GB2578369A - Information processing device, method therefor and computer program - Google Patents

Abstract

An information processing device includes a processor, a schedule creator and a communicator. The processor selects a plurality of target consumers 301 to which a power reduction request is made based on power reduction histories of consumers and predicts reduction power amounts of the plurality of target consumers in response to the request. The schedule creator 101 creates a discharging schedule of a storage battery 1 possessed by at least one of the plurality of target consumers 301 based on a difference between a reduction target amount of the first power reduction request and a sum of the reduction power amounts predicted for the plurality of target consumers. A communicator transmits the first power reduction request to consumer systems of the target consumers, and transmits the discharging schedule to a storage battery system 311 including the storage battery.

Description

INFORMATION PROCESSING DEVICE, METHOD THEREFOR AND COMPUTER PROGRAM

FIELD

The present disclosure relates to an information processing device, a method therefor and a computer program.

BACKGROUND

Demand response (power reduction) is proposed to 10 stabilize power by promoting restraining of power usage and suppressing power consumption during peak usage.

In a negawatt aggregation business, an aggregate provider (aggregator) collects negawatt (negawatt power) from consumers using a method such as setting price and paying price to consumers who restrain usage during peak usage. "Negawatt" refers to a reduction (negative power) in a power demand in comparison with normal power demand (positive power). Power consumption can be reduced by collecting negawatt from consumers.

Under the current system, the aggregator concludes a contract about an amount of power reduction in advance with a power grid operator, a retail electricity provider, a parent aggregator or the like (these are generically referred to as "grid operators" hereinafter). The aggregator acquires a reward for success if the aggregator achieves the contract reduction amount. The aggregator can select consumers to whom a demand response request (DR request) which is a request for power reduction is made based on a request from the grid operator and make the demand response request for the selected consumers.

The aggregator can achieve the contract power reduction as a total amount of power reduction by the selected consumers. However, when the reduction amount by the consumers fluctuates from the estimated amount, a risk of failure of the aggregator may increase. In the case of a fast DR where time from a DR request to DR request is short, it is highly possible that consumers may not be able to react in time in a first time period of the DR request period.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a schematic configuration of a 5 demand response system according to a first approach; FIG. 2 is a functional block diagram of a demand response scheduling device; FIG. 3 is a diagram illustrating examples of reduction target information; FIG. 4 is a diagram illustrating examples of reduction histories of consumers; FIG. 5 is a diagram illustrating examples of storage battery information; FIG. 6 is a diagram illustrating examples of reduction 15 scenarios; FIG. 7 is a diagram describing examples of creation of discharging schedule and success or failure in execution of scenario; FIG. 8 is an explanatory diagram of specific examples of the first approach; FIG. 9 is a diagram illustrating an example of output information identifying consumers selected by a DR scheduling device; FIG. 10 is a hardware block diagram of a demand response scheduling device according to the first approach; FIG. 11 is a flowchart of operation according to the first approach; FIG. 12 is a diagram illustrating specific examples of scenario source data according to a second approach; FIG. 13 is a diagram illustrating specific examples of scenarios by consumers selected in a third approach; and FIG. 14 is a diagram illustrating specific examples of scenarios by consumers selected in a fourth approach.

DETAILED DESCRIPTION

According to one approach, an information processing device includes a processor, a schedule creator and a communicator. The processor selects a plurality of target consumers to which a first power reduction request is made among the plurality of consumers based on power reduction histories of the plurality of consumers in response to a power reduction request; and predicts reduction power amounts of the plurality of target consumers in response to the first power reduction request. The schedule creator creates a discharging schedule of a storage battery possessed by at least one of the plurality of target consumers based on a difference between a reduction target amount of the first power reduction request and a sum of the reduction power amounts predicted for the plurality of target consumers. The communicator transmits the first power reduction request to consumer systems of the plurality of target consumers, and transmits the discharging schedule to a storage battery system including the storage battery.

Hereinafter, approaches of the present invention will be described with reference to the accompanying drawings.

FIG. 1 is a block diagram of a schematic configuration of a demand response system (DR system) according to an approach of the present invention. The DR system according to the present approach includes a demand response scheduling device (DR scheduling device) 101 which is an information processing device according to the present approach, a grid operator system 201 and a consumer system 301 operated by each of a plurality of consumers. All or some of the plurality of consumers each possess a storage battery system 311. The consumer system 301 includes a communication device that communicates information with the DR scheduling device 101. The consumer system 301 of each consumer who possesses a storage battery includes the storage battery system 311. The storage battery system 311 includes a storage battery (secondary battery) 1, a control device 2 that control charge/discharge of the storage battery and a communication device 3 that communicates with the DR scheduling device 101. The DR scheduling device 101 and the grid operator system 201, and the DR scheduling device 101 and the consumer system 301 are respectively connected via a communication medium. The communication medium may be a wide area network such as an Internet channel or a dedicated channel. The communication medium need not always be a 5 communication network, but may be different communication means such as a telephone channel. The communication device and the storage battery system 311 provided for each consumer system 301 may communicate with the DR scheduling device 101 via different communication media or communicate with the DR 10 scheduling device 101 via the same communication medium.

The grid operator system 201 is a system possessed by a grid operator (e.g., power company) and issues a DR request which is a power reduction request to an aggregator. The DR scheduling device 101 is a system possessed by the aggregator and creates a DR schedule according to the DR request. The DR scheduling device 101 requests consumers to reduce power according to the created DR schedule. The DR scheduling device 101 can control at least one of charging and discharging of the storage battery 1 in each consumer via communication with the storage battery system 311 as part of execution of the DR schedule. In the present approach, it is assumed that discharging can be controlled, but both charging and discharging or only charging can be controlled.

FIG. 2 is a functional block diagram of the DR scheduling device 101 which is an information processing device according to the present approach. It is one of features of the DR scheduling device 101 to create a DR schedule to request consumers selected from among a plurality of consumers to reduce demand power based on the DR request from the grid operator and create a discharging schedule of the storage battery 1 so that a success rate of the DR schedule is made higher as much as possible.

The DR scheduling device 101 includes a DR schedule optimizer 20, a communicator 30, an input/output I/F 27, a scenario creator 21, an operation input device 28, a displayer 29, a consumer reduction history DB 40, a reduction scenario DB 41, a reduction target amount DB_42, a schedule creation parameter DB_43, a storage battery information DB_44, a charging/discharging schedule DB_45 and a DR requested consumer combination DB_46. The communicator 30 includes an information communicator 25 and a storage battery controller 26. The scenario creator 21 includes a consumer combination creator 22. The DR schedule optimizer 20 includes a charging/discharging schedule creator 23 and a processor 24.

The information communicator 25 performs communication with the grid operator system 201 and the consumer system 301 via the aforementioned communication medium. The consumer system 301 is a system for consumers to receive information from the DR scheduling device 101 (aggregator) or send information to the aggregator. The consumer system 301 may be a mobile terminal such as a smartphone, a dedicated device for communicating with the DR scheduling device 101, a general personal computer or a telephone. One example of the information reported to the consumers by the DR scheduling device 101 is a DR request to be transmitted to the consumers selected in the present approach.

The information also includes a request for transmission of a power consumption history in each consumer's household, a request for transmission of consumer information or the like. An example of information to be transmitted by each consumer to the DR scheduling device 101 is information transmitted according to a request of the DR scheduling device 101. The information transmitted/received between the DR scheduling device 101 and the consumer system 301 is not limited to these kinds of information.

