Information processing device, information processing method, information processing system, and computer program

Abstract

To calculate an adjustable power amount for users as a whole.SOLUTION: An information processing device comprises a processing unit that determines, on the basis of history of charging and discharging of an accumulator battery at one or more users in a first period, a battery level of the accumulator battery in a second period different from the first period, and calculates an adjustable power amount, which is a sum of chargeable amounts or dischargeable amounts of the accumulator battery of the one or more users in the second period, on the basis of an estimated value of the battery level of the accumulator battery.SELECTED DRAWING: Figure 9

Description

[Technical field]

[0001] An embodiment of the present invention relates to an information processing device, an information processing method, an information processing system, and a computer program. [Background technology]

[0002] In order to stabilize the power grid, it is necessary to adjust the supply and demand of electricity and achieve a balance between supply and demand. On the other hand, residential EVs (Electric Vehicles) and storage batteries have a large idle capacity (amount of charge stored in the storage battery without being used), and if a large number of them are collected together, they can become a resource of a certain scale. Therefore, it is conceivable to achieve a balance between supply and demand of electricity by collecting a large number of residential EVs and storage batteries to ensure power adjustment capacity and to keep the total demand of the consumer group within the upper and lower limits of the power adjustment capacity.

[0003] However, demand fluctuates greatly at residential consumers, making it difficult to adjust supply and demand. In addition, charge and discharge controls for residential EVs and storage batteries, such as economy-priority mode and water heater scheduling, are often set on the home side. Since the contents of the set controls are not known from the outside, it is not always possible for the home to respond to a charge and discharge request. In addition, there are times when the EV is not present at the home, so there is a high degree of uncertainty in the response to a charge and discharge request. In addition, the actual charge and discharge amount at a consumer is often determined not by the output characteristics of the storage battery, but by the contracted power (which is often smaller than the possible output of the storage battery) and reverse power flow constraints (for example, reverse power flow from the storage battery may be prohibited).

[0004] Due to the above uncertainties, it is difficult to calculate in advance the amount of power that can be adjusted by consumers (DR possible amount) when a DR (demand response) request, which is a request for supply and demand adjustment, is made. On the other hand, in the supply and demand adjustment market, it is necessary to determine the bidding amount at least one day in advance. Also, in economic DR, it is desirable to know the amount of power adjustment that can be made in advance. Therefore, there is a demand to calculate the amount of power adjustment that can be made with high accuracy in advance under uncertain conditions. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2022-139181 A [Patent Document 2] International Publication No. 2015 / 045337 Summary of the Invention [Problem to be solved by the invention]

[0006] The embodiments of the present invention provide an information processing device, an information processing method, an information processing system, and a computer program that enable calculation of an amount of power adjustment possible for all consumers. [Means for solving the problem]

[0007] The information processing device of this embodiment includes a processing unit that estimates the remaining capacity of a storage battery in a second period different from a first period based on a charging and discharging history of the storage battery of one or more consumers during the first period, and calculates a power adjustment possible amount, which is the total chargeable or dischargeable amount of the storage battery of the one or more consumers during the second period, based on the estimated remaining capacity of the storage battery. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram showing an outline of an overall system configuration according to an embodiment of the present invention. [Diagram 2] A diagram showing product classifications in the supply and demand adjustment market. [Diagram 3] A diagram detailing the requirements for tertiary control reserve[1] and tertiary control reserve[2]. [Figure 4] A diagram showing the flow of control instructions and the positioning of the RA (resource aggregator) in the VPP demonstration. [Diagram 5] A diagram showing the flow of calculating actual values ​​in a VPP demonstration. [Figure 6] A diagram explaining the pre-screening method for tertiary control capacity [2]. [Figure 7]A diagram explaining the pre-screening method for tertiary control capacity [2]. [Figure 8] A diagram to explain an example of a success judgment in tertiary control capacity [1]. [Figure 9] FIG. 1 is a block diagram showing the configuration of a DR possible amount estimation device and a consumer according to the present embodiment. [Figure 10] FIG. 10 is a block diagram showing a simplified configuration in which some elements are omitted from the configuration shown in FIG. 9. [Figure 11] 11A and 11B are diagrams showing examples of SoC time series estimates and unconnected time series estimates; [Figure 12] FIG. 13 is a diagram showing an example of a demand time series estimated value. [Figure 13] FIG. 13 is a diagram showing an example of DR content information in the case of a supply and demand adjustment market. [Figure 14] FIG. 13 is a diagram showing an example of DR content information in the case of economic DR. [Figure 15] FIG. 4 is a diagram showing an example of storage battery specification information. [Figure 16] 13A is a diagram showing an example of a calculation result of an available charge / discharge amount when the original battery control is not taken into account, and FIG. 13B is a diagram showing an example of a calculation result of an available charge / discharge amount when the battery control is taken into account. [Figure 17] FIG. 13 is a supplementary explanatory diagram for calculating the chargeable / dischargeable capacity when taking into account the original battery control. [Figure 18] FIG. 11 is a diagram showing an example of parameter information. [Figure 19] FIG. 13 is a diagram showing an example of a DR possible amount DB. [Figure 20] 11 is a flowchart of the process of the simplified configuration of FIG. 10 . [Figure 21] FIG. 13 is a diagram showing possible DR amount information in the case of an upward DR. [Figure 22] 1A shows an example of DR content information, (B) shows an example of coefficient values, and (C) shows an example of a calculation result of a possible DR amount. [Diagram 23] FIG. 13 is a diagram showing an example of calculation of a possible DR amount in the fourth embodiment. [Figure 24] FIG. 13 is a diagram showing an example of a flowchart when a risk of estimated deviation is taken into consideration. [Diagram 25] FIG. 13 is a diagram showing a specific example of the operation of the fifth embodiment. [Figure 26]4 shows an example of an output screen of a display unit. [Figure 27] FIG. 2 is a diagram showing a hardware configuration of a possible DR amount estimation device which is an information processing device according to the present embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, the present embodiment will be described with reference to the drawings.

[0010] FIG. 1 is a diagram showing an outline of the overall system configuration according to this embodiment.

[0011] This embodiment is broadly provided with consumers 10 that use power and have storage batteries 27, a power company 700 that supplies power to each of the consumers 10, a higher-level system 600 such as a DRAS (Demand Response Application Server) that issues a control command for power supply and demand (power reduction command in the illustrated example), and an aggregator 200 that mediates between the consumers 10. In the illustrated example, a "down DR" is assumed, which requests a reduction in the demand (power consumption) of all the consumers, and a reduction command is issued as a control command. In the case of an "up DR" which requests an increase in the demand (power consumption) of all the consumers, a power consumption command is issued. In the operation of the power system, the aggregator 200 mediates between the power company 700, such as a power supplier that generates or distributes power, and the consumers 10 that use power, aiming to reduce power. The aggregator 200 promises the power company 700 to reduce power, while creating a power reduction plan (for example, a charge / discharge plan for the storage battery 27) for the consumers 10 under its control, and requests the consumers 10 to charge or discharge according to the plan. This request is called a demand response (DR) request. With this, the aggregator 200 aims to achieve a power reduction target for all consumers. For this reason, the aggregator 200 includes a DR possible amount estimation device 100 that estimates the power adjustment possible amount (DR possible amount) of all consumers with high accuracy.

[0012] The consumer 10 is mainly assumed to be a house (low voltage consumer), but may also be a high voltage consumer or a special high voltage consumer such as an office building, a commercial building, a public facility, a factory, etc. The electric power company 700 and the upper system 600 may be integrated. The electric power company 700 may be a business that integrally manages the processes from power generation to distribution, or may be at least one of a power transmission and distribution business, a retail business, and a power generation business.

[0013] The aggregator 200 requests DR (requests charging or discharging) from the consumer 10 according to a reduction command from the upper system 600. The aggregator 200 uses the DR possible amount estimation device 100 according to this embodiment to create a charge and discharge plan (DR plan) for the storage battery 27 owned by the consumer 10 based on the reduction command from the upper system 600 and information (consumer information) of the consumer 10. The aggregator 200 issues a DR request (request for charging or discharging), which is a control command for the storage battery 27, to the consumer 10 under its control based on the DR plan. In this way, the aggregator 200 achieves the power reduction target of the consumers as a whole. The storage battery 27 of the consumer 10 controls charging and discharging according to the charge or discharge request from the aggregator 200. The discharged power may be used within the consumer's home, or may be supplied to a buyer when the power is sold in the wholesale power trading market.

[0014] The aggregator 200 may be included in at least one of the upper system 600 and the electric power company 700. Alternatively, the aggregator 200 may have a structure of two or more hierarchies, in which a parent aggregator issues commands to a child aggregator instead of the upper system 600, and the DR possible amount estimation device 100 of the child aggregator mediates between the parent aggregator and the consumer 10. The aggregator 200 may have a function of bidding in a supply and demand adjustment market system that processes a supply and demand adjustment market, which will be described later, or in an electric power trading market system that processes an electric power trading market (also called a wholesale electric power trading market).

[0015] Below, the outline of this embodiment will be explained assuming the supply and demand adjustment market system that started in fiscal year 2021.

[0016] Figure 2 shows the product classification of the supply and demand adjustment market. Figure 2 is based on materials excerpted from Document 2 of the 13th Supply and Demand Adjustment Market Study Subcommittee. In the supply and demand adjustment market that started in fiscal year 2021, five types of products are offered according to differences in response time, etc. The response time is the time from when a reduction command (also called a reduction request) is issued from the upper system 600 to when the reduction command is responded to. The five types of products include primary adjustment capacity, secondary adjustment capacity [1], secondary adjustment capacity [2], tertiary adjustment capacity [1], and tertiary adjustment capacity [2]. In the case of aggregation that bundles consumers (houses) via a network, a communication delay of at least about one minute is expected, so the two types of tertiary adjustment capacity [1] and tertiary adjustment capacity [2] are considered to be the main targets.

