for example, server 1 in Figures 3 to 5), the power load is a floor or section of the building, and the memory control means (for example, memory control unit 57 in Figure 5) can store the set temperature of the floor or section as the reduction order in the memory device (for example, memory unit 18 in Figure 5).

[0126] By determining the priority of power reduction based on the set temperature for each floor or section in this way, efficient power control can be achieved that takes into account the comfort of building users.

[0127] (8) The information processing device (e.g., server 1 in Figures 3 to 5) further includes a price prediction means (e.g., the power price prediction unit 73 in Figure 5) that predicts the electricity market price, and the power control means (e.g., the power control unit 54 in Figure 5) can control the amount of charge to be pre-charged to the storage battery based on the predicted market price predicted by the price prediction means (e.g., the power price prediction unit 73 in Figure 5) when a time period is expected in which the predicted power generation amount is smaller than the predicted power consumption amount.

[0128] By controlling the amount of charge in the storage battery based on predicted electricity market prices in this way, it is possible to minimize electricity procurement costs while optimizing the balance of electricity supply and demand for the entire building.

[0129] (9) In the information processing device (for example, the server 1 in FIGS. 3 to 5), the power generation facility is a solar power generation facility (for example, the solar power generation facility SGS or the solar carport power generation facility SCGS in FIG. 2), and the power generation amount prediction means (for example, the power generation prediction unit 71 in FIG. 5) predicts the power generation amount based on at least weather forecast information and the power generation capacity of the solar power generation facility (for example, the solar power generation facility SGS in FIG. 2).

[0130] By predicting power generation taking into account weather forecast information and the characteristics of the power generation equipment in this way, highly accurate energy management that responds to the variability of solar power generation can be achieved.

[0131] (10) In the information processing device (e.g., server 1 in Figures 3 to 5), the power consumption prediction means (e.g., demand prediction unit 72 in Figure 5) can predict the power consumption based on at least one of the past actual power consumption for each power load and the power consumption plan for each power load.

[0132] By utilizing past performance data and planning information in this way, more accurate power consumption predictions become possible, contributing to the optimization of control.

[0133] (11) The information processing device (for example, the server 1 in FIGS. 3 to 5) may further include a power supply and demand gap determination means (for example, the optimal solution determination unit 53 in FIG. 5) that compares the power consumption of the power generation facility and the building with the charge / discharge amount of the storage battery, based on the predicted power generation amount and / or the state of the storage battery, and the predicted power consumption, and the power control means (for example, the power control unit 54 in FIG. 5) may perform control based on the determination result by the power supply and demand gap determination means (for example, the optimal solution determination unit 53 in FIG. 5).

[0134] By continuously determining the state of the balance between power supply and demand in this way, it becomes possible to control the system at the appropriate timing in response to fluctuations in power generation and power consumption, thereby improving power utilization efficiency.

[0135] (12) In the information processing device (e.g., server 1 in Figures 3 to 5), the power control means (e.g., power control unit 54 in Figure 5) can, when the predicted power generation amount is smaller than the predicted power consumption amount and the charge amount of the storage battery exceeds a predetermined threshold, perform discharge control from the storage battery to the power load of the building, and control at least one of the power consumption amount of the building and the charge / discharge amount of the storage battery so that the sum of the power generated from the power generation equipment and the discharged power from the storage battery is equivalent to the power consumption amount of the building.

[0136] By optimally allocating generated power in this way, it is possible to minimize wasted generated energy and, in some cases, prevent backflow to the grid, while maximizing the building's power demand with renewable energy.

[0137] (13) In the information processing device (e.g., server 1 in Figures 3 to 5), the power control means (e.g., power control unit 54 in Figure 5) can, when reducing the power consumption of the building, classify multiple power loads in the building into essential loads and non-essential loads, and control the reduction of power supply to the non-essential loads first.

[0138] By performing step-by-step power suppression control based on the importance of the load in this way, it is possible to achieve efficient power reduction while maintaining the basic functions of the building.

[0139] (14) In the information processing device (for example, the server 1 in Figures 3 to 5), the power supply and demand gap determination means (for example, the optimal solution determination unit 53 in Figure 5) can determine an optimal solution based on the predicted power generation amount and the predicted power consumption amount using an evaluation function that takes into account multiple indexes including at least one of power cost, environmental contribution, and equipment lifespan, and the power control means (for example, the power control unit 54 in Figure 5) can control at least one of the power generation amount, the power consumption amount of the building, and the charge / discharge amount of the storage battery based on the optimal solution determined by the power supply and demand gap determination means (for example, the optimal solution determination unit 53 in Figure 4).

