Electric power management system, electric power management method, and program

Abstract

An electric power management system (10) assists a business operator who supplies electric power to a plurality of consumers to execute Demand Response (DR), the electric power management system comprising: an electric power demand monitoring unit (11) that predicts the total electric power demand of the plurality of consumers; a grouping unit (13) that groups the plurality of consumers into one or more groups on the basis of the past DR record of each of the plurality of consumers; and a prediction unit (15) that, on the basis of the result of the prediction performed by the electric power demand monitoring unit (11), the DR record, and the result of the grouping performed by the grouping unit (13), predicts the total electric power demand of the plurality of consumers in each of the one or more groups in cases where the group performs DR.

Description

Power management system, power management method and program

[0001] The present invention relates to a power management system, a power management method, and a program.

[0002] Conventionally, various techniques for reducing electricity usage (e.g., electricity usage during peak hours) have been considered. For example, requesting a demand response (DR) to reduce the amount of electricity supplied by a retail electricity supplier has been considered (see, for example, Patent Document 1).

[0003] JP 2023-150897 A

[0004] However, in the technology of Patent Document 1, DR requests are sent to an unspecified number of people, so that it may not be possible to effectively reduce electricity consumption.

[0005] Therefore, the present invention provides a power management system, a power management method, and a program that can effectively reduce the amount of electricity used.

[0006] One aspect of the present invention provides a power management system that supports a business operator supplying power to multiple consumers in implementing DR (Demand Response), and includes: a power demand monitoring unit that predicts the total power demand of the multiple consumers; a grouping unit that groups the multiple consumers into one or more groups based on the past DR performance of each of the multiple consumers; and a prediction unit that predicts the total power demand of the multiple consumers for each of the one or more groups if the group implements the DR based on the prediction results of the power demand monitoring unit, the DR performance, and the grouping results of the grouping unit.

[0007] A power management method according to one aspect of the present invention is a power management method that assists a business operator that supplies electricity to multiple consumers in implementing DR (Demand Response), and includes predicting the total power demand of the multiple consumers, grouping the multiple consumers into one or more groups based on the past DR performance of each of the multiple consumers, and predicting the total power demand of the multiple consumers for each of the one or more groups if the group implements DR based on the prediction results of the total power demand, the DR performance, and the grouping results.

[0008] A program according to one aspect of the present invention is a program for causing a computer to execute the above-described power management method.

[0009] According to one aspect of the present invention, it is possible to realize a power management system or the like that can effectively reduce the amount of electricity used.

[0010] FIG. 1 is a diagram illustrating a configuration of a power management system according to an embodiment. FIG. 2 is a diagram illustrating an example of an input screen for DR target criteria according to an embodiment. FIG. 3A is a diagram illustrating an example of a first group according to an embodiment. FIG. 3B is a diagram illustrating an example of a second group according to an embodiment. FIG. 4A is a diagram illustrating a predicted result of electricity usage when DR is requested for the first group according to an embodiment. FIG. 4B is a diagram illustrating a predicted result of electricity usage when DR is requested for the first group and the second group according to an embodiment. FIG. 5 is a diagram illustrating an example of a report according to an embodiment. FIG. 6 is a sequence diagram illustrating an example of the operation of a power system including a power management system according to an embodiment. FIG. 7 is a sequence diagram illustrating another example of the operation of a power system including a power management system according to an embodiment.

[0011] (Background to the Invention) Before describing the embodiments of the present invention, the background to the invention will be described.

[0012] A capacity market was established as an electricity trading market in fiscal year 2020. The capacity market is a market where the supply capacity (kW) of electricity that will be needed nationwide in the future is traded. In the capacity market, supply capacity for the next four years is traded in an auction format, and from 2024, electricity retailers (e.g., retail electricity suppliers) will be required to pay capacity contributions.

[0013] The amount of the capacity contribution is calculated based on the value (demand) of each electricity retailer at the time of peak demand in the relevant area for each target month from July to September and December to February. Therefore, in order to reduce the capacity contribution burden rate of the electricity retailer, it is necessary to reduce the value (demand) of the electricity retailer. As a measure to reduce the value (demand) of the electricity retailer, for example, as shown in Patent Document 1, the electricity retailer may request each consumer to adjust the supply and demand of electricity (request DR). Note that the consumer here is a consumer who has an electricity supply contract with the electricity retailer. The consumer may also have a contract under which the electricity retailer has partial or full control of the consumer's energy storage, energy generation, or energy conservation energy resources. The energy resources are energy storage, energy generation, or energy conservation devices owned by consumers who have an electricity sales contract with the electricity retailer. Examples of energy resources that can store energy include, but are not limited to, secondary batteries such as storage batteries, chargers or chargers / dischargers for electric vehicles, and heat pump water heaters (e.g., EcoCute (registered trademark)). The storage battery may be, for example, a home or commercial storage battery, or a storage battery installed in an electric vehicle. Examples of energy resources that can generate energy include, but are not limited to, fuel cells and solar cells. Examples of energy resources that can save energy include, but are not limited to, electrical equipment such as air conditioning equipment and lighting equipment.

[0014] However, when an electricity retailer requests DR for all consumers, it is difficult to predict how much electricity usage will be reduced, and there is a risk that the costs for DR (e.g., the costs paid to consumers who participate in DR) will be too high. It is desirable for an electricity retailer to reduce electricity usage (e.g., to keep electricity usage below a target value) while keeping the costs for DR low. For example, it is desirable for the cost-effectiveness of DR for an electricity retailer to be maximized (e.g., maximized). Note that reducing electricity usage means, for example, reducing electricity usage during peak hours in a day. Note that electricity usage is also referred to as power demand.

[0015] Therefore, the inventors of the present application have conducted extensive research into power management systems etc. that can effectively reduce electricity consumption, and have devised the power management system etc. described below. Specifically, the inventors of the present application have devised a power management system etc. that can effectively reduce electricity consumption while suppressing DR costs by narrowing down the consumers that request DR based on DR performance such as the amount of power reduction.

[0016] Hereinafter, the embodiments will be specifically described with reference to the drawings.

[0017] The embodiments described below are all comprehensive or specific examples. The numerical values, numerical ranges, components, component placement and connection configurations, steps, and step order shown in the following embodiments are merely examples and are not intended to limit the present invention. Furthermore, among the components in the following embodiments, components that are not recited in independent claims are described as optional components.

[0018] Furthermore, each figure is a schematic diagram and is not necessarily an exact illustration. Therefore, for example, the scales of the figures do not necessarily match. Furthermore, in each figure, substantially the same components are given the same reference numerals, and redundant explanations are omitted or simplified.