[0017] Figure 3 shows in detail the requirements for tertiary control reserve[1] and tertiary control reserve[2]. Figure 3 is based on materials excerpted from the FY2020 VPP Project Common Demonstration Specifications.

[0018] For example, the tertiary control capacity [2] has a response time of 45 minutes or less, as shown in Figure 3 or the above-mentioned Figure 2. The duration is 3 hours, which is the product block time, and the command interval (command value change interval) is 30 minutes.

[0019] Here, the product block time is From 0:00 to 3:00 From 3:00 to 6:00 6:00 to 9:00 9:00 to 12:00 From 12:00 to 15:00 From 15:00 to 18:00 From 18:00 to 21:00 From 9:00pm to midnight In either case, the duration is 3 hours. Since the command interval (command value change interval) is 30 minutes, for example, in the case of a product block time from 15:00 to 18:00, From 15:00 to 15:30 From 15:30 to 16:00 From 16:00 to 16:30 From 16:30 to 17:00 From 5:00pm to 5:30pm From 17:30 to 18:00 Command values ​​(reduction command values, etc.) are determined for each 30-minute slot.

[0020] Furthermore, since the response time is within 45 minutes, for example, the reduction command value for the period from 15:00 to 15:30 is determined by 14:15. If the aggregator does not receive a reduction command from the upper system 600 within 45 minutes, the command value is considered to be 0 (no reduction command).

[0021] Since the command value is determined according to the bid unit price or contract amount, it is highly likely that the reduction command value will be the maximum value, which is the "Δ kW contract amount" (described later). The bid unit price is determined in advance by any method.

[0022] Using Figures 4 and 5, we will explain a typical example of aggregation that is being carried out in VPP (Virtual Power Plant) demonstration experiments (https: / / sii.or.jp / vpp02 / ) and other such experiments.

[0023] FIG. 4 is a diagram showing the flow of control instructions and the positioning of the RA (resource aggregator) in the VPP demonstration. FIG. 5 is a diagram showing the flow of calculating performance values ​​in a VPP demonstration.

[0024] In FIG. 4, a DR command (power reduction command, etc.) which is a control command is notified from the highest DRAS 600 owned by the power company to the resource aggregator (RA) 162 via the higher-level aggregation coordinator (AC) 161, for example, 15 minutes before the start of DR. A set of AC 161 and RA 162 corresponds to the aggregator 200. The control command includes, for example, a command to reduce by 10 kW between 18:00 and 21:00. The RA 162 collects information such as the measured value of the power meter (also called a meter value) and the charge / discharge amount of the storage battery 27 from each consumer 10 at any time. When the RA 162 is notified of the DR command (control command), it estimates the demand of each consumer under its control based on the collected information, for example, 2 minutes before the start of DR, and performs DR optimization processing. In the DR optimization processing, the content of charging / discharging to be requested of each consumer is determined, and a DR command (discharge command or charge command) is generated. The RA 162 notifies each consumer of the calculated DR command as a control request, for example, one minute before the start of DR. The DR optimization process and the notification of the control request to each consumer are performed, for example, every five minutes. As shown in FIG. 5, the meter values ​​of the consumers 10 under the control of the RA 162 after the completion of DR implementation are acquired, and the DR performance (whether DR is successful or not) is determined based on the total value of the acquired meter values. Specifically, the DR performance is determined based on how close the total value is to the DR target value. Therefore, the RA 162 is required to appropriately control the meter values ​​of the power meters of the consumers under its control by making a DR request (request for charging / discharging) to each consumer so that the total of the meter values ​​of the power meters of each consumer is as close as possible to the target value.

[0025] Next, the FY2020 VPP Project Common Demonstration Specifications (https: / / sii.or.jp / vpp02 / uploads / R2VPP Based on this, we will discuss the currently assumed conditions for success in achieving tertiary control reserve.

[0026] As shown in Figure 3 above, the VPP Demonstration Project Specifications stipulate that the success criteria for each of tertiary control reserve [1] and tertiary control reserve [2] are that the actual demand volume must remain within ±10% of the bid volume (equivalent to the ΔkW contract volume in the supply and demand adjustment market). The evaluation unit is set at 1 minute for tertiary control reserve [1] and 30 minutes for tertiary control reserve [2].

[0027] On the other hand, the Subcommittee on Supply and Demand Adjustment Market has set a requirement in the pre-examination of tertiary adjustment capacity [2] that the amount of power reduction (power adjustment amount) every five minutes must be within a range of ±10% of the contract amount with respect to the control instruction amount (e.g. reduction instruction amount) given by the control command from the higher-level system.

[0028] In the case of tertiary control reserve [1] or tertiary control reserve [2] in the supply and demand adjustment market, it is necessary to bid the amount of electricity that can be increased / decreased the day before or earlier. Specifically, in the case of tertiary control reserve [1], bidding must be made between 14:00 on the previous Monday and 14:00 on the previous Tuesday, and in the case of tertiary control reserve [2], bidding must be made between 12:00 and 14:00 the previous day. The contract process is then carried out between 14:00 and 15:00. If the contract is concluded as a result, the ΔkW contract amount is calculated, and this ΔkW contract amount becomes the maximum command value. Therefore, if the bid amount is too large, the risk of failure of the increase / decrease DR increases. On the other hand, if the bid amount is too small, the appropriate incentive (determined by the bid amount x bid price) will not be obtained, so it is important to accurately estimate the bid amount the day before or earlier.

[0029] Figures 6 and 7 are diagrams explaining the pre-screening method for tertiary adjustment reserve [2]. Figures 6 and 7 are based on materials excerpted from Document 3 of the 10th Supply and Demand Adjustment Market Review Subcommittee. In Figure 6, "ΔkW planned for bidding" corresponds to the contract quantity. As shown in Figure 7, it is necessary to adjust the power reduction amount of all consumers in 30-minute increments within a range of ±10% of the ΔkW value with respect to the power control instruction amount from the upper system, within the range of the ΔkW value. In other words, the difference between the target value (power when the power is adjusted by the control instruction amount from the reference value described below) and the average power value (30-minute value) of all consumers in 30-minute increments must be kept within ±10% of the ΔkW contract amount (in the case of tertiary control reserve [2]. In the case of tertiary control reserve [1], the 1-minute value is used).

[0030] Figure 8 is a diagram to explain an example of success determination in tertiary control reserve [1]. Figure 8 is based on materials excerpted from the FY2012 VPP Project Common Demonstration Specifications. Graph G1 shows the reference value equivalent to the estimated (forecasted) value of the demand (electricity) of all consumers. Solid line graph G2 shows the actual demand (electricity). Graph G3 shows the control instruction amount. The reference value is the estimated (forecasted) value of demand calculated immediately before or a certain time before the DR start instruction or control instruction.

[0031] For example, in the case of tertiary control reserve [1], the actual control amount is given 15 minutes before the target control time. In that case, the response evaluation is judged to be successful if the 1-minute value (average power value for 1 minute) is within ±10% of the ΔkW contract amount with respect to the target value (= reference value - control instruction amount). In other words, it is considered successful if the demand reduction amount is between (control instruction amount + 10% of contract amount) and (control instruction amount - 10% of contract amount).

[0032] In the example shown in the figure, the ΔkW contract amount is 1,000kW, and 10% of 1,000kW is 100kW. A control instruction is given 15 minutes before the control target time 9:00, and the control instruction amount (reduction instruction amount) is 1,000kW. If (reference value - 1,000)kW is the target value, and the power value after the aggregator's demand adjustment is ±100kW from the target value, that is, if the demand reduction amount is 1,100 to 900kW, the judgment result is success. At the change instruction time (10:43) within the control target time (9:00 to 12:00) corresponding to the product block time, an instruction to change the control amount for the change target time (10:58) is given. If the reduction amount of the 1-minute average kW from the change instruction time to the change target time is within the range of ±10% of the ΔkW contract amount for either the control instruction amount before or after the change, it is considered successful.

[0033] The range in which the difference between the 1-minute or 30-minute power value and the target value is within ±10% of the ΔkW contract amount is defined as the successful section S (see Figure 8). In the case of tertiary control capacity [1], the 1-minute power value is used, and in the case of tertiary control capacity [2], the 30-minute power value is used. The proportion of the time within the successful section S out of the controlled time is called the stay rate. The stay rate may be calculated in any time unit (5-minute units, unit of controlled time, etc.). A responsive evaluation may be performed according to the stay rate.

[0034] The above outline of this embodiment has been explained assuming the supply and demand adjustment market system that began in fiscal year 2021. Next, the outline of this embodiment will be explained assuming the case of economic DR.

