JP7329993B2 - power management device - Google Patents

Description

The present invention relates to a power management device for balancing power demand and supply.

In recent years, we have concluded a demand response (hereinafter referred to as "DR") contract with multiple consumers, and in response to DR requests from electric power companies, control that can store or generate power such as storage batteries and solar power generation equipment of each consumer. Aggregators that control devices are emerging. DR means that an aggregator requests a consumer to change the power demand.

The aggregator satisfies the DR request from the electric power company by appropriately selecting the consumer and the control device, or by appropriately calculating the control command value to be sent to the control device of the consumer. . For example, Patent Literature 1 below proposes an aggregation system in which an aggregator satisfies a DR request by controlling charging and discharging of a storage battery of a consumer with a contractual relationship. Hereinafter, the adjustment of power supply and demand so as to satisfy the DR request is referred to as "achievement of DR".

JP 2018-33213 A

The technique of Patent Document 1 does not take into consideration the cost of the amount of power purchased by the aggregator from the retailer (purchasing power is hereinafter referred to as "purchased power"). For example, even if the aggregator is able to satisfy the DR requirement, if the charging/discharging efficiency of the storage battery used to satisfy the DR requirement is poor, the amount of power purchased from the retailer will increase accordingly, resulting in purchases. There was a problem that electricity cost increased.

SUMMARY OF THE INVENTION It is an object of the present invention to provide a power management apparatus capable of balancing power supply and demand while reducing power purchase costs.

The power management apparatus according to the present invention includes a retailer information receiving unit that receives retailer information including DR (demand response) request value and charge system information from a retailer, and from at least one or more consumers. , a consumer information receiving unit for receiving consumer information including storage battery equipment information, storage battery actual value, demand actual value, and power generation actual value of each consumer; and said demand actual value of each consumer. and a power generation amount that calculates the power generation amount prediction value of each consumer based on the power generation actual value of each consumer. a prediction unit; a facility constraint calculation unit that calculates facility constraints for each consumer based on the storage battery facility information and the storage battery performance value for each consumer; a power receiving point constraint calculation unit that calculates a power receiving point constraint for each of the consumers based on the predicted power generation amount; a DR cost calculation unit that calculates a DR cost based on the DR request value and the amount of power purchased by each consumer from the retailer; the DR cost and the purchase price; A storage battery that calculates a storage battery control command value for each consumer by solving an optimization problem with the sum of the power cost and the power cost as an objective function and with the facility constraint and the power receiving point constraint of each consumer as constraint conditions. A control command value calculation unit and a storage battery control command value transmission unit that transmits the storage battery control command value to each consumer.

According to the present invention, the storage battery control command value for each consumer is calculated based on the solution of the optimization problem whose objective function is the sum of the DR cost and the power purchase cost. A storage battery control command value that takes both into account is obtained. Therefore, the aggregator can balance supply and demand while reducing the power purchase cost.

1 is a diagram for explaining an outline of a power supply and demand system according to Embodiment 1; FIG. 1 is a diagram showing a configuration of a power management device according to Embodiment 1; FIG. FIG. 4 is a diagram showing an example of DR request values included in retailer information; It is a figure which shows the example of the charge system contained in retailer information. It is a figure which shows the example of the storage battery equipment information contained in consumer information. It is a figure which shows the example of the storage battery performance value contained in consumer information. It is a figure which shows the example of the demand amount performance value contained in consumer information. FIG. 5 is a diagram showing an example of actual power generation amount values included in consumer information; It is a figure which shows the example of a demand forecast value. FIG. 5 is a diagram showing an example of a power generation amount prediction value; FIG. 2 is a diagram schematically showing the flow of electric power between retailers and consumers; It is a figure which shows the example of a storage battery control command value. 4 is a flowchart showing the operation of the power management device according to Embodiment 1; FIG. 10 is a diagram showing the configuration of a power management device according to Embodiment 2; It is a figure which shows the example of a DR reward amount. FIG. 10 is a diagram showing an example of DR reward distribution amount; 9 is a flowchart showing operations of a power management device according to Embodiment 2;

<Embodiment 1>
FIG. 1 is a diagram for explaining the outline of the power supply and demand system according to Embodiment 1, showing the relationship between general power transmission and distribution companies, retailers, aggregators, and consumers in the system. Under the rule of simultaneous equality of planned values, retailers are required to submit a power supply and demand plan regarding the amount of electricity demanded to general power transmission and distribution business operators, and to match planned values with actual values in 30-minute increments. be. If this demand cannot be met, the retailer must pay a penalty charge (imbalance charge) according to the difference between the planned value and the actual value to the general power transmission and distribution company.

In order to avoid paying an imbalance fee, the retailer makes a DR request to the aggregator (herein, both upward DR and downward DR are collectively referred to as "DR"). In order to satisfy the DR request from the retailer, the aggregator charges and discharges the storage battery of the consumer with the desired amount of demand through the EMS (Energy Management System) of the consumer with a contractual relationship. to adjust the supply and demand balance at the power receiving point on the consumer side.