[0140] By making a comprehensive judgment by taking into account multiple evaluation indicators in this way, it is possible to achieve optimal energy management from a multifaceted perspective, not just considering the balance of electricity supply and demand, but also considering economic efficiency, environmental friendliness, and the longevity of equipment.

[0141] DESCRIPTION OF SYMBOLS 1: Server, 2a: Electricity market server, 3a: Electric power company server, 4a: User terminal, 6a: Building equipment, 11: CPU, 12: ROM, 13: RAM, 14: Bus, 15: Input / output interface, 16: Input unit, 17: Output unit, 18: Storage unit, 19: Communication unit, 20: Drive, 30: Removable media, DTM: Electricity trading market, KDC: Retail electricity supplier, HC: Power generation company, TS: Power storage device, SGS: Solar power generation equipment, SCGS...solar carport power generation equipment, EVCS1 to EVCSn...EV charging equipment, EV1 to EVn...EV vehicles, IMS...integrated management system, MS1 to MSn...management system, KS1 to KSn...machinery equipment, KT1 to KTn...air conditioning equipment, SS1 to SSn...lighting equipment, OS1 to OSn...other equipment, S1 to Sn...sensors, T1 to Tn...buildings, NW...network, 51...information acquisition unit, 52 ...Prediction unit, 53...Optimal solution determination unit, 54...Power control unit, 55...Setting unit, 56...DR reception unit, 57...Memory control unit, 61...Power generation information acquisition unit, 62...Demand information acquisition unit, 63...Power price information acquisition unit, 64...Storage battery information acquisition unit, 65...EV charging equipment information acquisition unit, 66...Other equipment information acquisition unit, 67...Sensor information acquisition unit, 71...Power generation prediction unit, 72...Demand prediction unit, 73...Power price prediction unit, 74...Storage battery state prediction unit, 75...EV charging equipment Status prediction unit, 76...other equipment status prediction unit, 77...sensor status prediction unit, 81...power generation control unit, 82...demand control unit, 83...electricity buying and selling control unit, 84...storage battery control unit, 85...other equipment control unit, 91...power generation information DB, 92...demand information DB, 93...electricity price and transaction information DB, 94...storage battery operation information DB, 95...EV charging equipment operation information DB, 96...other equipment information DB, 97...sensor information DB, 98...user information DB, 99...equipment information DB

Claims

1. An information processing device that controls the amount of power of a building that is equipped with at least one of a storage battery and / or power generation equipment and that uses power supplied from at least one of the storage battery and / or power generation equipment, and that comprises at least one of a power generation amount prediction means that predicts the amount of power generated by the power generation equipment and outputs the result of the prediction as a predicted power generation amount, and a storage battery control means that controls the storage battery; a power consumption amount prediction means that predicts the amount of power consumed by the building and outputs the result of the prediction as a predicted power consumption amount; and a power control means that controls at least one of the amount of power generated, the amount of power consumed by the building, and the amount of charge and discharge of the storage battery based on the predicted power generation amount and / or the state of the storage battery, and the predicted power consumption amount.

2. The information processing device according to claim 1, wherein the power control means is capable of controlling the storage battery to charge the surplus power generated by the power generation equipment that exceeds the power consumption of the building when the predicted power generation amount is greater than the predicted power consumption amount.

3. The information processing device according to claim 1, wherein the power control means monitors the charge / discharge state of the storage battery and adjusts the charge / discharge amount of the storage battery based on the predicted power generation amount and the predicted power consumption amount.

4. The information processing device according to claim 1, further comprising a charging start detection means for detecting the timing of the start of charging of the electric vehicle, wherein the power control means controls at least one of the amount of power generated, the amount of power consumed by the building, and the amount of charge and discharge of the storage battery based on the timing of the start of charging detected by the charging start detection means.