[0035] As stated in https: / / www.jstage.jst.go.jp / article / ieejpes / 139 / 10 / 139_NL10_10 / _pdf / -char / ja, in the current supply and demand operation, the power generation and sales actors are required to simultaneously and simultaneously set the planned values ​​(in 30-minute units) by the power company, and it is necessary to formulate the planned values ​​for both power generation and sales in advance. Simultaneous matching of planned values ​​means matching the power generation plan with the demand plan. If there is a certain amount of discrepancy between the planned value and the actual value, a penalty called an imbalance fee may be imposed. Therefore, when the demand forecast changes, it is often the case that the planned value is reviewed in advance by procuring the necessary power, and the actual value is matched to the planned value. In the case of the power generation side, the decision on whether to procure the necessary power is made by considering the economic merits of adjusting the generator output and trading in the power trading market (wholesale power trading market, hourly market, etc.). On the other hand, in the case of the seller, if the remuneration paid to consumers for demand adjustment is cheaper than the cost of procuring electricity, there is an economic benefit to the seller by suppressing demand (saving electricity) with a remuneration lower than the market price. Therefore, it is possible for the seller to suppress demand (adjust supply and demand). This demand adjustment is called "Economic DR". For example, consider a case where the original planned value of demand was 1000kWh, but the planned value of demand exceeds the planned value of demand by 1500kWh. In this case, it is necessary to procure 500kWh of electricity from the electricity trading market, but if the apparent demand can be reduced by 100kWh by generating electricity or discharging rechargeable batteries, the amount of electricity procured from the electricity trading market can be reduced by 100kWh to 400kWh.

[0036] In economic DR, the problem of calculating how much the amount of procurement from the electricity trading market can be reduced, that is, how much the apparent demand can be reduced, can be understood in the same framework as the supply and demand adjustment market in Figure 1. Economic DR does not necessarily have a higher-level system such as DRAS, but it is similar in that it is obligated to balance the planned value. In order to match the actual demand with the planned value, there are two options: procurement from the electricity trading market and procurement from consumers (charging and discharging of storage batteries). Of these, the procurement from consumers, which is cheaper, is considered as bidding, and the goal of economic DR is to maximize the amount of procurement from consumers. The difference is that the evaluation interval and bidding interval (hereinafter called block) of the planned value balance are both 30 minutes, and that instead of obtaining a direct incentive by increasing the amount of procurement from consumers as in the supply and demand adjustment market, an indirect incentive is obtained by reducing the fee for each block (the fee for procurement from the electricity trading market), and the unit price for each block may be different.

[0037] In addition, the three cases of the supply and demand adjustment market (pre-screening), the supply and demand adjustment market (actual evaluation), and economic DR can be treated uniformly by considering the variables listed below.

[0038] Number of blocks (or unit time of blocks) Price of each block Evaluation unit (evaluation length)

[0039] In the case of a supply and demand adjustment market (pre-screening), the number of blocks should be 1, the price of the block should be none, and the evaluation unit should be 1 minute for tertiary adjustment capacity [1] and 5 minutes for tertiary adjustment capacity [2]. In the case of a supply and demand adjustment market (actual evaluation), the number of blocks is 1, the price of the block is none, and the evaluation unit is 1 minute for tertiary adjustment capacity [1] and 30 minutes for tertiary adjustment capacity [2]. In the case of economic DR, the number of blocks is set to DR time divided by 30 minutes, the price of the block is set to the unit price for procurement from the electricity trading market, and the evaluation length is set to 30 minutes. In the case of economic DR, there is no benefit to increasing or decreasing the supply beyond the original planned value, which is another difference from the supply and demand adjustment market; however, this point will be discussed later.

[0040] FIG. 9 is a block diagram showing in detail the configuration of the DR possible amount estimation device 100 and the consumers 10 (consumers A, B, C, ...) according to this embodiment. FIG. 9 also shows a power system 500 and a higher-level system 600 such as a DRAS owned by a power company 700 or the like. Although the figure shows only the configuration of consumer A, consumers B, C, ..., etc. also have a similar configuration. The configuration shown in FIG. 9 is an example, and some of the elements shown in FIG. 9 may not be present, or additional elements may be present. For example, FIG. 10 is an example of a block diagram of a configuration in which some elements are omitted from the configuration shown in FIG. 9 (for convenience, this is called a simplified configuration).

[0041] 9, a receiving unit 110 of the DR possible amount estimation device 100 acquires a meter value 31 per minute and a charge / discharge value 32 per minute (at least one of a charge value and a discharge value) from a consumer 10 via a communication network 400. The communication network 400 may be a wide area network such as the Internet, a local area network, or a private network. The receiving unit 110 also receives a power reduction command 30 (DR command or control command) from a higher-level system 600 via the communication network 400. When the power reduction command 30 is received, a processing unit 120 of the DR possible amount estimation device 100 estimates a DR possible amount, which will be described later.

[0042] The processing unit 120 of the DR possible amount estimation device 100 may have a charge / discharge plan creation function. In this case, the processing unit 120 creates a charge / discharge plan for the consumer based on the meter value 31 per minute and the charge / discharge value 32 per minute during the DR time period, for example, and transmits a charge command 33 or a discharge command 34 to the consumer 10. The creation of the charge / discharge plan and the transmission of the charge command 33 or the discharge command 34 are performed at regular intervals (for example, every 5 minutes). The storage battery 27 of the consumer 10 that receives the charge command 33 or the discharge command 34 charges or discharges at a predetermined charge power value or a predetermined discharge power value. The configuration and operation of the charge / discharge plan creation function are not essential to this embodiment, so further explanation will be omitted.

[0043] A consumer 10 receives a supply of power from a power system 500. The supplied power is provided to a load 22 through a distribution board 21. The amount of power supplied from the power system 500 is measured, for example, every minute by a power meter 20. In addition, a storage battery 27, an electric vehicle (EV) 26, a photovoltaic (PV) panel 25, etc. are connected to the distribution board 21 through a PCS 23. The storage battery 27 may be a part of the EV 26.

[0044] The storage battery 27 and the electric vehicle (EV) 26 can receive at least one of an external signal, such as a charging command 33 and a discharging command 34, through a gateway (GW) 24 such as an HEMS. The storage battery 27 can execute charging or discharging based on the charging command 33 or the discharging command 34. The storage battery 27 can also transmit a charging / discharging value 32 indicating the amount of charged or discharged power to the DR possible amount estimation device 100 through the gateway 24.

[0045] The power meter 20 transmits the measured meter value 31 to the DR possible amount estimation device 100. The power meter 20 transmits the meter value 31 without passing through the gateway 24. However, a configuration in which the meter value 31 is transmitted through the gateway 24 is also possible.

[0046] The DR possible amount estimation device 100 includes a receiving unit 110, a processing unit 120, an input / output DB 200, a history DB 191, and a DR possible amount DB 210. The processing unit 120 includes a storage battery SoC time series estimation unit 140, a demand estimation unit 150, and a DR possible amount estimation unit 160. The input / output DB 200 stores DR content information 170, battery specification information 180, and parameter information 190.

[0047] The DR possible amount estimation device 100 is connected to an input / output I / F 220 with a user who is an operator of the device 100, by wire or wirelessly. The input / output I / F 220 may be connected to the DR possible amount estimation device 100 via a communication network 400. The input / output I / F 220 includes an operation input unit 230 and a display unit 240. The operation input unit 230 is a device for inputting information or data, such as a keyboard, a mouse, a touch panel, a voice input device, or a gesture input device. The display unit 240 is a device for displaying information or data on a screen, such as a liquid crystal display device or an organic EL display device.

[0048] The operation input unit 230 has a function of inputting information to be stored in the input / output DB 200. For example, the input / output DB 200 may download data from an arbitrary external device based on user instruction information from the input / output I / F 200, and store the data in the input / output DB 200. The display unit 240 has a function of displaying information of the input / output DB 200 or information of the DR possible amount DB 210. The display unit 240 may have a function of displaying information of the DR possible amount DB 210 or data based on the information.

[0049] The receiving unit 110 receives the meter value (measured value) 31 and the charge / discharge value 32 from the consumer 10 via the communication network 400. For example, the meter value 31 and the charge / discharge value 32 are received every minute. The receiving unit 110 stores the received meter value 31 and the charge / discharge value 32 in a history DB 191. The history DB 191 stores a history of the charge / discharge value 32 in a first period and a history of the meter value 31 in a second period. The first period and the second period may be the same or different. The receiving unit 110 also receives a power reduction command 30, which is an example of a control command from the upper system 600.

[0050] The storage battery SoC time series estimation unit 140 estimates the time series of the storage battery SoC of each consumer based on the charge / discharge value 32 stored in the history DB 191, thereby calculating the SoC time series estimation value 141 of each consumer. The target time period of the estimation corresponds to, for example, the second period which is the DR time period. Note that, although it is assumed in this embodiment that the DR time period to be estimated is a future time period, estimation for a past time period is also not excluded. Note that estimation for a future time period may be specifically called a prediction.

[0051] Furthermore, the storage battery SoC time series estimation unit 140 estimates the time during which the EV 26 (or the storage battery 27) is not connected to the house, and calculates the unconnected time series estimation value 142. The estimation is performed, for example, for the DR time period (second period). If the EV 26 is not connected to the house, the storage battery in the EV 26 cannot be used for supply and demand adjustment. When the EV 26 is not connected to the house, it means that the storage battery in the EV 26 is not connected to the house power grid (PCS 23) so as to be capable of charging and discharging. In this embodiment, the time during which the EV 26 (or the storage battery 27) is not connected to the house is estimated, but the time during which the EV 26 is connected to the house may also be estimated. The time during which the EV 26 is connected to the house or the time during which the EV 26 is not connected to the house may also be described as connected / unconnected time.