The operation input device 28 is intended for an operator of the aggregator to input various kinds of operation or data.

Examples of the operation input device 28 include a keyboard, a mouse, a touch panel or a mobile terminal such as a smartphone. The display 29 is a display device to display various kinds of information. Examples of the display device include a liquid crystal display device, an organic EL display device or a CRT display device.

The input/output I/F 27 is connected to the operation input device 28 and the display 29, and performs interface operation of input/output. The operation input device 28 may be connected to the display 29 by wired or wireless means.

The reduction target amount DB_42 stores information relating to a power reduction target amount (reduction target information) based on a contract between the aggregator and the grid operator.

FIG. 3 illustrates examples of the reduction target information stored in the reduction target amount DB_42. The reduction target information is defined based on the contract between the system operator and the aggregator in units of, for example, a one-year contract. A specific example of such a contract can be "power reduction by a reduction target amount or more is requested assuming that a maximum duration is 8 hours in an arbitrary time period of 8:00-17:00". The grid operator issues a DR request based on this contract. The issued DR request includes a DR request specification period (DR request period) and reduction target information in each time period (slot) of the above period. The reduction target amount DB_42 stores the reduction target information included in the DR request in association with the specified period of the DR request (DR implementation period) therein. However, when the reduction target amount value is predetermined, only information on the DR request period may be included in the DR request and the reduction target amount value need not be included. Furthermore, when the DR request period is predetermined, the information on the DR request period need not be included in the DR request.

The reduction target information in FIG. 3 requests that power be reduced by 20 kWh for all consumers in all 30-minute periods (corresponding to 4 slots) of 13:00-15:00 as a specified period (description of the specified period is omitted). It is a target for the aggregator to reduce power by 20 kWh for each slot.

The grid operator system 201 transmits the DR request to the DR scheduling device 101 at a predetermined point in time or at an arbitrarily determined point in time (e.g., a certain time before the DR period), as an example. For example, at a point in time of 12:45, it is requested that power be reduced by a power amount defined in the contract (e.g., 20 kWh) in all 30-minute periods (corresponding to 4 slots) of 13:00-15:00.

A success condition based on this reduction target amount are defined in the contract between the aggregator and the grid operator. The grid operator may give some kind of incentive to the aggregator when the success condition is met or the grid operator may impose some kind of penalty on the aggregator when the success condition is not met. Information on the success condition may be stored in the reduction target amount DB_42. Alternatively, the information on the success condition may be described in program code that implements operation of the present approach.

As a first example of the success condition, the total power reduction amount of consumers selected as the DR request targets may be a reduction target amount or more for each of all the slots.

As a second example of the success condition, the total of power reduction amounts of consumers selected as the DR request targets may fall within a predetermined target range for each of all the slots. An example of the predetermined target range is 90% or more and 110°M or less of the reduction target amount for each of all the slots.

However, examples of the success condition are not limited to the above-described ones.

Although the success conditions in the above-described first and second examples request that the condition (the first condition or the second condition) be met in all the slots, partial success may also be determined when the condition is met in some of the slots. In the case of partial success, the penalty may be reduced.

The actual power reduction amount in a slot is calculated as 35 an example, based on a difference between baseline power defined for each slot and total received power (power consumption) of consumers to whom DR is requested. A variety of techniques are known as methods of calculating baseline power such as a High 4 of 5 (with adjustment on the day) method, a High 4 of 5 (without adjustment on the day) method, an equivalent day employing method or a pre-measuring method, but the baseline power can be calculated using any technique. The information communicator 25 may receive information on the power consumption of the consumers to whom DR is requested from a smart meter possessed by the consumers, for example or the information communicator 25 may receive the information from a server that manages power consumption of the consumers. Alternatively, the grid operator system 201, instead of the DR scheduling device 101, may receive information on power consumption of the consumers to whom DR is requested. A success or failure of the DR request may be determined by the DR scheduling device 101 or the grid operator system 201. When the storage battery 1 of each consumer discharges, the measured power reduction amount also includes a discharge amount from the storage battery 1.

The consumer reduction history DB_40 stores information on a power reduction history of each consumer in response to a past DR request (power reduction request).

FIG. 4 illustrates examples of power reduction histories of respective consumers stored in the consumer reduction history DB_40. The information in FIG. 4 includes power reduction results of respective consumers A, B and C at the past DR requests. Here, the number of consumers is 3, but the number of consumers may be 4 or more or 2. The day on which a DR request is made varies from one consumer to another. Power reduction results of 4 slots are illustrated for each day on which a DR request is made about each consumer.

For example, there are DR requests on 8/1 13:00-15:00, 8/3 13:00-15:00 and 8/5 13:00-15:00 for consumer A (consumer whose consumer ID is A), and power reduction results in slots 1 to 4 are shown. It is indicated that there are power reduction results, for example, of 8 kWh in slot 1 (13:00-13:30) on 8/1, 10 kWh in slot 2 (13:30-14:00), 11 kWh in slot 3 (14:00-14:30) and 10 kWh in slot 4 (14:30-15:00). The reduction result of each consumer on each day is assigned an individual history ID to distinguish the history on each day. The history data on each day includes a consumer ID, a DR request period, an individual history ID and a reduction result of each slot.

It is understood from the information in FIG. 4 that there are various tendencies in responses to the DR requests in each consumer.

For example, consumer A is an example of a consumer who has a variation in start timing (launch timing) of DR request. Consumer A performs power reduction starting in the first slot on 8/1, performs power reduction starting in the second slot on 8/3 and performs power reduction only starting in the third slot on 8/5.

Consumer B is an example of a consumer whose power reduction amount varies depending on days of DR request. Consumer B achieves a power reduction of 13.5 kWh on average on 8/1, 9.25 kWh on average on 8/5 and only 5.5 kWh on average on 8/8.

Consumer C is an example of a consumer who shows a variation as to whether or not to execute power reduction. Consumer C executes a power reduction on the order of 10 kWh on average on 8/5 and 8/8, whereas consumer C executes no power reduction on 8/12, and the demand (power consumption) rather increases by 10 kWh or more. In the case of increases in demand, the values of power reduction amount are represented by negative values.

Note that here the DR duration (DR request period) on a DR request date is 4 slots, but when the DR duration is 5 slots or more, results in 5 slots or more may be stored. Alternatively, as another method, results to be stored may be stored in 4 slots fixedly. In this case, when there is a DR request period longer than 4 slots, only the results in the first 4 slots may be extracted.

On the contrary, when there is a day when the DR request period is less than 4 slots, the missing slot value may be calculated by complementation processing using a mechanical learning technique or the like. Furthermore, when a time period of DR request on a certain day is different from a time period on another day, correction may be performed using a typical demand curve.

Furthermore, the baseline on a DR request date and the demand curve immediately before starting DR are different from the baseline of a normal date and a tendency of the demand curve, the reduction amount may be corrected by the difference.

The storage battery information DB_44 stores storage battery information on the storage battery 1 of each consumer.

FIG. 5 illustrates examples of storage battery information of each consumer stored in the storage battery information DB_44. The information in FIG. 5 includes the presence or absence of a storage battery of each consumer A, B, C, and values of power output amount per unit time (per slot) and battery capacity or the like when a storage battery is present. Examples of other than the power output amount and capacity include a power charge amount (charging speed) per unit time (per slot), a response delay time with respect to communication (time elapsed after transmitting a request for the storage battery from the DR scheduling device 101 until the request is reflected), a degree of deterioration of the storage battery or information on a priority level with which the storage battery is used for discharging or charging during DR request. Examples using the charging speed, response delay time, degree of deterioration or priority level or the like will be described in the approaches described later. When a consumer possesses two or more storage batteries with different characteristics, information may be registered for each storage battery.