5. An information processing device as described in claim 1, further comprising an adjustment request receiving means for receiving an adjustment request from outside requesting a reduction or increase in the amount of power consumed by the building, wherein the power control means increases or decreases the total amount of power supplied to the building from the power generation equipment and / or charged / discharged to the storage battery, so as to increase or decrease the amount of power consumed by the building or increase or decrease the amount of power procured from the grid, based on the adjustment request received by the adjustment request receiving means.

6. The information processing device according to claim 5, further comprising a storage control means for storing in a storage device a reduction ranking set for each power load in the building, the actual power consumption in the past for each power load, and a power consumption plan for each power load, wherein the power control means controls the power consumption of the building based on at least one of the reduction ranking, the actual power consumption, and the power consumption plan.

7. The information processing device according to claim 6, wherein the power load is a floor or section of the building, and the storage control means stores the set temperature of the floor or section in the storage device as the reduction order.

8. An information processing device as described in claim 1, further comprising a price prediction means for predicting an electricity market price, wherein the power control means controls the amount of charge to be pre-charged to the storage battery based on the predicted market price predicted by the price prediction means when a time period is expected in which the predicted power generation amount is smaller than the predicted power consumption amount.

9. The information processing device according to claim 1, wherein the power generation facility is a solar power generation facility, and the power generation amount prediction means predicts the amount of power generation based on at least weather forecast information and the power generation capacity of the solar power generation facility.

10. The information processing device according to claim 1, wherein the power consumption prediction means predicts the power consumption based on at least one of the past actual power consumption for each of the power loads and the power consumption plan for each of the power loads.

11. The information processing device according to claim 1, further comprising a means for determining a power supply and demand gap by comparing the power consumption of the power generation equipment and the building with the charge and discharge amount of the storage battery based on the predicted power generation amount and / or the state of the storage battery, and the predicted power consumption amount, wherein the power control means controls the total amount of power based on the determination result by the power supply and demand gap determination means.

12. The information processing device according to claim 1, wherein the power control means controls discharge from the storage battery to the building's power load when the predicted power generation amount is smaller than the predicted power consumption amount and the charge amount of the storage battery exceeds a predetermined threshold, and controls at least one of the power consumption amount of the building and the charge / discharge amount of the storage battery so that the sum of the power generated from the power generation equipment and the power discharged from the storage battery is equal to the power consumption amount of the building.

13. The information processing device according to claim 1, wherein, when reducing the power consumption of the building, the power control means classifies the multiple power loads within the building into essential loads and non-essential loads, and controls the reduction of power supply to the non-essential loads first.

14. The information processing device described in claim 11, wherein the power supply and demand gap determination means determines an optimal solution based on the predicted power generation amount and the predicted power consumption amount using an evaluation function that takes into account multiple indicators including at least one of power cost, environmental contribution, and equipment lifespan, and the power control means controls at least one of the power generation amount, the power consumption amount of the building, and the charging and discharging amount of the storage battery based on the optimal solution determined by the power supply and demand gap determination means.

15. An information processing method executed by an information processing device that controls the amount of power of a building that is equipped with at least one of a storage battery and / or power generation equipment and that uses power supplied from at least one of the storage battery and / or power generation equipment, the information processing method including: at least one of a power generation amount prediction step that predicts the amount of power generated by the power generation equipment and outputs the result of the prediction as a predicted power generation amount, and a battery control step that controls the storage battery; a power consumption amount prediction step that predicts the amount of power consumed by the building and outputs the result of the prediction as a predicted power consumption amount; and a power control step that controls at least one of the amount of power generation, the amount of power consumed by the building, and the amount of charge / discharge of the storage battery based on the predicted power generation amount and / or the state of the storage battery, and the predicted power consumption amount.

16. A program that causes a computer that controls the amount of electricity of a building that is equipped with at least one of a storage battery and / or power generation equipment and that uses electricity supplied from at least one of the storage battery and / or power generation equipment to execute control processing including at least one of a power generation amount prediction step that predicts the amount of electricity generated by the power generation equipment and outputs the result of the prediction as a predicted power generation amount, and a battery control step that controls the storage battery; a power consumption amount prediction step that predicts the amount of electricity consumed by the building and outputs the result of the prediction as a predicted power consumption amount; and a power control step that controls at least one of the amount of electricity generated, the amount of electricity consumed by the building, and the amount of charge / discharge of the storage battery based on the predicted amount of electricity generated and / or the state of the storage battery, and the predicted power consumption amount.

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