[0052] The demand estimation unit 150 obtains a demand time series estimate value 151 of each consumer by estimating a time series of the power demand (power demand) of each consumer based on the meter value 31 stored in the history DB 191. The estimation is performed, for example, for a DR time period. The estimation method may be the same as that of the SoC time series estimate value 141 and the unconnected time series estimate value 142. Alternatively, the demand value may be estimated by regression analysis from the meter value 31. Here, the power meter 20 may measure a meter value that is the sum of the demand value and the charge / discharge amount. In this case, in order not to include the charge / discharge amount of the storage battery in the calculated demand value, the demand value may be obtained by subtracting the charge amount of the storage battery from the value measured by the power meter 20 and adding the discharge amount to it (see Equation (1) and Equation (2) described later).

[0053] The DR possible amount estimation unit 160 estimates the DR possible amount, which is the amount of power adjustment possible when using the storage battery 27 of each consumer, based on the demand time series estimated value 151, the SoC time series estimated value 141, and the unconnected time series estimated value 142, and stores the estimated DR possible amount in the DR possible amount DB 210. The DR possible amount (amount of power adjustment possible) corresponds to the total chargeable amount or dischargeable amount of the storage batteries (including the case of storage batteries provided in EVs) of the consumer group.

[0054] Here, a known method may be used for each consumer as an algorithm for the operation of the storage battery SoC time series estimation unit 140 and the demand estimation unit 150. Simply, the actual demand value or the actual SoC value from k days ago may be used as the demand time series estimation value 151 and the SoC time series estimation value 141 as it is, or a method of shifting the actual value by a fixed value may be used. The estimated values ​​may be calculated using information such as attributes of a day, such as a weekday or a holiday, weather, and temperature. In an example using multiple forecast scenarios, which will be described later, the actual demand or SoC value for each day within the past few days may be used as the demand time series estimation value 151 and the SoC time series estimation value 141 as it is, or a method of restoring or estimating a non-existent past actual (fictitious actual) from an existing actual may be used. As for the unconnected time series estimation value 142, for example, the connection history of the EV may be stored, and the actual value from k days ago may be used as the unconnected time series estimation value 142 as it is, or a method of shifting the actual value by a fixed value may be used. Also, the estimated value may be calculated using attributes of the day, such as weekday or holiday, and information on weather, temperature, etc. In an example using multiple forecast scenarios, which will be described later, the actual value of the connection status for each day within the past few days may be used as it is as the non-connection time-series estimated value 142, or a method may be adopted in which a non-existent past result (fictitious result) is restored or estimated from an existing result.

[0055] In addition, in this embodiment, there are no particular limitations on the method of data transmission and reception via the network by the receiving unit 110 and the method of data input and output in the input / output DB 200. In the following, data related to input and output of the DR possible amount estimating unit 160 will be described in detail.

[0056] [SoC time series estimate 141 and unconnected time series estimate 142] The details of the SoC time series estimated value 141 and the unconnected time series estimated value 142 created by the storage battery SoC time series estimation unit 140 will be described with reference to Fig. 11. The left diagram in Fig. 11 shows examples of the SoC time series estimated value 141 and the unconnected time series estimated value 142. The right diagram in Fig. 11 shows an example in which data on the SoC estimated value of each consumer is displayed in a graph. Times when there is no graph mean that the storage battery is unconnected. Unconnected storage batteries include cases where an EV is not connected.

[0057] FIG. 11 shows a non-connection time series estimate 142 (1 for connection, 0 for no connection) that indicates the connection status of each consumer for 30 minutes from 18:00 to 18:30 every minute, and a SoC time series estimate 141 that indicates the estimated SoC (in kWh) of the storage battery of each consumer every minute. If the storage battery is an EV storage battery, it will be non-connected if the EV is absent or forgotten to be connected. If an event in which an EV is connected or disconnected occurs during the DR time period, it will have a large impact on the DR possible amount, so the non-connection time series estimate 142 is important. In addition, for storage batteries connected to a home, various charging and discharging controls are performed autonomously according to the settings on the home side. For example, there may be cases where the air conditioner is set to operate during a specific time period, or the water is set to boil during a specific time period. Therefore, there may be cases where charging and discharging starts or ends at a predetermined time or after a certain time has elapsed since the EV arrived at the consumer's home.

[0058] In this example, consumer 1 has an SoC of 5.00 kWh at 18:00, and thereafter the estimated SoC value increases by 0.06 kWh (= 3.6 kW) per minute (i.e. the battery continues to charge after 18:00). Consumer 2 has a constant SoC of 1.25 kWh until 18:15, and the battery is disconnected (e.g. the EV is not present) after 18:15. Consumer 3 has an unconnected battery (e.g. the EV is not present) until 18:05, and at 18:05 the battery is connected with an SoC of 3.93 kWh, and after 18:10 the estimated SoC value decreases by 0.03 kWh (= 1.8 kW) per minute (i.e. the battery continues to discharge after 18:10).

[0059] [Demand time series estimate 151] The demand time-series estimated value 151 generated by the demand estimator 150 will be described in detail with reference to Fig. 12. Fig. 12 shows an example of the demand time-series estimated value 151.

[0060] Here, the estimated demand value (unit: Wmin) of consumers for the 15 minutes from 18:00 to 18:15 is shown every minute. There are basically no missing demand readings, and values ​​are shown for all times. The demand value can be obtained by the following method. The meter value, which combines the demand value and the charge / discharge amount, is measured. Meter value = Demand + Charge amount - Discharge amount (1) The following relationship holds true. therefore Demand = meter value - charge amount + discharge amount (2) The demand value can be obtained by the following relational expression.

[0061] [DR content information 170] The DR content information 170 in the input / output DB 200 will be described in detail with reference to FIG. 13 and FIG. 13 shows an example of DR content information 170 in the case of a supply and demand adjustment market. The DR content information 170 includes information such as DR date, time period, increase / decrease, block length, evaluation length, and block price.

[0062] Here, a case is shown where a downward DR was issued from 18:00 to 21:00 on January 13th, and the block length was specified as 3 hours. This DR content information is not the DR that was actually issued, but the content of the DR that was specified (input) by the user as expected to occur in the future. Here, a block is the time unit for bidding, and if the block length is 180 minutes, the bid amount for each 180 minutes must be calculated. In the case of a supply and demand adjustment market, one bid amount is bid for the entire three time periods, so the number of blocks is always 1. For this reason, the block length is 180 minutes, which corresponds to the entire DR time period. The evaluation length is also 5 minutes. In this case, the success condition is that the power for each 5 minutes is included in the allowable range of the target value (= reference value - command value (control instruction amount)) (adjusted to a range of ±10% of the target value). Note that here, the DR direction is "downward," but if it is "upward," the target value is the reference value + command value.

[0063] 14 shows an example of DR content information 170 for economic DR. Here, a downward DR is issued from 18:00 to 21:00 on January 13th, and the block length is specified as 30 minutes (or the number of blocks is 6). This DR content information is not a DR that was actually issued, but the content of a DR that was specified (input) by the user as a DR that is expected to occur in the future.

[0064] If the block length is 30 minutes, the DR possible amount should be calculated for six blocks obtained by dividing the three hours from 18:00 to 21:00 by 30 minutes. In this case, a block price is set for each block, and the DR possible amount is calculated to maximize the sum of the product of the bid amount and the price for each block.

[0065] In economic DR, a "downward DR" occurs when the actual value is likely to exceed the planned value. In this case, if the planned value is exceeded, a fee will be paid to procure electricity from the electricity trading market. On the other hand, if the electricity can be reduced to the planned value, this fee will not be required, and this procurement cost can be considered as a block price.

[0066] [Battery Specification Information 180] The storage battery specification information 180 in the input / output DB 200 will be described in detail with reference to Fig. 15. Fig. 15 shows an example of the storage battery specification information 180. The storage battery specification information 180 includes capacity, discharge output, charge output, minimum meter, maximum meter constraint, etc. Here, the capacity of the storage batteries of the consumers 1 to 4 is 10.0 kWh, the discharge output and charge output are 4.0 kW, the minimum meter constraint is 100 W, and the maximum meter constraint is 6000 W. The meter constraint is a constraint on the value of the power meter 20, and the meter value 31 of the power meter 20 must be 100 W or more and 6000 W or less. Since the minimum meter constraint is a positive value, reverse power flow is prohibited. To permit reverse power flow, the minimum meter constraint should be set to a negative value.

[0067] [Details of apparent charge / discharge margin calculation] Although the discharge output and charge / discharge output themselves shown in the above-mentioned Fig. 15 are values ​​independent of time, the apparent chargeable / dischargeable capacity varies with time depending on whether the storage battery is connected at each time and whether or not there is control (original battery control) preset for the storage battery. Details of the apparent chargeable / dischargeable capacity will be explained using Figs. 16 and 17. An example will be shown in which the apparent chargeable / dischargeable capacity varies with time depending on whether or not there is original battery control for the storage battery.

[0068] FIG. 16(A) shows an example of the calculation result of the chargeable and dischargeable amounts when the original battery control is not taken into consideration. The dischargeable and chargeable amounts at time t for consumer k are respectively expressed as E k,t ,F k,t Let us assume that. First, an example will be given in which the apparent chargeable / dischargeable capacity of a storage battery changes with time depending on whether it is connected or not. In the case of the estimation results of FIG. 11 described above, the storage battery is connected to consumer 3 from 18:05. In this case, if the presence or absence of the storage battery (for example, the presence or absence of the EV) is judged in 30-minute intervals, charging / discharging is not allowed until 18:30. For this reason, as shown in FIG. 16(A), k,t(dischargeable capacity) is 0, and E after 18:30 k,t is 2.0.