The consumer combination creator 22 in the scenario creator 21 creates a consumer combination s(k) targeted for a DR request (first power reduction request). Examples of the method of creating the consumer combination s(k) include a method of randomly creating the consumer combination s(k) and a method of creating all combinations. There is also a method of selecting a combination similar to a (k-1)-th consumer combination s(k-1) created immediately before (replacing some consumers by other consumers or deleting some consumers or adding a new consumer or the like). Alternatively, a consumer combination may be created using publicly known meta-heuristic techniques such as simulated annealing, a taboo search or a genetic algorithm. In the case of consumer A, B, C, examples of consumer combination include (A, B, C), (A, B), (A, C) and (B, C). In the case where single consumers are allowed as consumer combinations, each of consumer A, consumer B, and consumer C may be added as a consumer combination.

The scenario creator 21 generates a power reduction scenario (hereinafter simply referred to as a "scenario") during a DR request period for each consumer combination created by the consumer combination creator 22 using the consumer reduction history DB_40. The scenario expresses a predicted value of a total reduction amount for each slot regarding a consumer combination. More specifically, the scenario is created by extracting history data of each consumer on an arbitrary date (DR request date) included in the consumer combination from the consumer reduction history DB_40 and summing power reduction amounts of the extracted history data for each slot. The scenario creator 21 stores the created scenario in the reduction scenario DB_41. The reduction scenario DB_41 stores the scenario created by the scenario creator 21.

FIG. 6 illustrates examples of scenarios stored in the reduction scenario DB_41. A plurality of scenarios are generated for each consumer combination. To be more specific, 27 scenarios ABC1 to ABC27 are generated for a consumer combination (A, B, C), 9 scenarios AB1 to AB9 are generated for a consumer combination (A, B), 9 scenarios AC1 to AC9 are generated for a consumer combination (A, C), and 9 scenarios BC1 to BC9 are generated for a consumer combination (B, C). Consumers with "*" mean that they are not included in a consumer combination for which a scenario is generated. For example, a scenario AB1 is generated from history data of consumers A and B, whereas history data of consumer C is not used. In the example in FIG. 4, since there are 3 pieces of history data for each consumer, when the consumer combination is (A, B, C), a total of 3 x 3 x 3 = 27 scenarios are generated. In the case of a combination of two consumers, 3x3 = 9 scenarios are generated respectively. However, only some scenarios may be randomly selected as scenarios and, for example, in the case of a consumer combination (A, B, C), some of the 27 scenarios may be randomly selected. Furthermore, history data of a day common to a plurality of consumers may be used in the same 10 scenario.

Each scenario includes an individual history ID of each consumer used to generate a scenario, a total value of power reduction amounts per slot of history data of the individual history IDs. For example, a scenario ABC4 is obtained by summing history data on a date with individual history ID = 1 of consumer A, history data on a date with individual history ID = 2 of consumer B and history data on a date with individual history ID = 1 of consumer C for each slot.

More specifically, when power reduction amounts of slots 1, 2, 3 and 4 are represented by (x1, x2, x3, x4), power reduction amounts with individual history ID = 1 of consumer A are represented by (8, 10, 11, 10), power reduction amounts with individual history ID = 2 of consumer B are represented by (8, 12, 9, 8), and power reduction amounts with individual history ID = 1 of consumer C are represented by (10, 11, 10, 11). Therefore, a predicted value of a power reduction amount per slot of the scenario ABC4 is calculated by summing the power reduction amounts of these consumers.

That is, the predicted value is calculated as (8, 10, 11, 10) + (8, 12, 9, 8) + (10, 11, 10, 11) = (26, 33, 30, 29).

The DR schedule optimizer 20 selects a consumer(s) as a DR request target based on the reduction scenario DB_41, creates a discharging schedule of at least one storage battery possessed by the selected consumer based on the predicted value of the power reduction amount of the selected consumer (target consumer) and creates a DR schedule including information on the selected consumer and the created discharging schedule. Hereinafter, details of the DR schedule optimizer 20 will be described.

The charging/discharging schedule creator 23 of the DR schedule optimizer 20 creates a discharging schedule corresponding to each scenario for each consumer combination created by each consumer combination creator 22. The created discharging schedule is stored in the charging/discharging schedule DB_45. The processor 24 of the DR schedule optimizer 20 determines a success or failure in execution of the scenario based on the created discharging schedule and the scenario.

The discharging schedule refers to scheduling a discharge amount of the storage battery for each slot (storage battery possessed by the consumer(s) included in the scenario). The discharge amount from the storage battery is treated as a power reduction amount in DR request. This is because it is possible to reduce power consumption in the system by power of the discharge amount. Creating a discharging schedule also includes a case where the discharge amount for each slot is set to zero.

For example, when the execution of a scenario is successful without performing discharging, the discharge amount for each slot may be set to zero.

A success in execution of a scenario means that the success condition is met, if (1) DR request is requested to all consumers included in the scenario, (2) all the consumers reduce power in accordance with the scenario and (3) the storage battery of the consumer is discharged in accordance with the discharging schedule (including a case where no discharging is performed, that is, a case where the discharge amount is zero). A failure in execution of a scenario means that it is impossible to create any discharging schedule that satisfies constraint on the storage battery information (storage battery constraint) and the success condition cannot be met, even if (1) DR request is requested to all the consumers included in the scenario and (2) all the consumers perform power reduction in accordance with the scenario. The charging/discharging schedule creator 23 determines a success or failure in execution of each scenario for each consumer combination and calculates a success rate "rate" for each consumer combination based on a ratio between the number of successes and the number of failures.

Examples of creation of a discharging schedule and examples of determination of success/failure in execution of a scenario will be described using FIG. 7. FIG. 7A illustrates an example where execution of a scenario according to a created discharging schedule will be successful and FIG. 7B illustrates an example where a discharging schedule that satisfies constraints of storage battery information (storage battery constraints) cannot be created and execution of the scenario fails.

In FIG. 7A, the power reduction amounts of slots 1 to 4 in a certain scenario of consumer combination (A, B, C) are (12, 16, 22, 25). In this case, when the discharge amount of the storage battery of consumer A is determined in order from first slot 1 so that the power reduction amount becomes 20 kWh or more, the discharge amounts of slots 1 to 4 of the discharging schedule become (8, 4, 0, 0). In this case, the total reduction amounts of slots 1 to 4 become (20, 20, 22, 25).

A discharge amount of a storage battery in each slot is output 10 kWh/slot or less stored in the storage battery information DB_44 (FIG. 4). The total discharge amount in all slots is 12 (= 8+4+0+0) kWh and this value is 20 kWh or less which is a capacity of the storage battery of consumer A stored in the storage battery information DB_44. Therefore, this discharging schedule satisfies the constraints of the storage battery information.

Thus, in the case of FIG. 7A, the power reduction amounts in all slots are 20 kWh or more and the discharging schedule satisfies the constraints of the storage battery information, and so if consumers perform power reduction according to the scenario and the discharging schedule is executed, execution of a DR request will be successful. Therefore, the execution of this scenario is determined to be a success. In consideration of a margin, a certain power amount is added to the reduction amount (20 kWh) defined by the contract, and a discharge amount may be determined so that a reduction amount per slot becomes the added reduction amount or more as much as possible.