[0019] Furthermore, in this specification, terms indicating relationships between elements such as "same," as well as numerical values ​​and numerical ranges, are not expressions that only express a strict meaning, but are expressions that also include a substantially equivalent range, for example, a difference of about several percent (or about 10%).

[0020] Furthermore, in this specification, ordinal numbers such as "first" and "second" do not refer to the number or order of components unless otherwise specified, but are used for the purpose of avoiding confusion and distinguishing between components of the same type.

[0021] (Embodiment) Hereinafter, a power system including a power management system according to the present embodiment will be described with reference to Figs.

[0022] [1. Configuration of Power Management System] First, the configuration of a power system including a power management system according to the present embodiment will be described with reference to Figs. 1 to 5. Fig. 1 is a diagram showing the configuration of a power system according to the present embodiment. Note that Fig. 1 shows an exemplary functional configuration of a power system (e.g., power management system 10), and the functional configuration of the power system (e.g., power management system 10) is not limited to that shown in Fig. 1.

[0023] 1 , the power system includes a power management system 10, a first server 20, and a second server 40. The power system may also include employees (users 30) of a retail electricity supplier. The retail electricity supplier is an example of a business that supplies power to multiple consumers.

[0024] The power management system 10 is an information processing system that executes processes to effectively reduce electricity consumption and supports a utility that supplies power to multiple consumers in implementing dynamic redistribution (DR) for the multiple consumers. The power management system 10 includes, as its functional components, a power demand monitoring unit 11, a business goal acquisition unit 12, a grouping unit 13, a status information acquisition unit 14, a prediction unit 15, a report creation unit 16, a control unit 17, a first output unit 18, and a second output unit 19. The power management system 10 also includes, as its hardware components, a non-volatile memory that stores programs, a volatile memory that serves as a temporary storage area for executing the programs, input / output ports, a communication interface, and a processor that executes the programs. The memory may be a read-only memory (ROM) or a random access memory (RAM), and can store programs executed by the processor. Each functional component of the power management system 10 is realized by the processor that executes the programs stored in the memory. The power management system 10 may be realized by a mobile terminal such as a stationary PC (Personal Computer), a smartphone, a tablet, or a dedicated computer, or may be realized by a server (e.g., a cloud server), or may be realized by a combination thereof.

[0025] The power demand monitoring unit 11 is a processing unit that monitors the electricity usage status in the electricity retailer's own area to which the electricity retailer supplies electricity and determines the need for DR in the own area. The power demand monitoring unit 11 predicts the electricity usage of all multiple consumers (for example, the entire company's own area) based on at least one of the local demand in the company's area (electricity usage in the company's own area), the weather in the company's area, and consumer information for each consumer that has a contract with the electricity retailer. It can also be said that the power demand monitoring unit 11 predicts the electricity usage of all multiple consumers if DR is not implemented. Furthermore, the power demand monitoring unit 11 determines whether or not to implement DR based on the predicted power demand.

[0026] The method for predicting electricity usage in the power demand monitoring unit 11 is not particularly limited, and any known method may be used. For example, the power demand monitoring unit 11 may predict electricity usage in the company's area based on past records of at least one of the local demand in the company's area, the weather in the company's area, and consumer information, and the electricity usage at that time, as well as at least one of the local demand in the company's area, the weather in the company's area, and consumer information for a future target date and time or for each target month (e.g., July to September and December to February). The power demand monitoring unit 11 then determines the need for dynamic load balancing based on the predicted electricity usage. The power demand monitoring unit 11 determines the need for dynamic load balancing, for example, by comparing the predicted electricity usage with a preset threshold. For example, the power demand monitoring unit 11 determines the need for dynamic load balancing if the predicted electricity usage exceeds the threshold.

[0027] Furthermore, the power demand monitoring unit 11 may further monitor the electricity usage status of the entire area including the company areas of each of multiple electricity retailers. The entire area is, for example, an area combining the company areas of each of the electricity retailers to which capacity contributions are allocated. In other words, the power demand monitoring unit 11 may predict the demand for the entire area to which the electricity retailer belongs. Furthermore, the power demand monitoring unit 11 may predict the total amount of capacity contributions for the entire area based on the electricity usage status of the entire area. There are no particular limitations on the method for predicting the total amount of capacity contributions based on the electricity usage status, and any known method may be used. Note that the total amount of capacity contributions here may merely be an estimate. The predicted total amount of capacity contributions is notified to the electricity retailer.

[0028] The power demand monitoring unit 11 may be configured to include, for example, a communication interface for acquiring various information used to predict electricity usage, etc. The power demand monitoring unit 11 may be configured to include, for example, a communication circuit (or a communication module).

[0029] The business goal acquisition unit 12 is a communication interface for acquiring information input by a user 30 of the retail electricity supplier, and acquires business goals, etc. The business goals are, for example, but not limited to, target values ​​for business income and expenditure. The business goal acquisition unit 12 may acquire the business goals, etc. directly from the user 30, or may acquire the business goals, etc. via another device. The business goal acquisition unit 12 is, for example, but not limited to, configured to include a communication circuit (or a communication module). The business goal acquisition unit 12 is an example of a first acquisition unit.

[0030] Fig. 2 is a diagram showing an example of an input screen for the DR target criteria according to this embodiment. The input screen shown in Fig. 2 is displayed, for example, on a display unit of an information terminal 50 of an electricity retailer (or an information terminal carried by a user 30). The information terminal 50 includes a display unit such as a display that displays the input screen, and a reception unit such as buttons, a touch panel, or a microphone that receives input from the user 30 in response to the displayed questionnaire. The information terminal 50 may be, for example, a portable terminal device such as a smartphone or a tablet, or a stationary terminal device such as a PC (personal computer).

[0031] As shown in FIG. 2, the DR target criteria include basic information and contract status.

[0032] The basic information includes a business income target and a form for requesting DR. The business income target is a business income target of the retail electricity supplier, and for example, a target amount is input. The business income target is, for example, a monthly business income target value. The business income target can be used, for example, to determine a group for requesting DR.

[0033] The form of making a DR request is information indicating how to communicate the DR request to a consumer, and examples of such information include telephone, email, etc. The form of making a DR request can be used to create a report.

[0034] The contract status includes the number of households currently under contract with the retail electricity supplier (e.g., the number of the above-mentioned multiple consumers). The number of households may be, for example, an upper limit or lower limit of the number of households included in each group.