[0069] Similarly, for consumer 2, the storage battery is disconnected from 18:16 (see Figure 11). In this case, if the connection or non-connection of the storage battery (for example, the presence or absence of an EV) is judged every 30 minutes, discharge is not possible during the entire time period. However, if a logic is used that allows discharge until just before the battery is disconnected, the E of consumer 2's storage battery from 18:00 to 18:30 is as shown in Figure 16(A). k,t is 1.0. This value is calculated as 2 x 15 / 30, because 2 kW is used for 15 minutes out of the total 30 minutes. Note that for consumer 3, a logic similar to that for consumer 2 can be used to calculate the dischargeable amount, using logic that allows discharge from when connected at 18:05 until 18:30.

[0070] The consumers other than those described above (consumers 1 and 4) are either always connected or not connected in 30-minute time slots. Therefore, for consumers 1 and 4, only the connected time slots are k,t and F k,t is a non-zero value, and during the non-connection period, E k,t and F k,t will have a value of zero.

[0071] Fig. 16(B) shows an example of the calculation result of the chargeable / dischargeable amount when the original battery control is taken into consideration. Fig. 17 is a supplementary explanatory diagram of the chargeable / dischargeable amount calculation when the original battery control is taken into consideration. As shown in Fig. 17, when the original battery control is present, the value increases or decreases from the rated output accordingly, so it is necessary to calculate the apparent chargeable / dischargeable amount.

[0072] First, consumer 1 is estimated to continue charging at 3.6 kW from 18:00 to 19:30 (see Figure 11). Therefore, during the time period when this charging is estimated to occur, the apparent discharge reserve is 7.6 kW, which is 3.6 kW higher than the rated capacity, and the charge reserve is 0.4 kW, which is 3.6 kW lower than the rated capacity.

[0073] On the other hand, for consumer 3, it is estimated that discharging will continue at 1.8 kW after 18:10 (see Figure 11), so the apparent discharge reserve is 2.2 kW, which is 1.8 kW less than the rated capacity, and the charging reserve is 5.8 kW, which is 1.8 kW more than the rated capacity.

[0074] For consumer 2, the original battery control does not exist during the time period from 18:00 to 18:15 when the storage battery is estimated to be connected, so that the charging capacity and the discharging capacity both match the rated output of 4.0 kW.

[0075] For consumer 4, since the original battery control does not exist in the storage battery and the estimated SoC value is 0, only charging is possible and the charging capacity matches the rated output of 4.0 kW.

[0076] From the above, when considering the presence or absence of the original battery control in addition to the presence or absence of the battery connection, the value shown in Fig. 16(B) is set to E k,t and F k,t Note that kWh for 30 minutes is half the value of kW. For example, the E k,t was calculated to be 7.6kW, but since Figure 16(B) is in kWh units, the value 3.8, which corresponds to 3.8kWh, which is equal to 7.6kW, is shown. k,t Or F k,t The calculation of (a) uses the SOC estimated value and the unconnected estimated value as a time series after the DR start time (the estimated value at the DR start time is not commonly applied throughout the DR time period), which improves the calculation accuracy of the DR possible amount.

[0077] Whether the original battery control is set to be active during the DR time period differs depending on the consumer, so the method of Fig. 16(A) or Fig. 16(B) can be used depending on the situation or settings of the consumer. For example, if the consumer has set the original battery control to be released during the DR time period, the method of Fig. 16(A) can be used. Information on whether the original battery control is performed during the DR time period for each consumer may be stored in the input / output DB 200.

[0078] [Parameter information 190] The parameter information 190 in the input / output DB 200 will be described with reference to Fig. 18. Fig. 18 shows an example of the parameter information 190. The parameter information 190 is a parameter used when the DR possible amount estimation unit 160 estimates the DR possible amount using a plurality of scenarios. The parameter information 190 includes, for example, the number S of scenarios used for estimation, the number of days of past data SCENARIO_DAYS used to create a scenario, and a value P indicating which estimation result is to be selected when the estimation results for each scenario are sorted in ascending or descending order. Details of each parameter will be described later.

[0079] [DR capacity DB210] The DR possible amount DB210 that stores the DR possible amount information that is the output of the DR possible amount estimating unit 160 will be described with reference to Fig. 19. The operation of the DR possible amount estimating unit 160 will be described in detail later. Fig. 19 shows an example of the DR possible amount DB210. Here, the total DR capacity (power adjustment capacity) of all consumers for each block from 18:00-18:30 to 20:30-21:00 and the breakdown for each consumer are shown in kWh (note that because each cell is 30 minutes, this value will be doubled if expressed in average kW). For example, the total DR capacity from 18:00-18:30 is 3.0 kWh, with Consumer 1 accounting for 2.0 kWh and Consumer 3 accounting for 1.0 kWh.

[0080] Hereinafter, examples of the operation of the DR possible amount estimating unit 160 will be described as first to fifth embodiments.

[0081] (Example of lowering DR in the simplified configuration shown in FIG. 10: Example 1) Here, an embodiment will be described in which, in the simplified configuration of Figure 10, the DR possible amount estimation unit 160 estimates the DR possible amount using the SoC time series estimate value 141, the unconnected time series estimate value 142, the storage battery specification information 180, and the DR content information 170 as input, and stores information on the estimated DR possible amount in the DR possible amount DB 210.

[0082] FIG. 20 is a flowchart of the process of the simplified configuration of FIG. First, in Step 1, the battery SoC time series estimation unit 140 estimates the connection status and the SoC of each consumer during the DR time period, and generates an SoC time series estimation value 141 that represents the estimated SoC result of the battery of each consumer, and an unconnected time series estimation value 142 that represents the estimated result of the connection status of the battery of each consumer.

[0083] Next, in Step 2, the DR possible amount estimation unit 160 calculates the dischargeable amount (supplyable amount) of each consumer for each block based on the SoC time series estimation value 141 and the unconnected time series estimation value 142. As described above, the discharged power can be used within the home or supplied outside the home (provided to a buyer).

[0084] Finally, in Step 3, the DR possible amount estimation unit 160 sums up the dischargeable amounts of all consumers for each block, and outputs the total as the DR possible amount (the amount of power adjustment possible).

[0085] As a specific example, the details of Step 2 in FIG. 20 will be described below when the SoC time series estimate 141 and the unconnected time series estimate 142 in FIG. 11, the storage battery specification information 180 in FIG. 15, and the DR content information 170 in FIG. 14 are input.

[0086] First, for consumer 1, the estimated SoC result at 18:00 is 5.0 kWh, and the discharge output (maximum value) is 4.0 kW, so if the discharge output continues at the maximum of 4.0 kW (2.0 kWh per 30 minutes), it can be seen that it can continue for 1 hour and 15 minutes. Therefore, when the DR possible output is calculated every 30 minutes, it can be seen that 2.0 kWh of power can be discharged for the blocks of 18:00-18:30 and 18:30-19:00, and 1.0 kWh for the block of 19:00-19:30.

[0087] Next, for consumer 2, although the estimated SoC at 18:00 is 1.25kW, it will not be able to connect at 18:15, so it will only be able to discharge for the first 15 minutes. In addition, since the discharge output (maximum value) is 4.0kW, it will be able to discharge 1.0kWh of power in 15 minutes. Note that this calculation was made under the assumption that it will be reliably connected until 18:15, but if there is a high possibility that it will not be connected before 18:15, it can be considered that it will not be able to discharge, and the dischargeable amount can be set to 0kWh.

[0088] Next, consumer 3 is expected to be absent at 18:00, so it is assumed that discharge will not be possible until 18:30. In this case, the dischargeable amount from 18:00-18:30 will be 0kW. On the other hand, since the estimated SoC at 18:30 is 3.3kWh, if the maximum discharge output of 4kW is continued, although 2.0kWh will be able to be discharged in the first block from 18:30-19:00, only the remaining 1.1kWh can be discharged in the next block from 19:00-19:30.

[0089] Next, for consumer 4, the estimation result shows that the consumer has been connected continuously since 18:00, but since the estimated SoC result is 0 kW, the dischargeable amount is 0 kWh. The above results are summarized in the DR possible amount information shown in FIG.

[0090] In Step 3, the DR possible amount estimation unit 160 sums up the values ​​of each consumer for each block, thereby obtaining the total DR possible amount of all consumers, as shown in Fig. 19. That is, the total DR possible amount is 3.0 kWh, 4.0 kWh, 2.3 kWh, 0 kWh, 0 kWh, and 0 kWh in the order of the blocks.

[0091] Using the above method, it is possible to calculate the DR possible amount (dischargeable amount) of one or more consumers even if there is a possibility that a storage battery (e.g., a storage battery installed in an EV) will not be connected to the power grid.

[0092] (Example of raising DR: Example 2) In the first embodiment, the case of a lowering DR was shown, but in the second embodiment, the case of an increasing DR will be described. In the case of an increasing DR, the remaining capacity of the storage battery is defined as "capacity value-estimated SoC value" ("-" indicates subtraction) and the discharge output in the description of the first embodiment is replaced with the charge output, so that the DR possible amount can be estimated by the same process as in the first embodiment. An example of calculating the DR possible amount in the case of an increasing DR is shown below. The time period for increasing DR is set to 18:00-21:00.

[0093] For consumer 1, the charge headroom (charging headroom) at 18:00, i.e., the remaining capacity of the storage battery, is calculated as 10.0-5.0=5.0kWh, calculated by "capacity value - estimated SoC value at 18:00". Since the charging output (maximum value) is 4kW, the available charging time is (5.0 / 4.0=1.25h=) 1 hour and 15 minutes.