Note that it is assumed that a certain power amount or a 5 power amount with a predetermined ratio of the battery capacity remains in the storage battery of the consumer at a time at which a DR request may be issued from the aggregator to the consumer or from the grid operator to the aggregator. Such a situation may be realized by a contract concluded between the aggregator and the consumer or may be realized using different methods. The storage battery may be charged using an arbitrary method such as nighttime charging or charging with power generated from a photovoltaic power generation panel.

Here, of consumers A to C, only consumer A possesses a 15 storage battery but other consumers may possess storage batteries. In this case, discharge amounts of storage batteries of one or more consumers may be determined and the sum of the determined discharge amounts and the power reduction amounts may be 20 kWh or more for each slot.

On the other hand, in FIG. 7B, power reduction amounts of slots 1 to 4 are (11, 13, 15, 25) in a certain scenario. In this case, when the discharge amount of the storage battery of consumer A is determined in order from first slot 1 so that the power reduction amount becomes 20 kWh or more, the discharge amounts of slots 1 to 4 of the discharging schedule become (9, 7, 5, 0). The total reduction amounts become (20, 20, 20, 25).

In this case, however, the total discharge amount in all slots of the storage battery of consumer A is 21 (= 9+7+5+0) (kWh). This value exceeds 20 kWh, which is a capacity determined in the storage battery information DB_44. This scenario cannot be executed, and so the scenario is determined to be a failure.

Depending on the scenario, even when the discharge amount in each slot is zero (even if no discharging schedule is executed), the execution of the scenario is determined to be a success. For example, if DR request is requested to all the consumers included in the scenario ABC4 in FIG. 6 and all the consumers reduce power in accordance with the scenario ABC4, the total reduction amount is 20 kWh or more in all slots without discharge from the storage batteries, and DR request is thus successful. DR request will be likewise successful in the cases of scenario 1 and scenario 2.

Using the above-described method, the charging/discharging schedule creator 23 generates a discharging schedule for the storage battery corresponding to each scenario for each consumer combination and the processor 24 determines a success or failure in the execution of each scenario based on the discharging schedule. For example, in the case of a consumer combination (A, B, C), there are 27 scenarios and execution of 18 scenarios thereof will be successful and a success rate "rate" = 18/27 = 66.7%. Success rates can be calculated likewise for other consumer combinations (A, C), (A, B) and (B, C).

FIG. 8 illustrates a table of results listing for each scenario of each consumer combination, a power reduction amount Q per slot, a discharge amount P per slot in a discharging schedule, a power reduction amount S per slot when discharge of discharge amount P is performed (discharge amount P added to the power reduction amount Q), a minimum value of power reduction amount S in each slot and a flag of success or failure in execution of a scenario. However, only consumer combination (A, B) are shown and table parts of other consumer combinations are omitted in this example. The success rate "rate" can be calculated by calculating a ratio between the number of successes (0) and the number of failures (x) about each consumer combination.

Here, since the success rate "rate" of the consumer combination (A, B) is highest, the processor 24 selects consumers A and B as consumers to whom DR is requested. Note that the schedule creation parameter DB_43 previously stores calculation parameters used when the processor 24 performs the processing (details will be described later).

The processor 24 determines a discharging schedule to be applied to the selected consumer(s) (selected discharging schedule). The selected discharging schedule may be one arbitrarily selected from, for example, discharging schedules of scenarios of the selected consumer combination or may be an average of discharging schedules of the scenarios (however, constraints of the storage battery information need to be satisfied) or may be determined using other methods.

The processor 24 generates information for identifying the selected consumers and output information (DR schedule) including the selected discharging schedule. The generated DR schedule is stored in the DR requested consumer combination DB_46. In this case, the DR schedule may be associated with information on the DR request received from the grid operator system 201.

The processor 24 may display the generated DR schedule on the display 29.

FIG. 9 illustrates a display example of the display 29. FIG. 9 illustrates an example of information identifying the selected consumers of the DR schedule. Consumers to whom DR request is requested are assigned "0' and the other consumers are assigned "x." Furthermore, information on the selected discharging schedule may be displayed on the display 29.

The information communicator 25 transmits the DR request to the consumer system 301 of the selected consumers based on the DR schedule at the DR start time or at a constant time before the DR start time. The DR request may include information on a period of the DR request. Also, the request of the DR request may include information on the power reduction amount expected from the consumers. The power reduction amount expected from the consumers may be a predetermined value or a value defined by the contract with the consumers or other value.

The storage battery controller 26 transmits the selected discharging schedule (that is, discharge request per slot) included 35 in the DR schedule to the storage battery system 311 of the consumer (consumer A in this example). The control device 2 of the storage battery system 311 performs charge and discharge of the storage battery 1 according to the selected discharging schedule. In this way, the discharge of the storage battery 1 is controlled. When the present device 101 calculates, in real time, the power reduction amount of each selected consumer, and if the possibility of not satisfying a success condition is high (e.g., when a power reduction of a predetermined percent of a reduction amount specified by the contract cannot be achieved at a predetermined time before an end of slot), a discharge request (modification request of a discharging schedule) may be outputted to the storage battery system 311 so as to perform discharge even if it is not defined in the discharging schedule (however, constraints of storage battery information shall be satisfied). Information of a real time power reduction amount of the selected consumer may be displayed on the display 29. In this case, the operator may input a request of discharge to the storage battery system 311 using the operation input device 28 if the operator determines it necessary, and thereby a discharge request is output to the storage battery system 311.

The DR scheduling device 101 may perform processing of determining a consumer combination when receiving a DR request from the grid operator system 201 or may perform the processing in advance before receiving the DR request.

FIG. 10 illustrates a hardware configuration of the DR scheduling device (information processing device) 101 according to the present approach. The information processing device 101 according to the present approach is constructed of a computer apparatus 150. The computer apparatus 150 is provided with a CPU 151, an input interface 152, a display device 153, a communication device 154, a main storage 155 and an external storage device 156, which are mutually connected by a bus 157.

The CPU (central processing unit) 151 executes a computer program for implementing the above-mentioned respective functional components of the information processing device 101 on the main storage 155. The CPU 151 executes the computer program and thereby implements the respective functional components.

The input interface 152 is a circuit for inputting operation signals from the input device such as a keyboard, mouse, and touch panel or the like into the information processing device 101.

The display device 153 displays data or information outputted from the information processing device 101. The display device 153 is, for example, an LCD (Liquid Crystal Display), a CRT (Cathode Ray Tube), and a PDP (plasma display), but the display device 153 is not limited thereto. The data or information outputted from computer apparatus 150 can be displayed by this display device 153.

The communication device 154 is a circuit for the information processing device 101 to communicate with the external device by wireless or wired means. Information can be inputted from the external device via the communication device 154. The information inputted from the external device can be stored in the DB. The part of the information communicator 25 and the storage battery controller 26 that carries out the communication function can be constructed on the communication device 154.

The main storage 155 stores a program that implements processing of the present approach, data necessary to execute the program and data generated by executing the program. The program is developed and executed on the main storage 155.

The main storage 155 may be, for example, RAM, DRAM or SRAM, but it is not limited to this. The various DBs and the storage in each approach may be constructed on the main storage 155.

The external storage device 156 stores the above-described program and data necessary to execute the program, data generated by executing the program or the like. The program and data are read into the main storage 155 during processing of the present approach. The external storage device 156 is, for example, a hard disk, an optical disk, a flash memory or a magnetic tape, but it is not limited to this. The various DBs and the storage in each approach may be constructed on the external storage device 156.