[0035] The questionnaire may be entered in a multiple-choice format, a free format, or a combination thereof. Instead of or in addition to the questionnaire, the DR target criteria may be obtained through an interview.

[0036] The business goal acquisition unit 12 acquires the input results of the questionnaire shown in FIG.

[0037] The business goal acquisition unit 12 may be configured to include, for example, a communication circuit (or a communication module). Alternatively, the business goal acquisition unit 12 may include a button, a touch panel, a microphone, or the like, and may be configured to directly acquire the DR goal criteria from a user 30 of the retail business operator, or the like.

[0038] The business goal acquisition unit 12 may acquire input results based on information acquired by at least one of the contents entered in a paper questionnaire, voice input, and telephone responses. In other words, the business goal acquisition unit 12 is not limited to acquiring the input results of the questionnaire via the information terminal 50.

[0039] 1 , the grouping unit 13 is a processing unit that groups multiple consumers who have contracts with the electricity retailer into multiple groups based on the past DR performance of each of the consumers. The grouping unit 13 may perform grouping when the power demand monitoring unit 11 determines that DR is to be performed.

[0040] For example, when the DR record includes a probability (also referred to as a DR implementation rate or a DR success rate) that each of the multiple consumers will respond to a DR request (execute DR), the grouping unit 13 may group the multiple consumers into multiple groups based on the DR implementation rate of each of the multiple consumers. Furthermore, when the DR record includes a power reduction amount due to DR for each of the multiple consumers, the grouping unit 13 may group the multiple consumers into multiple groups based on the power reduction amount when DR is implemented for each of the multiple consumers. Furthermore, when the DR record includes date and time information indicating the date and time when each of the multiple consumers participated in DR, the grouping unit 13 may group the multiple consumers into multiple groups based on the date and time information for each of the multiple consumers. For example, the grouping unit 13 may create multiple groups for Monday based on the DR record for that Monday, and create multiple groups for Tuesday based on the DR record for that Tuesday. In other words, the grouping unit 13 may group the multiple consumers into multiple groups for each day of the week based on the DR record for that day. Furthermore, the grouping unit 13 may group a plurality of consumers into a plurality of groups by combining two or more of these.

[0041] Hereinafter, an example will be described in which the grouping unit 13 groups consumers based on the DR implementation rate. Furthermore, when the contract status is acquired by the business goal acquisition unit 12, the grouping unit 13 may set a threshold or a range for the number of consumers to be included in a group based on the contract status. Furthermore, the DR performance may be a performance acquired by making a DR request on a day other than the maximum demand day or the H1 demand day in the area in each month from July to September and December to February, for example.

[0042] 3A and 3B are diagrams showing examples of groups according to this embodiment.

[0043] 3A and 3B show a first group and a second group among the multiple groups grouped by the grouping unit 13. The first group is a group including consumers who are expected to implement DR 100% if a DR request is made, and in the example of FIG. 3A, the first group includes three consumers. The DR implementation rate of the first group is 100%. The second group is a group including consumers who are expected to implement DR 80% if a DR request is made, and in the example of FIG. 3B, the first group includes nine consumers. The second group includes consumers with various DR implementation rates.

[0044] The number of consumers included in each group may be different or the same. The number of groups created by grouping is not particularly limited as long as it is one or more (for example, two or more). Some consumers among the multiple consumers may be grouped in two or more groups. Information indicating which consumers are included in which group is also referred to as grouping information. The grouping unit 13 generates the grouping information.

[0045] Note that, when the recent status information acquiring unit 14 acquires at least the most recent power demand information for each of the multiple consumers, the grouping unit 13 may further group the multiple consumers into multiple groups based on the power demand information. For example, the grouping unit 13 may change the group of the consumers that was grouped based on the DR performance to another group based on the power demand information of the consumers. For example, the grouping unit 13 may correct the DR implementation rate of the consumer based on the consumer's most recent electricity usage included in the consumer information, and change the group to which the consumer belongs based on the corrected DR implementation rate. For example, when the consumer's most recent electricity usage has decreased (e.g., decreased by more than a predetermined amount), the grouping unit 13 may correct the DR implementation rate of the consumer to a lower value in accordance with the amount of decrease in electricity usage, and change the group to which the consumer belongs to to a group determined based on the lowered DR implementation rate. Furthermore, for example, if the consumer's most recent electricity usage has increased (for example, by more than a predetermined amount), the grouping unit 13 may significantly correct the consumer's DR implementation rate in accordance with the increase in electricity usage, and change the group to which the consumer belongs to a group determined based on the significantly corrected DR implementation rate.

[0046] Referring again to FIG. 1 , the current status information acquisition unit 14 acquires consumer information indicating the most recent status of the consumer. The most recent refers to, for example, a range of several days or weeks prior to the day of maximum demand currently occurring in the area in the current month between July and September and December and February, or the day on which DR is scheduled to be implemented. The consumer information also includes, for example, the most recent electricity usage status of the consumer (e.g., electricity usage amount). The current status information acquisition unit 14 acquires information that can predict whether the consumer is away from home (whether the consumer can participate in DR), such as information indicating whether there is an increase or decrease in electricity usage at the consumer. The current status information acquisition unit 14 is an example of a second acquisition unit.

[0047] The prediction unit 15 is a processing unit that predicts the total electricity consumption (power demand) of multiple consumers in each of multiple groups when the group implements DR, based on the prediction result of the power demand monitoring unit 11, the DR record, and the grouping result of the grouping unit 13. It can also be said that the prediction unit 15 predicts the total electricity consumption of multiple consumers when each group grouped by the grouping unit 13 requests DR. The prediction unit 15 predicts the electricity consumption (or the amount of reduction in electricity consumption) of each consumer when the consumer implements DR, based on the DR record. The DR record includes, for example, at least one of the electricity consumption and the amount of reduction in electricity consumption (power reduction) of each of the multiple consumers when DR was implemented in the past. The prediction unit 15 may also predict the total electricity consumption (power demand) of multiple consumers when the group implements DR, based at least on the DR record.

[0048] The prediction unit 15 predicts, for each group, the total electricity consumption of the multiple consumers when DR is requested for the group. The prediction unit 15 may predict the total electricity consumption of the multiple consumers when DR is requested, for example, by using a statistical value of the amount of reduction in electricity consumption when DR was implemented in the past and the electricity consumption predicted by the power demand monitoring unit 11. The prediction unit 15 may predict, for example, a value obtained by subtracting the statistical value of the amount of reduction in electricity consumption when DR was implemented for the group from the electricity consumption predicted by the power demand monitoring unit 11 as the total electricity consumption of the multiple consumers when DR is implemented for the group. The statistical value is an average value, but may also be, for example, a median, a mode, a maximum value, a minimum value, or the like. The amount of reduction in electricity consumption when DR was implemented in the past is included in the DR performance.