[0094] As for consumer 2, it is estimated that the consumer will only be connected from 18:00 to 18:15, so the chargeable amount will be 1 kWh, just like in the case of downward DR.

[0095] For consumer 3, the maximum charge capacity at 18:30 is calculated as 10.0-3.3=6.7kWh, calculated by "capacity value - estimated SoC value at 18:30". As the charging output (maximum value) is 4.0kW, the available charging time is (6.7 / 4.0=) 1.675h, or approximately 1 hour and 40 minutes.

[0096] On the other hand, for consumer 4, the charge margin at 18:00 is calculated as 10.0-0.0=10.0kWh, calculated by "capacity value - estimated SoC value at 18:00". As the charging output (maximum value) is 4.0kW, it is possible to continue charging from 18:00 to 20:30.

[0097] The above calculation results are summarized in Figure 21.

[0098] Figure 21 shows the DR possible amount information in the case of upward DR. The DR possible amount (chargeable amount) of each consumer for each block and the total DR possible amount are shown. Also, the total DR possible amount of all blocks, that is, the DR possible amount for the entire DR time period, is shown.

[0099] Using the above method, it is possible to calculate the DR possible amount (here, the chargeable amount) of one or more consumers even if there is a possibility that a storage battery (e.g., a storage battery installed in an EV) will not be connected to the power grid.

[0100] (Example of economic DR that maximizes profits by bidding per block: Example 3) In the first and second embodiments, a method was described in which all consumers in each block divided into time periods discharge or charge at the maximum possible output, thereby achieving DR toward the front. Here, however, an embodiment will be described in which a unit price is defined for each block, and the sum of the bid volume x unit price is maximized.

[0101] In the case of lowering DR, this problem can be expressed as the following optimization problem. (In the case of raising DR, "-I" in the following formula (4) is b(t) " to "I b(t)" Note that since the charged or discharged electricity will eventually be discharged or recharged, the electricity purchase price at this point has been ignored, but if you are considering the balance only for this time period, you can think of the value of Pb as the bid price + electricity purchase price in the case of discharging (because discharging reduces the amount of electricity purchased), and the bid price - electricity purchase price in the case of charging (because charging increases the amount of electricity purchased). In the case of economic DR, since the goal is to approach the planned value, there is no point in charging or discharging beyond the planned value, so it is acceptable to set upper and lower limit constraints that mean that Ib must not exceed the planned value. Note that since the planned value is often not reached even with full charging and discharging, there is no problem in many cases even if the upper and lower limit constraints are omitted.

[0102] JPEG2025001561000002.jpg47168 Variable -x k,t : A continuous variable that is set to 1 if a maximum output discharge request is made to consumer k∈K at time t∈T, and set to 0 if no discharge request is made. -z k,t : A continuous variable that is set to 1 if a maximum output charging request is made to consumer k∈K at time t∈T, and set to 0 if no charging request is made. -I b : Bid amount for block b ·constant: -K: A collection of consumers -T: Set of times (evaluation units) -E k,t : Discharge amount when consumer k discharges at maximum output at time t -F k,t : Charge amount when consumer k charges at maximum output at time t -G k,t : The original charge / discharge plan amount of consumer k at time t (+ for charging, - for discharging) -A k : Discharge capacity of consumer k at the DR start time -C k : Charging capacity of consumer k at the DR start time -b(t): A function that returns the block that contains time t -Pb: Price (bid) for block b

[0103] Here, equation (3) is an equation that represents profit maximization. Equation (4) represents an equation that achieves a target value equivalent to the bid amount through charging and discharging. Note that here, a method is adopted that ignores the error between a reference value (e.g., an estimated value immediately before the start of DR (e.g., one hour before). See the reference value (one minute value) in FIG. 8) and an original demand estimation value (demand estimation value of the demand estimation unit 150. For example, the estimated value of the previous day), but the difference may also be taken into consideration. Equation (5) is a constraint equation that represents that the SoC of each consumer's storage battery at each time falls within the range from 0 to the capacity.

[0104] Here, E k,t is the discharge output of the storage battery of consumer k, and F k,t is the charging output of consumer k’s storage battery.

[0105] Also, A k is the amount equivalent to the SoC at the start of DR for consumer k, and C k is the amount equivalent to the capacity of consumer k at the start of DR minus SoC.

[0106] The above variable x k,t ,z k,t ,I b As a solution for finding an optimal solution or a quasi-optimal solution, a mathematical programming solver such as Gurobi Optimizer or CPLEX may be used, or a metaheuristic solution such as a gradient method, simulated annealing, or genetic algorithm may be used.

[0107] The above formulation is an example, and other objective functions and constraints may be used. For example, to add a condition that consumer k must discharge depending on the consumer's situation as an additional problem setting, the constraint formula x k,t Similarly, to add a condition that consumer k must charge, add the constraint z k,t= 1. To add a condition that consumer k is never allowed to charge, add the constraint x k,t Similarly, to add a condition that consumer k is never allowed to discharge, add the constraint z k,t Just add =0.

[0108] In addition, the above formulation only optimizes the behavior of consumers when they behave as expected. When the customer's estimated demand value deviates from the reference value If consumers do not operate as requested In cases where these errors are considered, the errors may be estimated in advance and the estimated values ​​may be used for optimization.

[0109] (Specific example of Example 3) As a specific example of the third embodiment, consider a case where 18:00-21:00 is divided into six blocks for bidding, and the bid unit prices for each block are 5 yen, 5 yen, 5 yen, 20 yen, 20 yen, and 20 yen, with the latter unit price being higher. The bid unit prices are determined in advance by any method. The bid unit prices for each block may be the same. FIG. 22(A) shows an example of DR content information in this case. In addition, when the SoC time series estimated value 141 and the unconnected time series estimated value 142 in FIG. 11, the storage battery specification information 180 in FIG. 15, and the DR content information 170 in FIG. 14 are input, the coefficients of the above model are as shown in FIG. 22(B). In this case, when the optimization problem is solved, a calculation result of the DR possible amount as shown in FIG. 22(C) is obtained. Here, x k,t ,z k,t For each customer and each time cell, x k,t If is nonzero, then E k,t x k,t The value of z k,t -F if is nonzero k,t xz k,t The values ​​of charging and discharging are negative and positive (unit: kW), respectively.

[0110] In this case, the DR possible amount of each block is 0.0 kWh, 0.0 kWh, 0.0 kWh, 4.0 kWh, 3.3 kWh, and 2.0 kWh. The DR possible amount of each block is the bid amount of each block I b The total amount of DR possible capacity is 9.3 kWh, the same as in Example 1, but the plan obtained has a biased bid amount toward the later time when the unit price is high. For consumer 4, charging is performed in the first half and discharging in the second half, and a plan is obtained that uses up the charging and discharging capacity of all consumers. Based on the calculation results in FIG. 22(C), the bid amount I b By bidding at this rate, profits are expected to be optimized.

[0111] (Example 4: When reverse power flow is not possible or when there is an upper limit on the amount of charge / discharge) First, variables and constants are defined as follows. D k,t : Estimated demand for consumer k at time t ·u k : Upper limit of power supply for consumer k (upper limit of meter value) l k : Lower limit of power supply for consumer k (lower limit of meter reading)

[0112] If reverse power flow is not possible, the meter value will be k The battery may be controlled so that the meter value does not fall below u k In some cases, the battery is controlled so that the load does not exceed the E k ,F k This can be addressed by changing it to the following:

[0113] In calculating this value, the demand estimation D k,t By improving the prediction accuracy, the accuracy of the DR possible amount can also be improved.

[0114] (Specific example of Example 4) As a specific example of Example 4, a case is considered in which a pre-screening of the supply and demand adjustment market is assumed, and a single bidding block is used for bidding for a down DR during the DR time period of 18:00-18:30 (one block is three hours in the supply and demand adjustment market, but for simplicity, one block is considered to be 30 minutes). Also, a case is considered in which the evaluation time interval is five minutes. In other words, this is a case in which the reduction target must be achieved every five minutes.

[0115] FIG. 23 shows an example of calculation of the DR possible amount in Example 4. As shown in the left diagram of Figure 23, the demand estimation results for each customer every 5 minutes and the discharge output (E in Equation (7)) k,t For simplicity, we assume that the value obtained is constant regardless of time.

[0116] The center diagram of Fig. 23 shows the dischargeable capacity of each consumer in the case of the left diagram of Fig. 23 as a shaded area. In the case where the magnitude relationship between the discharge output and the demand estimation result is constant, such as for consumer 1 and consumer 2, Σ t D k,t , and consumer 2 is Σ t E k,t This dischargeable amount is calculated by the rough demand estimation result (Σ t D k,t ) and find min(Σ t D k,t ,Σ t E k,t ) to derive the dischargeable amount.

[0117] On the other hand, in cases where the demand estimation results in a block monotonically increase (or decrease) as in the case of consumer 3, or where the demand estimation results in a block fluctuate significantly as in the case of consumer 4, D k,t and E k,t The magnitude relationship between the and varies depending on the time. Therefore, by estimating the dischargeable amount at time intervals close to the evaluation interval, a highly accurate dischargeable amount can be obtained.

[0118] The right diagram in Figure 23 is a schematic diagram showing a method for obtaining the possible DR amount from the total dischargeable amount of all consumers (the stacked graph in the shaded area in the center diagram in Figure 23). In the case of a supply and demand adjustment market, since it is necessary to achieve the target during the entire evaluation time period, the smallest value in the stacked graph can be regarded as the possible DR amount. In the example on the right diagram in Figure 23, the value indicated by the horizontal dashed line is the possible DR amount.