Note that the above-described program may be pre-installed in the computer apparatus 150 or may be stored in a storage medium such as a CD-ROM. The program may be uploaded on the Internet.

Note that the computer apparatus 150 may be provided with one or more processors 151, input interfaces 152, display devices 153, communication devices 154 and main storages 155, and peripheral devices such as a printer and a scanner may be connected thereto.

In addition, the information processing device 101 may be constructed of the single computer apparatus 150 or may be configured as a system composed of a plurality of mutually connected computer apparatuses 150.

FIG. 11 is a flowchart representing operation of the DR scheduling device 101 of the present approach. This operation may be performed when a DR request is received from the grid operator system 201 or may be performed at a predetermined time (e.g., a predetermined time before a DR request may be received) or may be performed at other timing (e.g., timing indicated by the operator).

First, the DR scheduling device 101 acquires information to be stored in at least one of the consumer reduction history DB_40, the reduction target amount DB_42, the schedule creation parameter DB_43 and the storage battery information DB_44 via at least one of the input/output I/F 27 and the information communicator 25 and stores the acquired information in these DBs (step S1). When the information is stored in these DBs in advance, storing the information in this step is not necessary.

In next step S2, the scenario creator 21 generates a consumer combination, and creates one or more power amount reduction scenarios for each consumer combination based on the history data of consumers in the consumer reduction history DB_40. The created scenarios are stored in the reduction scenario DB_41. A consumer combination may be generated for the consumers included in the consumer reduction history registered in the consumer reduction history DB_40.

Alternatively, a DB in which the consumer's information is registered may be prepared separately and a consumer combination may be generated using the DB.

In next step S3, the processor 24 initializes "rate_max," 5 which is a parameter for storing a success rate, to 0%. The processor 24 stores the initialized parameter in the schedule creation parameter DB_43.

Next, consumer combination s(k) is sequentially generated for k = 1 to Kmax starting from k = 1 and processes in steps S4 to 57 are performed every time consumer combination s(k) is generated. As an example, "Kmax" corresponds to a maximum value of the number of consumer combinations. Hereinafter, details of steps S4 to S7 will be described.

In step S4, "1" is added to previous "k" to generate a combination s(k) of the k-th. Processing is initially performed assuming k = 1.

Next, in step S5, a discharging schedule (represented by "b") of the storage battery possessed by a consumer included in the consumer combination is created based on a contract reduction amount between the grid operator and the aggregator with respect to each scenario for consumer's combination s(k). A success or failure in the execution of each scenario is determined based on the created discharging schedule and the storage battery information. A success rate "rate" of DR request is calculated based on the ratio between the number of successes and the number of failures.

In step S6, it is determined whether the success rate "rate" calculated in step 55 is greater than the "rate_max" or not. When the "rate" is greater than the "rate_max" (YES), the 30 "rate_max" is updated with the success rate "rate" in step S7.

Furthermore, "s*" is updated with consumer combination s(k) at this time. An selected discharging schedule "br" is determined based on discharging schedules "b" corresponding to the successful scenarios among scenarios of consumer combination s(k) and "b*" is updated with the determined selected discharging schedule "br." The selected discharging schedule "br" may be, for example, one discharging schedule selected from the discharging schedules "b" corresponding to the above-described successful scenarios or may be an average value of the discharging schedules "b" corresponding to the above-described successful scenarios (however, the constraints of the storage battery information need to be satisfied) or may be determined using other methods. The initial values of "s*" and "b*" may be arbitrary. On the other hand, if "rate" is equal to or less than "rate_max" (NO), none of "rate_max," "s*" or "b*" is updated.

When the processes in steps S4 to 57 are completed for Kmax-th consumer combination "s" (Kmax), a value representing a consumer combination corresponding to a maximum success rate is consequently stored in "s*" among Kmax consumer combinations, and a discharging schedule for the storage battery in that case is stored in "b*".

As described above, according to the present approach, it is possible to create a DR schedule that increases the success rate of execution of the DR request from the grid operator (selection of consumers to whom DR request is targeted and determination of an selected discharging schedule) by absorbing fluctuations in the power reduction amount of the consumers during the DR request using the storage battery of the consumer.

In the present approach, history data of each consumer is combined for each consumer combination and one or more scenarios is/are created, and a consumer combination with a high success rate of scenario execution is selected, but a reduction amount prediction model may be created for each consumer and consumers of the DR request target may be selected using the reduction prediction models. For example, prediction reduction amounts of slots 1 to 4 are sampled from a probability distribution (corresponding to a reduction amount prediction model) such as a normal distribution, and one or more pieces of sampling data so as to correspond to the history data is/are generated for each consumer. The sampling data is used as the history data of the aforementioned approach, which is then subjected to the same processing as above. The parameter defining a function form of probability distribution may be obtained in advance by parameter estimation using the consumer reduction history DB_40. A probability distribution may be generated for each consumer combination. In this case, prediction reduction amounts of slots 1 to 4 may be sampled for each consumer combination. Also, when similarity is observed in a tendency of reduction amount among a plurality of consumers (e.g., for a reason that the consumers have the same type of business), a Bayesian technique may be used in which sampling is performed using a common prior probability distribution. Furthermore, it may be possible to use a technique which uses a probability distribution with a large variance in an initial stage where less information on reduction histories of consumers is available, and in which accuracy increases as information is gathered. The technique includes, for example, reinforcement learning or banded algorithm.

(Second Approach) In the first approach, the success rate of execution of a plurality of scenarios generated for each consumer combination is calculated, and the consumer combination with the highest success rate and the selected discharging schedule are determined. In a second approach, a problem is modeled using mathematical programming, the problem is solved using a mathematical programming solver or the like and results similar to those in the first approach are thereby obtained. Examples of the mathematical programming solver include Gurobi and CPLEX.

In the present approach, the scenario creator 21 generates "scenario source data" that combines history data among all consumers. The scenario source data is stored in the reduction scenario DB_41.

FIG. 12 illustrates examples of scenario source data stored in the reduction scenario DB_41.

The processor 24 extracts data associated with a consumer combination from each piece of the scenario source data for each of a plurality of consumer combinations. The extracted data corresponds to a scenario of the consumer combination of the first approach. As in the case of the first approach, a discharging schedule corresponding to the extracted data (the extracted data may be hereinafter referred to as a "scenario") is generated, it is determined whether or not execution of the scenario is successful, and the number of scenario of successful execution is counted.

Among the plurality of consumer combinations, a consumer combination having a highest count value is selected. The processing described here is formulated as the following problem through mixed integer linear programming. "s.t." means a constraint condition.

[Formula 1] max Es ES Is) s. t.

+ (1-1s)N1 > C, Vt T,Vs S (2) 0 < cift < A,x,, Vi E Vt E T,Vs E S (3) 0 < Eitu<t cift, < Bz, Vi E I,Vt E T, Vs E S (4) xi E Vi E / (5) Is E {OM vs E S (6) Variables are defined as follows.

xi: Variable indicating whether or not a DR is requested to consumer i (whether or not to select consumer i) This variable is "1" when the DR is requested (when consumer i is selected) or "0" when no DR is requested. For example, when there are consumers 1 to 3, (xl, x2, x3) = (1, 1, 0) means that consumers 1 and 2 are selected, but consumer 3 is not selected. That is, this means that a consumer combination (1, 2) is selected.

c1.7t: Discharge amount of storage battery of consumer i at time (slot) t in the case of scenario source data s Is: Variable indicating whether or not execution of DR request is successful in the case of scenario source data s ("0" in the case of failure or "1" in the case of success) Constants are defined as follows.