[0049] The prediction unit 15 may also predict the total electricity usage of the multiple consumers when DR is requested for two or more groups out of the multiple groups. The prediction unit 15 may also predict the total electricity usage of the multiple consumers when DR is requested based on a business goal. The business goal may include, for example, an upper limit value for the total electricity usage of the multiple consumers. The upper limit value may be set based on the amount of capacity contributions, etc. The prediction unit 15 may predict a group or a combination of two or more groups such that the predicted value of the total electricity usage of the multiple consumers is equal to or less than the upper limit value for electricity usage. It can also be said that the prediction unit 15 selects a group or a combination of two or more groups that satisfies the business goal from the multiple groups.

[0050] FIG. 4A is a diagram showing predicted electricity usage when DR is requested to the first group according to the present embodiment. FIG. 4B is a diagram showing predicted electricity usage when DR is requested to the first and second groups according to the present embodiment. The solid lines in FIGS. 4A and 4B indicate predicted electricity usage when DR is not requested (when no measures are taken), and the dashed-dotted lines indicate electricity usage targets (target values) based on business income and expenditure. The dashed lines in FIG. 4A indicate predicted electricity usage when DR is requested only to the first group (when the first group is implemented), and the two-dot chain lines in FIG. 4B indicate predicted electricity usage when DR is requested to both the first and second groups (when both the first and second groups are implemented). In FIGS. 4A and 4B, the vertical axis indicates electricity usage (predicted electricity usage for all multiple consumers), and the horizontal axis indicates time.

[0051] Figure 4A shows the forecast results for when DR is requested only for the first group, in which case electricity consumption will not be below the target for any time period. In this case, the burden rate of the capacity contribution will increase, which may worsen the business balance of the electricity retailer. Note that the electricity consumption indicated by the dashed line in Figure 4A is calculated by subtracting the total amount of reduction in electricity consumption of each consumer in the first group from the forecasted electricity consumption when DR is not requested.

[0052] 4B shows the predicted results of electricity consumption being below the target for all time periods when DR is requested for both Group 1 and Group 2. In this case, the burden rate of the capacity contribution fee can be reduced, which may improve the business balance of the electricity retailer.

[0053] The prediction unit 15 outputs, for example, information capable of creating the graphs shown in Figures 4A and 4B to the report creation unit 16. It can also be said that the prediction unit 15 outputs prediction results including information based on business goals (information indicated by dashed dotted lines in Figures 4A and 4B).

[0054] 1 again, the report creation unit 16 is a processing unit that creates a report to send the prediction result of the prediction unit 15 to the electricity retailer. The electricity retailer can check the created report and determine to which group to request DR, etc. The number of groups to request DR is not particularly limited, and may be one or more.

[0055] FIG. 5 is a diagram showing an example of a report according to the present embodiment.

[0056] 5, the report created by the report creation unit 16 includes grouping information, a graph showing each amount of electricity usage, comments, and a user list DL. The upper part of FIG. 5 shows an example of how each piece of information is displayed when DR is requested only for the first group, and the lower part shows an example of how each piece of information is displayed when DR is requested for both the first group and the second group. The report is displayed to the user 30 via the information terminal 50.

[0057] The grouping information is generated by the grouping unit 13. The graph is created based on the predicted values ​​predicted by the prediction unit 15. The graph is an example of information that visualizes and displays the prediction results of the prediction unit 15. Visualization means displaying predicted values ​​so that people can intuitively understand the prediction results, and includes, for example, graphing.

[0058] The comment is a comment on the effect of reducing electricity usage, and includes, for example, the percentage of how much electricity usage can be reduced compared to when no measures are taken. This percentage can be calculated from the predicted values ​​of electricity usage when no measures are taken and when DR is requested. Note that no measures are taken means that DR is not requested.

[0059] The user list DL is an icon for downloading a list of contact points for requesting DR to target consumers who are to request DR. When the icon is operated by the user 30, the contact points of the target consumers are downloaded. The contact points include information corresponding to the information indicating the form of requesting DR entered on the DR target criteria input screen. For example, the contact points include a telephone number if the form is a telephone call, and an email address if the form is an email. When the user list DL in the upper row of FIG. 5 is operated, the contact points of the consumers in the first group are downloaded, and when the user list DL in the lower row is operated, the contact points of the consumers in each of the first and second groups are downloaded. The user list DL is an example of information listing one or more consumers included in a group that is a target of DR.

[0060] The user 30 can easily request a DR by checking the report, determining one or more groups for which to request a DR, and operating the user list DL corresponding to the determined one or more groups.

[0061] The graph may be a graph of something other than electricity consumption. For example, it may be a graph in which the vertical axis indicates the cost to be paid to consumers who participate in DR and the horizontal axis indicates time, or a graph in which the vertical axis indicates the predicted amount of capacity contributions to be paid and the horizontal axis indicates time.

[0062] The report creation unit 16 may create a report that includes, for example, at least one of information that visualizes and displays the prediction results of the prediction unit 15, and information that lists one or more consumers included in the group that is the target of DR.

[0063] 1 , the control unit 17 generates control information for the devices owned by each of one or more consumers included in a group that is a target of a DR request, so that the devices execute DR, and transmits the generated control information to the devices of each of the one or more consumers. That is, the control unit 17 automatically controls the devices of each of the one or more consumers. The control unit 17 may automatically control the devices of each of the one or more consumers, for example, when report generation by the report creation unit 16 is not required. The control information is an example of information for causing one or more consumers included in a group that is a target of a DR to execute DR.

[0064] The control unit 17 determines one or more groups to which DR is to be requested based on the prediction result of the prediction unit 15, and transmits control information to the appliances of consumers belonging to the determined one or more groups. Note that the control unit 17 may acquire group determination conditions in advance and determine one or more groups to which DR is to be requested based on the determination conditions. The determination conditions may include whether the electricity retailer prioritizes the amount of reduction in electricity usage or the cost paid to consumers who participate in DR. For example, if the determination conditions include prioritizing the amount of reduction in electricity usage, the control unit 17 may determine one or more groups to which DR is to be requested, the groups with a reduction amount equal to or greater than a predetermined amount or the largest. If the determination conditions include prioritizing the cost paid to consumers who participate in DR, the control unit 17 may determine one or more groups to which DR is to be requested, the groups with a cost equal to or less than a predetermined amount or the lowest.