[0119] The minimum value of the stacked graph reflects the bias of the demand of consumer 3 and consumer 4. Therefore, as a result of estimating the demand of consumer 3 and consumer 4 in 5-minute intervals, the DR possible amount can be correctly estimated. Note that, although the description here ignores the capacity of the storage battery, when performing optimization taking the capacity of the storage battery into consideration, the E calculated in this embodiment can be used. k,t The optimization of the third embodiment can be performed using the above.

[0120] (Example of performing scenario optimization while considering the risk that the demand estimation result, etc., deviates from the actual demand value (estimated deviation risk): Example 5) Up to this point, it has been assumed that the demand estimation result and the SoC estimation result do not deviate from the actual values, but in reality, the estimation results may deviate. In this embodiment 5, as a method for conservatively estimating the DR possible amount, a flow for performing optimization taking into account the above-mentioned risk of estimation deviation will be described.

[0121] FIG. 24 is an example of a flowchart for the case where the risk of an estimated deviation is taken into consideration. In Step 1, for each consumer, actual demand data and actual SoC data are extracted from past data for the number of days indicated by SCENARIO_DAYS (parameter). S scenarios including the demand and SoC of the consumer group are created. S may be one or more. The scenarios may be the extracted data itself, or may be generated by processing the extracted data.

[0122] For example, when SCENARIO_DAYS=7, actual data of demand and SoC on different days depending on the scenario are extracted as predicted values ​​for a certain consumer, such as 3 days before for s=1, 5 days before for s=2, 2 days before for s=3, etc., and for other consumers, data on a different day from the above consumer is extracted for the same scenario. Assume that data for at least two or more consumers is on different days for the same scenario. This allows scenarios that combine data for consumers on various days. For example, if many consumers tend to have low SoC in the first block of the DR time period, many scenarios are obtained in which the total SoC for the first block is low, but in some scenarios, some data for consumers on days with high SoC in the first block are also extracted, so that a scenario in which the total SoC for the first block is slightly larger can be realized. Note that demand and SoC are extracted for the same day for each consumer, which maintains consistency.

[0123] Next, in Step 2, for each scenario s (s=1, 2, . . . , S), the optimal bid amount for each scenario is obtained, for example, by the method described in the third or fourth embodiment.

[0124] In Step 3, the obtained results are sorted, for example, in ascending order of total revenue (or total bid amount), and the Pth value from the bottom is adopted as the optimization result.

[0125] In this case, for example, if you make the value of P smaller, you can make a more conservative estimate. If you make the value of P about S / 2, you can make an average estimate. If you make the value of P closer to S, you can make a riskier estimate (closer to the maximum profit).

[0126] (Specific example of Example 5) A specific example of the fifth embodiment will be described with reference to Fig. 25. Assume that S = 100 and P = 5. For simplicity, the case of a single block will be described.

[0127] Fig. 25 is a diagram showing a specific example of the operation of the fifth embodiment. The left diagram in Fig. 25 shows the 1st to 100th optimal bid amounts obtained as a result of Step 2. The center diagram in Fig. 25 shows these 100 values ​​sorted in ascending order. The right diagram in Fig. 25 shows the 5th value P=picked out of these.

[0128] (Example of output screen) Finally, an example of the output screen will be described. FIG. 26 shows an example of the output screen of the display unit 240. The output screen also includes a bid amount calculation button 300 as the operation input unit 230. For example, in the output screen of FIG. 26, the DR day, DR time period, parameter information (SCENARIO_DAYS, S, P), etc. are input, and the bid amount calculation button 300 is pressed, so that the calculation result is output in the screen portion of the charge / discharge request content. As the output format, the total DR possible amount may be displayed in a table format or a bar graph format. In addition, the DR possible amount for each consumer may be output as a breakdown of the total DR possible amount. Note that the unit price of the bid block for every 30 minutes is determined in advance by any method, and although it differs for each bid block in this example, it may be a common value for all bid blocks. It is also possible to carry out a process in which data indicating the bid amount for each block determined here is transmitted to an energy trading market system which processes the energy trading market. In the case of economic DR, since it is the sum of the amount procured from consumers, the amount procured from the power trading market, which is the difference between the planned value and the actual expected value (estimated power demand value) for each block minus the amount procured from consumers, may be output on the screen as the bid amount of electricity to be bid on the power trading market. Furthermore, data showing the amount procured from the power trading market as the bid amount may be transmitted to the power trading market system that processes the power trading market.

[0129] (Hardware configuration) The hardware configuration of the DR possible amount estimation device according to this embodiment will be described with reference to FIG. Fig. 27 shows the hardware configuration of the DR possible amount estimation device which is an information processing device in this embodiment. As shown in Fig. 27, the DR possible amount estimation device according to this embodiment is configured by a computer 1000. The computer 1000 includes a CPU 1001 (central processing unit), an input device 1002, a display device 1003, a communication device 1004, and a storage device 1005, which are connected to each other by a bus 1006.

[0130] The CPU 1001 is a control device and an arithmetic device of the computer 1000. The CPU 1001 performs arithmetic processing based on data and programs input from each device (e.g., the input device 1002, the communication device 1004, and the storage device 1005) connected via the bus 1006, and outputs the arithmetic results and control signals to each device (e.g., the display device 1003, the communication device 1004, and the storage device 1005) connected via the bus 1006.

[0131] Specifically, the CPU 1001 executes the OS (operating system) of the computer 1000, a DR possible amount estimation program (information processing program), and the like, and controls each device constituting the computer 1000. The DR possible amount estimation program is a program that causes the computer 1000 to realize each of the above-mentioned functional configurations of the DR possible amount estimation device. The CPU 1001 executes the DR possible amount estimation program, so that the computer 1000 functions as the DR possible amount estimation device. The input device 1002 is a device for inputting information to the computer 1000. The input device 1002 is, for example, a keyboard, a mouse, and a touch panel, but is not limited thereto. A user can input input information by using the input device 1002.

[0132] The display device 1003 is a device for displaying images and videos. The display device 1003 is, for example, but not limited to, an LCD (liquid crystal display), a CRT (cathode ray tube), or a PDP (plasma display). With these, the display device 1003 can display the optimization result.

[0133] The communication device 1004 is a device for the computer 1000 to communicate with an external device wirelessly or via a wire. The communication device 1004 is, for example, a modem, a hub, or a router, but is not limited to these. Input information may be input from an external device via the communication device 1004.

[0134] The storage device 1005 is a storage medium that stores the OS of the computer 1000, the DR possible amount estimation program, data required for executing the DR possible amount estimation program, and data generated by executing the DR possible amount estimation program. The storage device 1005 includes a main storage device and an external storage device. The main storage device is, for example, a RAM, a DRAM, or an SRAM, but is not limited thereto. The external storage device is, for example, a hard disk, an optical disk, a flash memory, and a magnetic tape, but is not limited thereto. The computer 1000 may include one or more of the CPU 1001, the input device 1002, the display device 1003, the communication device 1004, and the storage device 1005, or may be connected to peripheral devices such as a printer or a scanner. The DR possible amount estimation device may be configured by a single computer 1000, or may be configured as a system consisting of multiple computers 1000 connected to each other. Furthermore, the DR possible amount estimation program may be stored in advance in the storage device 1005 of the computer 1000, may be stored in a storage medium such as a CD-ROM, or may be uploaded onto the Internet. In any case, the DR possible amount estimation program is installed in the computer 1000 and executed to configure a DR possible amount estimation device.

[0135] The present invention is not limited to the above-described embodiments as they are, and the components can be modified and embodied in the implementation stage without departing from the gist of the invention. Various inventions can be formed by appropriately combining multiple components disclosed in the above-described embodiments. For example, a configuration in which some components are deleted from all the components shown in each embodiment can also be considered. Furthermore, the components described in different embodiments can be appropriately combined.