I = {1, 2, ..., N}: Set of consumers T = {1, 2, ..., T}: Set of slots S = {1, 2, ..., S}: Set of scenario source data Ric,: Power amount (kWh) reduced by consumer i in slot t in the case of scenario source data s Ai: Output amount (kWh/slot) per slot of storage battery of consumer i, that is, discharge rate Bi: Capacity (kWh) of storage battery of consumer i C: Reduction target amount (kWh) M: Sufficiently large constant E"s/s in expression (1) represents the number of successes of a DR request. Therefore, the number of successes is maximized by solving this programming. A combination of consumers i and an output amount per slot of storage batteries of consumers in the combination are obtained. Note that when maximizing the success rate instead of the number of successes, expression (1) may be replaced by: [Formula 2] -is max x 100(%) seslsl Expression (2) expresses that a success condition of a certain scenario (a success condition when a certain consumer combination is identified in certain scenario source data) is that the sum of the power reduction amounts and the discharge amounts becomes a reduction target amount or more per slot.

"(1-1s)M" is a term for the constraint condition (the left side of expression (2) is equal to or more than the reduction target amount C) being satisfied when execution of the scenario results in a failure. Assuming that "M" is a sufficiently large constant, when execution of the scenario results in a failure, the left side can always be larger than the target power amount. In the case of a success, "(1-15)M" becomes zero, and the constraint condition means that the sum of the power reduction amounts and the discharge amounts is equal to or more than the reduction target amount C per slot.

Expression (3) expresses that for consumer i, a discharge amount of each slot is equal to or less than Ai. Note that expression (3) simultaneously expresses that if DR is not requested from consumer i (when xi = 0), the storage battery of consumer i is not used.

Expression (4) expresses that the total discharge amount of the storage battery of consumer i is equal to or less than capacity Bi of the storage battery.

As a specific example, when the reduction target amount (contract reduction amount) in FIG. 3, the storage battery information in FIG. 5 and the scenario source data in FIG. 12 are used, assuming that consumers A, B, C are represented by consumers 1, 2, 3, The consumer set: I = {1, 2, 3}, The slot set: T = {1, 2, 3, 4}, and The scenario source data set: S = {1, 2, 3, ..., 27}.

Ric, is set by the scenario source data in FIG. 12. For example, R1211 represents a power reduction amount of slot 1 of consumer 2 (consumer B) in the scenario source data 4. The value RI, is 10 15 kWh from FIG. 12.

In this example, only consumer 1 (consumer A) possesses the storage battery (see FIG. 5), and Al = 10 (kWh/slot), B1 = 20 (kWh). Consumer 2 (consumer B) and consumer 3 (consumer C) do not possess any storage battery, and so A2 = B2 = A3 = B3 = 0.

The target power amount is C = 20 in each slot (see FIG. 3).

Solving the problem in this example allows an optimum solution, which is (xl, x2, x3) = (1, 1, 0), to be obtained. This means that consumers A and B are selected as DR request targets. The selected discharging schedule in this case may be calculated in the same way as in the first approach. For example, in the case of consumers (A, B), the selected discharging schedule may be 4, determined for consumers (A, B) in arbitrary one of the scenario source data pieces, execution of the scenario of which is successful. Alternatively, the selected discharging schedule may be an average of dist determined for consumer (A, B) in scenario source data pieces, execution of the scenario of which is successful. The selected discharging schedule may be determined using other methods.

Note that although a plurality of pieces of scenario source data (27 pieces of scenario source data in the example in FIG. 12) are used in the above example, only one piece of scenario source data may be created by averaging the plurality of pieces of scenario source data. In this case, 151 = 1. In such a case, since the problem is simplified, faster processing can be expected.

(Third Approach) When DR request is started for the consumers selected in the aforementioned second approach, there can be a situation in which power consumption may increase more than expected and a 10 power reduction amount may not reach a contract reduction amount (reduction target amount). In that case, the DR scheduling device 101 can communicate with the storage battery system 311 of the selected consumer in real time and control the storage battery 1 so as to increase the output amount (discharge amount). However, there can also be a situation in which a response of the storage battery 1 to a control command is slow, making real-time control difficult. In this case, it is difficult to change the discharging schedule in the middle. Assuming such a situation, the present approach adds a constraint condition to make a discharging schedule common in all scenarios in the second approach in creating a DR schedule.

In this case, a variable dist of the discharging schedule in the second approach may be modified to a variable di, common to all pieces of scenario source data and may be formulated as follows. Expressions (7), (11) and (12) are the same as expressions (1), (5) and (6). Expressions (8), (9) and (10) correspond to expressions obtained by substituting the above-described variables in expressions (2), (3) and (4). [Formula 3] max EsEs Is (7) s. t.

Let x, + + (1-Is)M > C, Vt ET,Vs E S (8) 0 < d1t < Aix" vi E I,Vt E T, Vs E S (9) 0 < Eitu<t di" <13,, Vi E I,Vt E T, Vs E S (10) x, E 0,11 VIED (11) is E {OM vs E S (12) In this case, the processor 24 solves the problem, and can thereby obtain an optimum solution of (x1, x2, x3) = (1, 1, 1). The selected discharging schedule may be determined in the same way as in the second approach.

FIG. 13 illustrates a table storing information with items similar to those in FIG. 8 for each scenario in a case where consumers 1 to 3 (consumers A to C) are selected in each piece of scenario source data based on the above-described optimum solution, that is, in a case where DR is requested from all consumers A to C. The indication of information on scenarios in which other consumer combinations (A, B), (A, C) and (B, C) are selected is omitted for simplicity of displaying. This table is created by the processor 24. The discharging schedule is common in all the scenarios. That is, the discharge amount is 6 kWh in slot 1 (tl), 3 kWh in slot 2 (t2), and 0 kWh in slot 3 (t3) and slot 4 (t4) for all scenarios 1 to 27. In this example, execution of scenarios is successful in 18 scenarios of scenarios 1 to 27. Therefore, a success rate "rate" = 18/27 = 66.7%.

(Fourth Approach) The present approach will deal with a case where the storage battery can also be charged during a DR request period. In this way, when there is room for reduction target amounts of slots or a target range of reduction amounts in the middle of the DR request period, it is possible to effectively use the storage battery by charging the storage battery and using it for discharge in the slots later.

In this case, a variable clis, of the discharging schedule in the second approach is defined so that it can take not only a positive value but also a negative value. A positive value indicates discharge and a negative value indicates charge. In the present approach, the problem with mixed integer linear scheduling is formulated as follows.

[Formula 4] max Eses ls (13) s. t.

E,E! R,st x, + 4 + (1 -ts)M > 0.9C, Vt E T,Vs E S (14) LET Rft x, + dft + (1-1s)M <1.1C, Vt E T,Vs E S (15) < < A,x" Vi I,Vt c T,Vs c S (16) 0 < Bto +Eu.uct < VI ELWE T,Vs E S (17) xt E {OM vi E / (18) ts E {0,1} Vs ES (19) Constants newly introduced in the second approach are shown below.

A'i: Charge amount (kWh/slot) per slot of storage battery of consumer i, that is, charging rate BiO: Initial chargeable amount of storage battery of consumer i (initial charge amount is Bi-Bi0) (kWh) Expression (14) and expression (15) require a power reduction amount in each slot to fall within a range of 90% or more and 110% or less (18 kWh or more and 22 kWh or less) of a 15 reduction target amount of 20 kWh.