[0065] The control unit 17 may transmit decision information indicating one or more groups that have been decided to request DR to the information terminal 50. When the report creation unit 16 creates a report, the control unit 17 may output the decision information to the report creation unit 16. In this case, the report creation unit 16 may include the decision information in the report.

[0066] The first output unit 18 is a communication interface that enables the power management system 10 to communicate with the information terminal 50. The first output unit 18 transmits a report to the information terminal 50. The first output unit 18 is configured to include, for example, a communication circuit (or a communication module).

[0067] The second output unit 19 is a communication interface for communication between the power management system 10 and each consumer. The second output unit 19 transmits control information to each consumer. The second output unit 19 includes, for example, a communication circuit (or a communication module).

[0068] The configuration of the power management system 10 is not limited to the above, and may include at least the grouping unit 13 and the prediction unit 15, for example.

[0069] [2. Operation of the Power System] Next, the operation of the power system configured as described above will be described with reference to FIGS. 6 and 7 . FIG. 6 is a sequence diagram illustrating an example of the operation (power management method) of a power system including the power management system 10 according to the present embodiment. In FIG. 6 , a case is described in which the power system includes, in addition to the power management system 10, a power company server 60 and an external server 70. The external server 70 may be a server that manages weather information, or may be a server including, for example, the first server 20 and the second server 40. FIG. 6 illustrates the operation performed on the day of maximum demand occurrence in the area in each of the months of July to September and December to February. On the day of maximum demand occurrence in the area in each of the months of July to September and December to February, the operation performed by the power management system 10 is repeated, for example, six times every four hours (loop 1). Note that, hereinafter, the day of maximum demand occurrence in the area in each of the months of July to September and December to February will also be simply referred to as the day of maximum demand occurrence in the area in that month.

[0070] 6 , the power demand monitoring unit 11 of the power management system 10 acquires data correlated with the demand forecast from the external server 70 (S11). The power demand monitoring unit 11 may, for example, acquire the weather for the entire area on the day to be determined as the day of maximum demand in the area in the current month.

[0071] Next, the power demand monitoring unit 11 acquires the actual value of the amount of electricity used in the entire area from the power company server 60 (S12). The acquired actual value is used to determine whether the day of the month is the day of maximum demand in the area, and therefore may be simplified data. The simplified data may include, for example, the amount of power generated on that day, information on the amount of power used in the company's area, etc.

[0072] Next, the power demand monitoring unit 11 makes a simple determination of the demand in the target area (here, the entire area) based on the data correlated with the demand forecast and the actual values ​​(S13). The power demand monitoring unit 11 predicts the electricity usage for each slot of the day for the entire area based on the data correlated with the demand forecast and the actual values, and determines whether the predicted value of the electricity usage for the day is equal to or greater than the maximum value of the actual value of the electricity usage up to the previous day of the current month. For example, "per slot" means, but is not limited to, every hour. Here, the electricity usage for one day is predicted for each slot.

[0073] The amount of the capacity contribution is determined based mainly on the peak power (kW) in the summer (e.g., July to September) and winter (e.g., December to March) of the previous year. In step S13, it is determined whether a peak time for electricity usage occurs in the entire area in summer or winter on the day.

[0074] Next, if the predicted value is greater than or equal to the maximum actual value, the power demand monitoring unit 11 determines that this is the day of maximum demand in the area for that month (Yes in S14) and proceeds to step S15, and if the predicted value is less than the maximum actual value, it determines that this is not the day of maximum demand in the area for that month (No in S14) and proceeds to step S11.

[0075] Next, if it is the day of maximum demand in the area in the current month, the power demand monitoring unit 11 acquires data correlated with the demand forecast from the external server 70 (S15). The data acquired in step S15 may be the same data as the data acquired in step S11, or additional data may be added. For example, if the consumer has a power generation facility, the added data may be power generation amount data of the power generation facility, but is not limited to this.

[0076] Next, the power demand monitoring unit 11 acquires actual values ​​of electricity usage from the power company server 60 (S16). The acquired actual values ​​are used to predict the electricity usage in the retail electricity supplier's own area on the day of maximum demand in the current month, and therefore may be detailed data. The detailed data may include, for example, data with a larger amount of data than the simplified data. The detailed data may include, for example, information indicating the amount of power generated on the day, the amount of power consumed by each company or household in the retail electricity supplier's own area, etc. Furthermore, the detailed data may have a shorter data acquisition interval (sampling time) than the simplified data.

[0077] Based on the information acquired in steps S15 and S16, the power demand monitoring unit 11 predicts the demand (power demand) for the entire retail target area (the company's area) for each slot on the target day (S17). The power demand monitoring unit 11 predicts the demand (electricity usage) for the entire retail target area. For example, each slot means, but is not limited to, every hour. Here, the electricity usage for one day is predicted for each slot.

[0078] The power demand monitoring unit 11 may determine the necessity of DR on the day of maximum demand in the area of ​​each month based on the demand predicted in step S17 and a threshold value. For example, if the demand is equal to or greater than the threshold value, the power demand monitoring unit 11 may determine that DR is necessary and execute the processing from step S18 onwards, and if the demand is less than the threshold value, the power demand monitoring unit 11 may determine that DR is not necessary and end the processing.

[0079] Next, the prediction unit 15 predicts the controllable amount (reduction in electricity usage) of the target consumer for each slot on the target day (S18). The target consumer is a consumer who has a contract with the electricity retailer. The prediction unit 15 predicts the controllable amount of energy resources of each consumer who has a contract with the electricity retailer based on the contract details, the current state of energy resources (e.g., the charge amount and available capacity of a storage battery), etc. The controllable amount includes the discharge amount, charge amount, etc.

[0080] Next, the prediction unit 15 acquires user information including the past DR implementation rate and the like from the external server 70 (S19). The prediction unit 15 acquires the user information of each consumer.

[0081] Next, the grouping unit 13 groups the consumers into a plurality of groups based on the user information, and the prediction unit 15 calculates the controllable amount for each group based on the controllable amount of each consumer and the grouping information (S20). The prediction unit 15 may calculate the controllable amount of the group by adding up the controllable amounts of one or more consumers belonging to the group. Note that the method of calculating the controllable amount of the group is not limited to this.

[0082] Loop 2 continues until the controllable amount of each group is calculated (a predetermined condition is met).

[0083] Next, the report creation unit 16 creates a report of the simulation results after DR is completed (S21). The report creation unit 16 calculates the amount of electricity usage (e.g., the amount of reduction) when DR is requested for each group based on the controllable amount calculated in step S20, graphs the calculated amount of electricity usage, and creates a report including the graphed information.