[0136] This embodiment can also have the following configuration. [Item 1] estimating a remaining capacity of the storage battery in a second period different from the first period based on a charge / discharge history of the storage battery of one or more consumers in the first period; a processing unit that calculates a power adjustment possible amount, which is a sum of a chargeable amount or a dischargeable amount of the storage battery of the one or more consumers in the second period, based on an estimated value of a remaining amount of the storage battery. An information processing device comprising: [Item 2] The processing unit estimates a connected / disconnected time of the storage battery during the second period based on a history of a connected / disconnected time, which is a time when the storage battery is connected or not connected so as to be capable of being charged or discharged at the consumer facility, and calculates a chargeable amount or a dischargeable amount of the storage battery at the consumer facility based on the estimated value of the connected / disconnected time. Item 1. An information processing device according to item 1. [Item 3] The processing unit acquires information on power demand of the one or more customers in the second period, and calculates a chargeable amount or a dischargeable amount of the storage battery of the customer based on the power demand information. 3. The information processing device according to item 1 or 2. [Item 4] The processing unit estimates a power demand of the consumer in the second period based on a history of meter values ​​in the consumer in a third period, and calculates a chargeable amount or a dischargeable amount of the storage battery of the consumer based on the estimated power demand. Item 3. An information processing device according to item 3. [Item 5] The processing unit estimates a charge output value and a discharge output value of the storage battery during the second period for each time based on the power demand and the history of charging and discharging of the storage battery, and calculates a chargeable amount or a dischargeable amount of the storage battery of the consumer based on the estimated charge output value and the discharge output value and the estimated power demand. Item 5. An information processing device according to item 4. [Item 6] The processing unit calculates a chargeable amount or a dischargeable amount of the storage battery of the consumer based on a preset control regarding a charging and discharging operation of the storage battery. Item 5. An information processing device according to item 5. [Item 7] The processing unit generates a plurality of scenarios including estimated values ​​of remaining amounts of the storage batteries of the plurality of the consumers in the second period, estimates the possible amount of power adjustment for each of the scenarios, and selects the possible amount of power adjustment from the possible amounts of power adjustment estimated for each of the scenarios. 7. The information processing device according to any one of items 1 to 6. [Item 8] The processing unit generates a plurality of scenarios including estimated values ​​of remaining capacity of the storage batteries of the plurality of consumers in the second period and estimated values ​​of the connection / disconnection times based on the history of charging and discharging of the storage batteries and the history of the connection / disconnection times, estimates the possible amount of power adjustment for each of the scenarios, and selects the possible amount of power adjustment from the possible amount of power adjustment for each of the scenarios. Item 3. An information processing device according to item 2. [Item 9] The processing unit determines a bid amount for the supply and demand adjustment market for the second time period based on the adjustable amount of power. 9. The information processing device according to any one of items 1 to 8. [Item 10] The processing unit transmits data indicating the determined bid amount to a supply and demand adjustment market system that processes the supply and demand adjustment market. Item 10. The information processing device according to item 9. [Item 11] The processing unit receives as input the number of blocks into which the second period is divided and the price for each of the blocks, estimates the possible power adjustment amount for each block obtained by dividing the second period by the number of blocks, calculates the procurement amount for each of the blocks so as to maximize or quasi-maximize a value obtained by multiplying and summing the unit price for each of the blocks and the procurement amount of power from the multiple consumers for each of the blocks, using the possible power adjustment amount for each of the blocks as a constraint condition, and determines, as a bid amount for the power trading market for each of the blocks, the amount of power obtained by subtracting the procurement amount for each block from the difference between a planned value of power demand for each of the blocks and the power demand estimated for each of the blocks. The information processing device according to claim 4. 7. The information processing device according to any one of items 4 to 6. [Item 12] The processing unit transmits data indicating the determined bid amount for each block to an energy trading market system that processes the energy trading market. Item 12. An information processing device according to item 11. [Item 13] The second period is a time period during which demand response is performed. 13. The information processing device according to any one of items 1 to 12. [Item 14] The processing unit receives command information of the demand response specifying the second period, and controls charging / discharging of the storage battery of the one or more consumers during the second period based on the command information. Item 14. An information processing device according to item 13. [Item 15] estimating a remaining capacity of the storage battery in a second period different from the first period based on a charge / discharge history of the storage battery of one or more consumers in the first period; Calculating a power adjustment possible amount, which is a total of a chargeable amount or a dischargeable amount of the storage battery of the one or more consumers during the second period, based on an estimated value of a remaining capacity of the storage battery. Information processing methods. [Item 16] A step of estimating a remaining capacity of the storage battery in a second period different from the first period based on a charge / discharge history of the storage battery of one or more consumers in the first period; calculating a power adjustment possible amount, which is a sum of a chargeable amount or a dischargeable amount of the storage battery of the one or more consumers in the second period, based on an estimated value of a remaining amount of the storage battery; A computer program for causing a computer to execute the above. [Item 17] One or more consumer storage batteries; estimating a remaining capacity of the storage battery in a second period different from the first period based on a charge / discharge history of the storage battery in the first period; Calculating a power adjustment possible amount, which is a total of a chargeable amount or a dischargeable amount of the storage battery of the one or more consumers during the second period, based on an estimated value of a remaining capacity of the storage battery. A processing section; An information processing system comprising: [Explanation of symbols]

[0137] 10 Consumer 20 Power Meter 21 Distribution Board 22 Load 23 PCS 24 Gateway (GW) 25 PV panels 26 Electric Vehicles (EV) 27 Storage battery 30 Power Reduction Directive 31 Meter value (measurement value) 32 Charge and discharge values 33 Charging command 34 Discharge command 100 DR possible amount estimation device 110 Receiving unit 140 Battery SoC Time Series Estimation Unit 141 SoC time series estimates 142 Unconnected Time Series Estimates 150 Demand Estimation Unit 151 Demand time series estimates 160 DR possible amount estimator 161 Aggregation Coordinator (AC) 162 Resource Aggregator (RA) 170 DR content information 180 Battery Specification Information 180 Battery Specification Information 190 Parameter Information 200 Aggregators 230 Operation input section 240 Display section 300 Bid amount calculation button 400 Communication Network 500 Power system 600 Upper System 700 Electric Power Companies 1000 Computers 1002 Input device 1003 Display device 1004 Communication equipment 1005 Storage device 1006 Bus

Claims

1. estimating a remaining capacity of the storage battery in a second period different from the first period based on a charge / discharge history of the storage battery of one or more consumers in the first period; a processing unit that calculates a power adjustment possible amount, which is a sum of a chargeable amount or a dischargeable amount of the storage battery of the one or more consumers in the second period, based on an estimated value of a remaining amount of the storage battery. An information processing device comprising:

2. The processing unit estimates a connected / disconnected time of the storage battery during the second period based on a history of a connected / disconnected time, which is a time when the storage battery is connected or not connected to be able to be charged or discharged at the consumer facility, and calculates a chargeable amount or a dischargeable amount of the storage battery at the consumer facility based on the estimated value of the connected / disconnected time. The information processing device according to claim 1 .

3. The processing unit acquires information on power demand of the one or more customers in the second period, and calculates a chargeable amount or a dischargeable amount of the storage battery of the customer based on the power demand information. The information processing device according to claim 1 .

4. The processing unit estimates a power demand of the consumer in the second period based on a history of meter values ​​in the consumer in a third period, and calculates a chargeable amount or a dischargeable amount of the storage battery of the consumer based on the estimated power demand. The information processing device according to claim 3 .

5. The processing unit estimates a charge output value and a discharge output value of the storage battery during the second period for each time based on the power demand and the history of charging and discharging of the storage battery, and calculates a chargeable amount or a dischargeable amount of the storage battery of the consumer based on the estimated charge output value and the estimated discharge output value and the estimated power demand. The information processing device according to claim 4.

6. The processing unit calculates a chargeable amount or a dischargeable amount of the storage battery of the consumer based on a preset control regarding a charging and discharging operation of the storage battery. The information processing device according to claim 5 .

7. The processing unit generates a plurality of scenarios including estimated values ​​of remaining amounts of the storage batteries of the plurality of the consumers in the second time period, estimates the possible amount of power adjustment for each of the scenarios, and selects the possible amount of power adjustment from the possible amounts of power adjustment estimated for each of the scenarios. The information processing device according to claim 1 .

8. The processing unit generates a plurality of scenarios including estimated values ​​of remaining capacity of the storage batteries of the plurality of consumers in the second period and estimated values ​​of the connection / disconnection times based on the history of charging and discharging of the storage batteries and the history of the connection / disconnection times, estimates the possible amount of power adjustment for each of the scenarios, and selects the possible amount of power adjustment from the possible amount of power adjustment for each of the scenarios. The information processing device according to claim 2 .

9. The processing unit determines a bid amount for the supply and demand adjustment market for the second time period based on the adjustable amount of power. The information processing device according to claim 1 .

10. The processing unit transmits data indicating the determined bid amount to a supply and demand adjustment market system that processes the supply and demand adjustment market. The information processing device according to claim 9.

11. The processing unit receives as input the number of blocks into which the second period is divided and the price for each of the blocks, estimates the possible power adjustment amount for each block obtained by dividing the second period by the number of blocks, calculates the procurement amount for each of the blocks so as to maximize or quasi-maximize a value obtained by multiplying and summing the unit price for each of the blocks and the procurement amount of power from the multiple consumers for each of the blocks, using the possible power adjustment amount for each of the blocks as a constraint condition, and determines, as a bid amount for the power trading market for each of the blocks, the amount of power obtained by subtracting the procurement amount for each block from the difference between a planned value of power demand for each of the blocks and the power demand estimated for each of the blocks. The information processing device according to claim 4.

12. The processing unit transmits data indicating the determined bid amount for each block to an energy trading market system that processes the energy trading market. The information processing device according to claim 11.

13. The second period is a time period during which demand response is performed. The information processing device according to any one of claims 1 to 12.

14. The processing unit receives command information of the demand response specifying the second period, and controls charging / discharging of the storage battery of the one or more consumers during the second period based on the command information. The information processing device according to claim 13.

15. estimating a remaining capacity of the storage battery in a second period different from the first period based on a charge / discharge history of the storage battery of one or more consumers in the first period; Calculating a power adjustment possible amount, which is a sum of a chargeable amount or a dischargeable amount of the storage battery of the one or more consumers during the second period, based on an estimated value of a remaining capacity of the storage battery. Information processing methods.

16. A step of estimating a remaining capacity of the storage battery in a second period different from the first period based on a charge / discharge history of the storage battery of one or more consumers in the first period; calculating a power adjustment possible amount, which is a sum of a chargeable amount or a dischargeable amount of the storage battery of the one or more consumers during the second period, based on an estimated value of a remaining amount of the storage battery; A computer program for causing a computer to execute the above.

17. One or more consumer storage batteries; estimating a remaining capacity of the storage battery in a second period different from the first period based on a history of charging and discharging of the storage battery in the first period; Calculating a power adjustment possible amount, which is a sum of a chargeable amount or a dischargeable amount of the storage battery of the one or more consumers during the second period, based on an estimated value of a remaining capacity of the storage battery. A processing section; An information processing system comprising:

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