Expression (16) expresses not only that the discharge amount in each slot is Ai or below for consumer i but also that the charge amount in each slot is A'i or below for consumer i.

As a specific example, when the above-described problem is solved assuming the charging rate (A'i = 10 (kWh/slots)), an optimum solution of (x1, x2, x3) = (1, 1, 1) is obtained. An selected charging/discharging schedule (charge/discharge amount in each slot) may be determined in the same way as in the selected discharging schedule of the second approach. Note that when solving the above-described problem, the values of the discharge amount and charge amount leading to successful execution of a scenario in a certain consumer combination have their respective ranges and any value within the range can be adopted. As an example, in the case of charging, a largest possible charge amount may be determined so that the reduction amount becomes a lower limit value in the target range or in the vicinity thereof (however, larger than the lower limit value) or in the case of discharging, a smallest possible discharge amount may be determined so that the reduction amount becomes a lower limit value in the target range or in the vicinity thereof (however, larger than the lower limit value).

FIG. 14 illustrates a table storing information with items similar to those in FIG. 8 for each scenario in a case where consumers 1 to 3 (consumers A to C) are selected in each scenario source data based on the above-described optimum solution, that is, in a case where DR is requested from all consumers A to C. However, the "discharge amount" in FIG. 8 is changed to "charge/discharge amount" and the "discharge scheduled reduction amount" is changed to the "charge/discharge scheduled reduction amount". The "charge/discharge scheduled reduction amount" is obtained by adding the discharge amount to the total reduction amount of consumers A and B or subtracting the charge amount from the total reduction amount of consumers A and B. In this example, since it is only consumer A who possesses the storage battery, it is only the storage battery of consumer A that performs charge/discharge. In the case where storage batteries of a plurality of consumers are targeted, the item of "charge/discharge amount" includes the sum of discharge amounts or the sum of charge amounts of the plurality of consumers.

For example, in a scenario ABC4, 2 kWh is discharged in slot 1 (tl), 4 kWh is charged in slot 2 (t2), 2 kWh is charged in slot 3 (t3) and neither discharge nor charge is performed in slot 4 (t4). Even when 4 kWh is charged in slot 2 (t2), since the charge/discharge scheduled reduction amount is 18 (= 22-4) kWh, this falls within a target range of reduction amount (18 kWh or more and 22 kWh or less). Similarly, even when 2 kWh is charged in slot 3 (t3), since the charge/discharge scheduled reduction amount is 18 (= 20-2) kWh, this falls within a target range of reduction amount (18 kWh or more and 22 kWh or less).

In the case where there is room for the target range of reduction amount, it is possible to charge the storage battery and use the charged power for subsequent discharge. Thus, by determining a charge amount so that it becomes a lower limit of the target range of reduction amount or in the vicinity thereof, it is possible to make execution of a DR request successful and efficiently use the storage battery.

In the example in FIG. 14, 21 scenarios of the 27 scenarios are successful. Therefore, the success rate "rate" = 21/27 = 77.8%.

(Fifth Approach) In the first to fourth approaches, the storage battery controller 26 of the DR scheduling device 101 may perform control so as to charge the storage battery of a consumer after receiving a DR request from the grid operator system 201 until a start time of DR request. A storage battery to be charged may be a storage battery of a consumer, a remaining power amount of which does not reach a predetermined value defined in the contract (e.g., a power amount requested at the DR start). In this case, the consumer needs to charge the storage battery up to the predetermined value by the start time of DR request.

Other examples of storage batteries to be charged may include storage batteries of all consumers, or storage batteries of a certain number of consumers randomly selected from all the consumers. The storage batteries to be charged may be selected using other methods.

Charge may be a full charge or a charge up to a predetermined value or a charge amount may be defined using other methods. For example, in a case where a DR request is received at 12:30 and the DR request specifies 13:00 as a start time of DR, the storage battery selected using the above-described method is fully charged at 12:30 to 13:00. This makes it possible to increase the discharge amount to be used for DR.

(Sixth Approach) Although a case has been assumed in the first to fourth approaches where all power amounts of storage batteries of consumers can be used for discharge, a constraint may be added whereby a maximum of 80% of rated capacity can be used for discharge and 20% is left. This makes it possible to use a storage battery with a consumer's request for the storage battery (for example, the consumer hopes to leave part of power for emergency. The consumer's request may be for other purposes) taken into consideration. Note that 80% and 20% are examples, and other numerical values may be used.

The consumer's request for the storage battery is not restricted to one relating to the power amount to be left in the storage battery. For example, there can also be a consumer having a request for preventing deterioration of the storage battery. Therefore, a DR schedule may be created by setting priority in a storage battery of each consumer so as to preferentially use storage batteries with higher priority for discharge or charge. Furthermore, storage batteries with higher priority may be preferentially used for real-time discharge or charge. A DR schedule may be created such that a limit is placed on the number of times each storage battery can be used and a storage battery having the number of times of use reaching the limit is not used for discharge or charge during DR request.

Information on priority or the number of times of use may be stored in the storage battery information DB_44 (see FIG. 5).

(Seventh Approach) When there is a response delay in a consumer's storage battery with respect to a command sent from the DR scheduling device 101, the response delay may be taken into consideration in selecting a consumer or a storage battery. For example, a case will be assumed where a DR request and a discharging schedule are transmitted to the consumer 10 minutes before the DR start time. For example, when the response delay of the storage battery is 15 minutes (e.g., when it takes 15 minutes after sending a request to the storage battery until the request is processed), the discharging schedule will arrive late for the DR start time even if the discharging schedule (including the discharging schedule of the first slot) is sent to the storage battery 10 minutes ahead. In such a case, a selection of a consumer's storage battery having a response delay of 10 minutes or more may be avoided as the storage battery that needs to be discharged in a first slot. A delay amount in response of the storage battery may be measured, for example, by sending a request message to the storage battery and measuring a time until a response message is received. The response delay amount can depend on a network delay or a load situation of the storage battery 1.

(Eighth Approach) Although a case has been treated in the first to seventh approaches where a power reduction request is made as a DR request, the present disclosure is also applicable to a case where a power consumption request for promoting power consumption is made. In this case, a power consumption target amount is defined between the aggregator and the grid operator. A consumer to whom DR is requested may be selected such that the total power consumption amount of the selected consumer becomes a target amount or more during a DR requested period based on a power consumption history of each consumer. For a time period in which the target amount is not reached, a charging schedule for the storage battery may be created such that the sum of the charge amount and the power consumption amount of the selected consumers becomes the target amount or more. In addition, the present disclosure is also applicable to a case of a power consumption request for each aforementioned approach as appropriate.

While certain approaches have been described, these approaches have been presented by way of example only, and are not intended to limit the scope of the inventions. Indeed, the apparatuses described herein may be embodied in a variety of other forms; furthermore various omissions, substitutions and changes in the form of the apparatuses described herein may be made. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the scope of the inventions.

[Clauses] Clause 1. An information processing device comprising: a processor (24) configured to: select a plurality of target consumers to which a first power reduction request is made among the plurality of consumers based on power reduction histories of the plurality of consumers in response to a power reduction request; and predict reduction power amounts of the plurality of target consumers in response to the first power reduction request; a schedule creator (23) configured to: create a discharging schedule of a storage battery possessed by at least one of the plurality of target consumers based on a difference between a reduction target amount of the first power reduction request and a sum of the reduction power amounts predicted for the plurality of target consumers; and a communicator (30) configured to: transmit the first power reduction request to consumer systems of the plurality of target consumers; and transmit the discharging schedule to a storage battery system including the storage battery.