[0084] Next, the report creation unit 16 sends an alert report including the report to the electric power company server 60 via the first output unit 18 (S22). In this way, when a day of maximum demand occurs in the area in each month and DR needs to be performed, an alert report is sent.

[0085] When the power company server 60 acquires the alert report (S23), it presents the alert report to the user 30, accepts a selection of a group for which a DR request is to be made from the user 30, and sends a DR request notice requesting DR to the selected consumer (S24). This may enable the amount of electricity usage to be reduced by a desired amount.

[0086] 6 illustrates an example in which the DR request notice is sent from the electric power company server 60, but the DR request notice may be sent from, for example, the control unit 17 of the energy management system 10. The control unit 17 may notify one or more consumers included in a group that is a target of the DR that the DR will be executed.

[0087] In step S24, control information may be transmitted to the consumer device together with the DR request notice or instead of the DR request notice.

[0088] FIG. 7 is a sequence diagram illustrating another example of the operation (power management method) of a power system including the power management system 10 according to the present embodiment. FIG. 7 illustrates the operation of performing normal DR on days other than the days when maximum demand occurs in the area in each of the months of July through September and December through February. In normal DR, the operation performed by the power management system 10 is performed, for example, once per day (loop 1). Note that FIG. 7 focuses on the differences from FIG. 6 , and explanations of processes that are the same as or similar to those in FIG. 6 are omitted or simplified. For example, steps S20 and S21 are not illustrated in FIG. 7 . Furthermore, in FIG. 7 , the power demand monitoring unit 11 executes step S13, which allows the necessity of DR to be determined in advance, thereby reducing the man-hours required for implementing DR.

[0089] 7, after step S13, the power demand monitoring unit 11 determines the demand in the target area (here, the company's own area) based on data correlated with the demand forecast and actual values, and determines whether DR is necessary (S101). The power demand monitoring unit 11 determines whether DR is necessary based on the electricity usage in the company's own area and a threshold. If the power demand monitoring unit 11 determines that DR is necessary, the process proceeds to step S15, and if it determines that DR is not necessary, the process proceeds to step S11.

[0090] Next, the report creation unit 16 sends an alert report including the electricity usage prediction result by the prediction unit 15 to the electric power company server 60 (S22). In this way, when DR needs to be performed, an alert report is sent.

[0091] When the power company server 60 acquires the alert report (S23), it presents the alert report to the user 30, accepts from the user 30 the selection of a group for which DR is to be requested, and sends a DR request notification to the selected consumer (S102).

[0092] Next, the electric power company server 60 monitors the DR implementation results and sends DR implementation record data to the power management system 10 (S103). The electric power company server 60 sends to the power management system 10, as DR implementation record data, information such as whether or not the consumer who requested DR implemented DR, and the amount of reduction in electricity usage if DR was implemented.

[0093] Next, when the power management system 10 acquires the DR implementation record data as the DR record (S104), it stores the acquired DR implementation record data in a storage unit (not shown) (S105). It can also be said that the power management system 10 updates the DR record. The DR implementation record data is used by the grouping unit 13 when performing grouping the next DR implementation.

[0094] Next, the power management system 10 transmits user information including the DR implementation rate of each consumer updated based on the DR implementation record data acquired in step S104 to the external server 70, and the external server 70 acquires the updated user information (S106). The updated user information is managed in the external server 70. The updated user information is used the next time the controllable amount is calculated.

[0095] (Effects, etc.) The invention derived from the disclosure of this specification and the effects, etc. obtained by the invention will be described below.

[0096] (Technology 1) A power management system that supports a business operator that supplies power to a plurality of consumers in implementing DR (Demand Response), the power management system comprising: a power demand monitoring unit that predicts the total power demand of the plurality of consumers; a grouping unit that groups the plurality of consumers into one or more groups based on past DR performance of each of the plurality of consumers; and a prediction unit that predicts the total power demand of the plurality of consumers for each of the one or more groups if the group implements the DR, based on the prediction result of the power demand monitoring unit, the DR performance, and the grouping result of the grouping unit.

[0097] This makes it possible to determine which of the multiple groups to request DR from, based on the power demand when each of the multiple groups implements DR. For example, the cost of implementing DR can be reduced compared to when DR is requested of all consumers, thereby improving cost-effectiveness. Therefore, electricity consumption can be effectively reduced.

[0098] (Technology 2) The power management system of Technology 1 further includes a first acquisition unit that acquires a business goal of the business operator, and the prediction unit outputs a prediction result including information based on the business goal.

[0099] This allows information based on business goals to be output, making it possible to grasp, for example, the required amount of DR. The required amount of DR is important information for selecting a group to request DR from multiple groups. Therefore, DR can be requested from a group according to the required amount of DR, thereby enabling more effective reduction of electricity consumption.

[0100] (Technology 3) The power management system according to Technology 2, wherein the prediction unit predicts a combination of one or more groups that satisfies the business objective from among the one or more groups.

[0101] This makes it possible to predict groups that will be able to achieve business goals with greater certainty, thereby enabling more reliable reductions in electricity usage.

[0102] (Technology 4) The power management system according to any one of Technologies 1 to 3, further comprising a report creation unit that creates a report including at least one of information that visualizes and displays the prediction results of the prediction unit and information that lists one or more consumers included in the group that is the target of the DR.

[0103] This makes it possible to visualize the prediction results, improving their visibility, and effectively assisting users in selecting a group for DR. In addition, displaying the list of information allows users to efficiently request DR.

[0104] (Technology 5) The power management system according to any one of Technologies 1 to 4, further comprising a control unit that outputs information for causing one or more consumers included in the group that is a target of the DR to execute the DR.

[0105] This allows information for executing DR to be output, thereby supporting the execution of DR.

[0106] (Technology 6) The power management system according to Technology 5, wherein the control unit notifies the one or more consumers included in the group that is a target of the DR that the DR will be executed.

[0107] This allows the consumer to be notified that DR will be executed.

[0108] (Technology 7) The power management system according to Technology 5 or 6, wherein the control unit outputs control information for executing the DR to devices owned by each of the one or more consumers included in the group that is the target of the DR.

[0109] This allows DR to be performed automatically, thereby reducing the business burden on the operator.

[0110] (Technology 8) The power management system of any of Technologies 1 to 7 further includes a second acquisition unit that acquires at least the most recent power demand information for each of the plurality of consumers, and the grouping unit further groups the plurality of consumers into the one or more groups based on the power demand information.

[0111] As a result, grouping is performed using the most recent power demand information (i.e., the latest power demand information), so more appropriate grouping can be performed than when the power demand information is not used, which leads to an effective reduction in electricity consumption.

[0112] (Technology 9) The power management system according to Technology 8, wherein the grouping unit changes the group of the consumers grouped based on the DR performance, based on the power demand information of the consumers.

[0113] This allows the group to which the consumers belong to to be changed (reorganized) into a group that corresponds to the most recent power demand information. In other words, appropriate grouping can be performed according to the most recent power demand information. This leads to an effective reduction in electricity consumption.

[0114] (Technology 10) The power management system according to any one of Technologies 1 to 9, wherein the DR performance includes a DR implementation rate for each of the plurality of consumers, and the grouping unit groups the plurality of consumers into the one or more groups based on the DR implementation rate for each of the plurality of consumers.

[0115] This makes it possible to narrow down the group (i.e., consumers) that requests DR according to the DR implementation rate. This leads to an effective reduction in electricity consumption. It also clarifies the consumers that request DR.

[0116] (Technology 11) A power management system according to any one of technologies 1 to 10, wherein the DR performance includes the amount of power reduction due to DR for each of the plurality of consumers, and the grouping unit groups the plurality of consumers into the one or more groups based on the amount of power reduction due to DR for each of the plurality of consumers.

[0117] This allows the group (i.e., consumers) requesting DR to be narrowed down based on the amount of power reduction, which leads to an effective reduction in electricity consumption. It also clarifies the consumers who should request DR.

[0118] (Technology 12) The power management system according to any one of Technologies 1 to 11, wherein the DR performance includes date and time information indicating the date and time when each of the plurality of consumers participated in the DR, and the grouping unit groups the plurality of consumers into the one or more groups based on the date and time information of each of the plurality of consumers.

[0119] This allows the group (i.e., consumers) requesting DR to be narrowed down based on the date and time of participation in DR. This leads to an effective reduction in electricity consumption. It also clarifies the consumers who should request DR.

[0120] (Technology 13) A power management system according to any one of technologies 1 to 12, wherein the power demand monitoring unit determines whether or not to perform dynamic rebalancing based on the predicted power demand, and the grouping unit performs grouping when the power demand monitoring unit determines that dynamic rebalancing should be performed.

[0121] This clarifies the need for DR. In addition, since grouping is performed when DR is implemented, grouping can be performed taking into account the most recent electricity usage status, etc., compared to when grouping is performed in advance. For example, appropriate grouping can be performed. This leads to an effective reduction in electricity usage.

[0122] (Technology 14) The power management system according to Technology 3, wherein the power demand monitoring unit further predicts the demand for the entire area to which the business operator belongs.

[0123] This makes it possible to predict the total amount of capacity contributions for the entire area.

[0124] (Technology 15) A power management system according to any one of technologies 1 to 14, wherein the power demand monitoring unit determines whether or not to perform dynamic rebalancing based on the predicted power demand, and the prediction result of the power demand monitoring unit includes a determination result of whether or not to perform dynamic rebalancing.

[0125] This allows the prediction unit to predict the total power demand of multiple consumers using the determination result of whether or not to perform DR.

[0126] (Technology 16) A power management method that supports a business operator that supplies power to a plurality of consumers in implementing DR (Demand Response), the power management method comprising: predicting the total power demand of the plurality of consumers; grouping the plurality of consumers into one or more groups based on past DR performance of each of the plurality of consumers; and predicting the total power demand of the plurality of consumers in each of the one or more groups when the group implements the DR based on the prediction result of the total power demand, the DR performance, and the grouping result.

[0127] This provides the same effects as the above-mentioned power management system.

[0128] (Technology 17) A program for causing a computer to execute the power management method described in Technology 16.

[0129] This provides the same effects as the above-mentioned power management system.

[0130] These general or specific aspects may be realized as a system, a method, an integrated circuit, a computer program, or a non-transitory recording medium such as a computer-readable CD-ROM, or as any combination of the system, method, integrated circuit, computer program, or recording medium. The program may be pre-stored in the recording medium, or may be supplied to the recording medium via a wide area communication network including the Internet.

[0131] While the power management system according to one or more aspects has been described above based on the embodiments, the present invention is not limited to these embodiments. As long as the modifications do not deviate from the spirit of the present invention, modifications that a person skilled in the art may make to the present embodiments, or modifications that are constructed by combining components of different embodiments, may also be included in the present invention.

[0132] For example, the business operator supplying electricity to multiple consumers in the above embodiment is not limited to being a retail electricity supplier, but may be, for example, an electric power company or a specified wholesale supplier (so-called aggregator).

[0133] Furthermore, for example, the power demand monitoring unit 11 in the above embodiment may be capable of outputting at least one of the electricity usage in the region to which the electricity retailer belongs (electricity usage in the entire area) and the electricity usage of the electricity retailer's consumers. The power demand monitoring unit 11 may calculate and output the electricity usage in the region based on the demand within the region. The power demand monitoring unit 11 may also calculate and output the electricity usage of the electricity retailer's consumers based on the electricity usage of the electricity retailer's consumers, contract information, etc. The contract information may include the family structure, the age and occupation of the head of household, etc. The power demand monitoring unit 11 may also determine the need for DR, etc., using a machine learning model such as a random forest or an SVM (support vector machine), or a machine learning model generated by deep learning. Such a machine learning model is trained to output a predicted value of the need for DR or the electricity usage in the entire area or the company's own area using at least one of data correlated with demand forecasting, actual values, electricity usage in the region, contract information, etc. as input data.

[0134] Furthermore, for example, the grouping unit 13 in the above embodiment may perform grouping using a clustering method such as k-means, DBSCAN (Density-Based Spatial Clustering of Applications with Noise), or hierarchical clustering. Furthermore, the grouping unit 13 may group multiple consumers in increments of a predetermined percentage (for example, 10%) of DR implementation rate, or may group consumers based on a combination of multiple parameters such as the DR implementation rate and the day of the week, or may group each consumer into one group. When each consumer is grouped into one group, there are as many groups as there are consumers. In this case, the grouping unit 13 may, for example, rank all consumers by DR implementation rate and group consumers as those who will implement DR.

[0135] Furthermore, in the above embodiment, the timing for grouping is described as being when it is determined that DR is necessary or on the day when maximum demand occurs in the area in each month from July to September and from December to February, but this is not limited to this, and grouping may be performed at any other timing, for example.