Clause 2. The information processing device according to clause 1, wherein the schedule creator (23) creates the discharging schedule of the storage battery for a time period in which the sum of predicted reduction power amounts is smaller than the reduction target amount under a condition that a total of the sum of predicted reduction power amounts and the discharge amount of the storage battery in the time period is equal to or more than the reduction target amount.

Clause 3. The information processing device according to clause 1 or 2, wherein the schedule creator (23) creates a charging schedule of the storage battery, wherein the schedule creator (23) creates the charging schedule of the storage battery in a time period in which the sum of predicted reduction power amounts is greater than the reduction target amount in a condition that a value obtained by subtracting the charge amount of the storage battery in the time period from the sum of predicted reduction power amounts is equal to or more than the reduction target amount, and wherein the communicator (30) transmits the charging schedule to the consumer system of at least one of the target consumers.

Clause 4. The information processing device according to any one of clauses 1 to 3, wherein the communicator (30) comprises a storage battery controller configured to: communicate with the consumer system or a grid operator system for a requested period of the power reduction request to calculate power reduced by the target consumer; determine a discharge amount to be added to the discharging schedule based on a difference between the reduced power and the reduction target amount; and control the storage battery system to perform discharge of the determined discharge amount.

Clause 5. The information processing device according to any one of clauses 1 to 3, wherein two or more of the target consumers possess storage batteries (1), priority is set in the storage batteries, and the processor (24) selects a storage battery for performing discharge from among the storage batteries possessed by the two or more target consumers based on the priority and creates the discharging schedule of the selected storage battery.

Clause 6. The information processing device according to any one of clauses 1 to 4, wherein two or more of the target consumers possess storage batteries (1), and the processor (24) selects a storage battery for performing discharge from among the storage batteries possessed by the two or more target consumers based on response delay times of the storage batteries and create the discharging schedule of the selected storage battery.

Clause 7. The information processing device according to any one of clauses 1 to 6, wherein the processor (24) predicts reduction power amounts of the plurality of target consumers based on distributions of respective power reduction amounts of the plurality of target consumers.

Clause 8. An information processing method comprising: selecting a plurality of target consumers to which a first power reduction request is made among the plurality of consumers based on power reduction histories of the plurality of consumers in response to a power reduction request; predicting reduction power amounts of the plurality of target consumers in response to the first power reduction request; creating a discharging schedule of a storage battery possessed by at least one of the plurality of target consumers based on a difference between a reduction target amount of the first power reduction request and a sum of the reduction power amounts predicted for the plurality of target consumers; transmitting the first power reduction request to consumer systems of the plurality of target consumers; and transmitting the discharging schedule to a storage battery system including the storage battery.

Clause 9. A computer program for causing a computer to perform processes comprising: selecting a plurality of target consumers to which a first power reduction request is made among the plurality of consumers based on power reduction histories of the plurality of consumers in response to a power reduction request; predicting reduction power amounts of the plurality of target consumers in response to the first power reduction request; creating a discharging schedule of a storage battery possessed by at least one of the plurality of target consumers based on a difference between a reduction target amount of the first power reduction request and a sum of the reduction power amounts predicted for the plurality of target consumers; transmitting the first power reduction request to consumer systems of the plurality of target consumers; and transmitting the discharging schedule to a storage battery system including the storage battery.

Claims (9)

1. CLAIMS1. An information processing device comprising: a processor (24) configured to: select a plurality of target consumers to which a first power reduction request is made among the plurality of consumers based on power reduction histories of the plurality of consumers in response to a power reduction request; and predict reduction power amounts of the plurality of target consumers in response to the first power reduction request; a schedule creator (23) configured to: create a discharging schedule of a storage battery possessed by at least one of the plurality of target consumers based on a difference between a reduction target amount of the first power reduction request and a sum of the reduction power amounts predicted for the plurality of target consumers; and a communicator (30) configured to: transmit the first power reduction request to consumer systems of the plurality of target consumers; and transmit the discharging schedule to a storage battery system including the storage battery.
2. 2. The information processing device according to claim 1, wherein the schedule creator (23) creates the discharging schedule of the storage battery for a time period in which the sum of predicted reduction power amounts is smaller than the reduction target amount under a condition that a total of the sum of predicted reduction power amounts and the discharge amount of the storage battery in the time period is equal to or more than the reduction target amount or within plus or minus 10% of the reduction target amount.
3. 3. The information processing device according to claim 1 or 2, wherein the schedule creator (23) creates a charging schedule of the storage battery, wherein the schedule creator (23) creates the charging schedule of the storage battery in a time period in which the sum of predicted reduction power amounts is greater than the reduction target amount in a condition that a value obtained by subtracting the charge amount of the storage battery in the time period from the sum of predicted reduction power amounts is equal to or more than the reduction target amount, and wherein the communicator (30) transmits the charging schedule to the consumer system of at least one of the target consumers.
4. 4. The information processing device according to any one of claims 1 to 3, wherein the communicator (30) comprises a storage battery controller configured to: communicate with the consumer system or a grid operator system for a requested period of the power reduction request to calculate power reduced by the target consumer; determine a discharge amount to be added to the discharging schedule based on a difference between the reduced power and the reduction target amount; and control the storage battery system to perform discharge of the determined discharge amount.
5. 5. The information processing device according to any one of claims 1 to 3, wherein two or more of the target consumers possess storage batteries (1), priority is set in the storage batteries, and the processor (24) selects a storage battery for performing discharge from among the storage batteries possessed by the two or more target consumers based on the priority and creates the discharging schedule of the selected storage battery.
6. 6. The information processing device according to any one of claims 1 to 4, wherein two or more of the target consumers possess storage batteries (1), and the processor (24) selects a storage battery for performing discharge from among the storage batteries possessed by the two or more target consumers based on response delay times of the storage batteries and create the discharging schedule of the selected storage battery.
7. 7. The information processing device according to any one of claims 1 to 6, wherein the processor (24) predicts reduction power amounts of the plurality of target consumers based on distributions of respective power reduction amounts of the plurality of target consumers.
8. 8. An information processing method comprising: selecting a plurality of target consumers to which a first power reduction request is made among the plurality of consumers based on power reduction histories of the plurality of consumers in response to a power reduction request; predicting reduction power amounts of the plurality of target consumers in response to the first power reduction request; creating a discharging schedule of a storage battery possessed by at least one of the plurality of target consumers based on a difference between a reduction target amount of the first power reduction request and a sum of the reduction power amounts predicted for the plurality of target consumers; transmitting the first power reduction request to consumer systems of the plurality of target consumers; and transmitting the discharging schedule to a storage battery system including the storage battery.
9. 9. A computer program for causing a computer to perform processes comprising: selecting a plurality of target consumers to which a first power reduction request is made among the plurality of consumers based on power reduction histories of the plurality of consumers in response to a power reduction request; predicting reduction power amounts of the plurality of target consumers in response to the first power reduction request; creating a discharging schedule of a storage battery possessed by at least one of the plurality of target consumers based on a difference between a reduction target amount of the first power reduction request and a sum of the reduction power amounts predicted for the plurality of target consumers; transmitting the first power reduction request to consumer systems of the plurality of target consumers; and transmitting the discharging schedule to a storage battery system including the storage battery.