[0136] In the above embodiments, each component may be configured with dedicated hardware, or may be realized by executing a software program suitable for each component. Each component may be realized by a program execution unit such as a CPU or processor reading and executing a software program recorded on a recording medium such as a hard disk or semiconductor memory.

[0137] The order in which the steps in the flowchart are executed is merely an example for specifically explaining the present invention, and other orders may be used. Some of the steps may be executed simultaneously (in parallel) with other steps, or some of the steps may not be executed.

[0138] The division of functional blocks in the block diagram is an example, and multiple functional blocks may be realized as a single functional block, one functional block may be divided into multiple blocks, or some functions may be moved to another functional block.Furthermore, the functions of multiple functional blocks having similar functions may be processed in parallel or in time-sharing by a single piece of hardware or software.

[0139] Furthermore, the power management system according to the above embodiment may be realized as a single device or may be realized by multiple devices. When the power management system is realized by multiple devices, the components of the power management system may be allocated in any manner among the multiple devices. When the power management system is realized by multiple devices, the communication method between the multiple devices is not particularly limited, and may be wireless communication or wired communication. Furthermore, wireless communication and wired communication may be combined between the devices.

[0140] Furthermore, each component described in the above embodiments may be implemented as software or, typically, as an LSI, which is an integrated circuit. These components may be individually integrated into a single chip, or some or all of them may be integrated into a single chip. Here, the term "LSI" is used, but depending on the level of integration, it may also be referred to as an IC, system LSI, super LSI, or ultra LSI. Furthermore, the integrated circuit implementation method is not limited to LSI, and may be implemented using a dedicated circuit (a general-purpose circuit that executes a dedicated program) or a general-purpose processor. After LSI fabrication, a field programmable gate array (FPGA) that can be programmed or a reconfigurable processor that can reconfigure the connections or settings of circuit cells within the LSI may also be used. Furthermore, if an integrated circuit technology that replaces LSI emerges due to advances in semiconductor technology or a derivative technology, that technology may naturally be used to integrate the components.

[0141] A system LSI is an ultra-multifunctional LSI manufactured by integrating multiple processing units on a single chip, and is specifically a computer system comprising a microprocessor, ROM, RAM, etc. The ROM stores computer programs. The system LSI achieves its functions when the microprocessor operates in accordance with the computer programs.

[0142] Another aspect of the present invention may be a computer program that causes a computer to execute each of the characteristic steps included in the power management method shown in either FIG. 6 or FIG.

[0143] Furthermore, for example, the program may be a program to be executed by a computer. Another aspect of the present invention may be a computer-readable non-transitory recording medium on which such a program is recorded. For example, such a program may be recorded on a recording medium and distributed or circulated. For example, the distributed program may be installed in a device having another processor, and the program may be executed by the processor, thereby causing the device to perform each of the above processes.

[0144] REFERENCE SIGNS LIST 10 Power management system 11 Power demand monitoring unit 12 Business target acquisition unit (first acquisition unit) 13 Grouping unit 14 Current status information acquisition unit (second acquisition unit) 15 Prediction unit 16 Report creation unit 17 Control unit

Claims

A power management system that supports a business operator that supplies power to a plurality of consumers to perform DR (Demand Response), an electric power demand monitoring unit that predicts the total electric power demand of the plurality of consumers; a grouping unit that groups the plurality of consumers into one or more groups based on past DR performance of each of the plurality of consumers; a prediction unit that predicts the total amount of power demand of the plurality of consumers in each of the one or more groups when the group performs the dynamic range reduction, based on the prediction result of the power demand monitoring unit, the dynamic range reduction record, and the grouping result of the grouping unit, Power management system. 　 Further, a first acquisition unit that acquires a business goal of the business operator is provided, the prediction unit outputs a prediction result including information based on the business goal. The power management system of claim 1 . 　 the prediction unit predicts a combination of one or more groups that will satisfy the business goal among the one or more groups. The power management system of claim 2 . 　 Further, a report creation unit is provided that creates a report including at least one of information that visualizes and displays the prediction result of the prediction unit and information that lists one or more consumers included in the group that is a target of the DR. The power management system according to any one of claims 1 to 3. 　 Further, a control unit is provided that outputs information for causing one or more consumers included in the group that is a target of the DR to execute the DR. The power management system according to any one of claims 1 to 3. 　 The control unit notifies the one or more consumers included in the group that is a target of the DR that the DR will be executed. The power management system of claim 5 . 　 the control unit outputs control information for executing the DR to devices owned by each of the one or more consumers included in the group that is a target of the DR. The power management system of claim 5 . 　 Further, a second acquisition unit that acquires at least the most recent power demand information of each of the plurality of consumers, The grouping unit further groups the plurality of consumers into the one or more groups based on the power demand information. The power management system according to any one of claims 1 to 3. 　 the grouping unit changes the group of the consumers grouped based on the DR performance, based on the power demand information of the consumers. The power management system of claim 8 . 　 The DR performance includes a DR implementation rate for each of the plurality of consumers, The grouping unit groups the plurality of consumers into the one or more groups based on the DR implementation rate of each of the plurality of consumers. The power management system according to any one of claims 1 to 3. 　 The DR performance includes an amount of power reduction due to DR for each of the plurality of consumers, The grouping unit groups the plurality of consumers into the one or more groups based on an amount of power reduction by the DR for each of the plurality of consumers. The power management system according to any one of claims 1 to 3. 　 The DR performance includes date and time information indicating a date and time when each of the plurality of consumers participated in the DR, The grouping unit groups the plurality of consumers into the one or more groups based on the date and time information of each of the plurality of consumers. The power management system according to any one of claims 1 to 3. 　 the power demand monitoring unit determines whether to perform DR based on the predicted power demand; The grouping unit performs grouping when the power demand monitoring unit determines that DR should be performed. The power management system according to any one of claims 1 to 3. 　 The power demand monitoring unit further predicts the demand for the entire area to which the business operator belongs. The power management system of claim 13 . 　 the power demand monitoring unit determines whether to perform DR based on the predicted power demand; The prediction result of the power demand monitoring unit includes a determination result of whether or not to perform DR. The power management system according to any one of claims 1 to 3. 　 A power management method for supporting a business operator that supplies power to a plurality of consumers to perform a demand response (DR), comprising: predicting the total amount of power demand of the plurality of consumers; Grouping the plurality of consumers into one or more groups based on past DR performance of each of the plurality of consumers; predicting, for each of the one or more groups, the total power demand of the plurality of consumers in a case where the group performs the DR, based on the prediction result of the total power demand, the DR performance, and the grouping result; Power management methods. 　 A program for causing a computer to execute the power management method according to claim 16.

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