The aggregator receives a reward from the retailer according to the degree of achievement of DR. In addition, a consumer who has a contractual relationship with an aggregator receives a reward from the aggregator as compensation for providing supply and demand adjustment such as charging and discharging of the storage battery.

In addition, the aggregator has a contract for collective power reception with the retailer, and consumers who have a contractual relationship with the aggregator purchase power from the retailer via the aggregator. In other words, the aggregator purchases power from the retailer according to the amount of power purchased by the consumers with whom the aggregator has a contractual relationship, and bills the consumers for electricity charges.

FIG. 2 is a diagram showing the configuration of the power management apparatus 200 according to Embodiment 1. As shown in FIG. The power management device 200 is a device deployed in the aggregator of the power supply and demand system shown in FIG. Then, the power demand is adjusted by controlling the EMS 102 of the consumer (hereinafter referred to as "customer EMS 102") with which the contract is established.

Details of the power management apparatus 200 will be described below while showing specific examples of data handled by the power management apparatus 200 . Here, the retailer and the aggregator have concluded a DR contract with three customers (not shown), customer 1, customer 2, and customer 3, and the current time is January 1, 2019. It is 12:00, and it is assumed that the power supply and demand adjustment is performed for 30 minutes from 12:30 to 13:00 on the same day.

As shown in FIG. 2, the power management device 200 includes a retailer information receiving unit 201, a consumer information receiving unit 202, a demand forecasting unit 203, a power generation forecasting unit 204, an equipment constraint calculator 205, a power receiving point constraint calculator A power purchase cost calculation unit 207 , a DR cost calculation unit 208 , a storage battery control command value calculation unit 209 and a storage battery control command value transmission unit 210 are provided.

The retailer information receiving unit 201 receives retailer information from the retailer server 101 . The retailer information includes two pieces of information: the DR request value from the retailer to the aggregator and the electricity tariff system.

FIG. 3 shows an example of DR request values included in the retailer information. In the table of FIG. 3, the first column represents the date and time in yyyy/MM/dd/hh:mm format (year=yyyy, month=MM, day=dd, hour=hh, minute=mm). Column 2 is the DR request value for 30 minutes from the date and time indicated by the first column. That is, in the example of the DR request value in FIG. 3, there is no DR request from 12:00 to 12:30, and the total value of the power purchase amount of consumers 1 to 3 from 12:30 to 13:00 is 15 kWh. It requires the aggregator to

FIG. 4 shows an example of the fee structure included in the retailer information. In the table of FIG. 4, the first column represents the time in hh:mm-hh:mm format, and the second column represents the unit price of electricity for the time in the first column.

The consumer information receiving unit 202 receives consumer information from the consumer EMS 102 of the consumer who has concluded the DR contract with the aggregator. The consumer information includes four types of information: storage battery equipment information, storage battery actual value, demand actual value, and power generation actual value.

FIG. 5 shows an example of storage battery equipment information included in consumer information. In the table of FIG. 5, the first column represents the identification number of the consumer, the second column represents the storage battery capacity, and the third column represents the upper limit of the remaining amount of the storage battery (SOC: State Of Charge). The fourth column represents the lower limit of SOC, the fifth column represents charging efficiency, and the sixth column represents discharging efficiency.

FIG. 6 shows an example of storage battery performance values included in consumer information. In the table of FIG. 6, the first column indicates the date and time in yyyy/MM/dd/hh:mm format, and the second to fourth columns indicate the storage batteries of consumers 1 to 3 at the date and time indicated by the first column. Each represents the SOC.

FIG. 7 shows an example of actual demand values included in consumer information. In the table of FIG. 7, the first column shows the date and time in yyyy/MM/dd/hh:mm format, and the second to fourth columns show the data of consumers 1 to 3 in 30 minutes from the date and time shown in the first column. , respectively, represent actual demand values.

FIG. 8 shows an example of actual power generation amount values included in consumer information. In the table of FIG. 8, the first column shows the date and time in yyyy/MM/dd/hh:mm format, and the second to fourth columns show the data of consumers 1 to 3 in 30 minutes from the date and time shown in the first column. , respectively.

The demand prediction unit 203 calculates a demand prediction value for each consumer from the demand actual value (FIG. 7) included in the consumer information. FIG. 9 shows an example of demand forecast values. In the table of FIG. 9, the first column shows the date and time in yyyy/MM/dd/hh:mm format, and the second to fourth columns show the data of consumers 1 to 3 in 30 minutes from the date and time shown in the first column. Demand forecast values for The predicted demand value can be calculated by, for example, adopting the actual demand value for the same date and time in the previous year as the predicted demand value.

The power generation amount prediction unit 204 calculates a power generation amount prediction value from the power generation amount actual value (FIG. 8) included in the consumer information. FIG. 10 shows an example of the predicted power generation amount. In the table of FIG. 10, the first column shows the date and time in yyyy/MM/dd/hh:mm format, and the second to fourth columns show the data of consumers 1 to 3 in 30 minutes from the date and time shown in the first column. , respectively. The power generation amount prediction value can be calculated, for example, by adopting the average of the power generation amount actual values for the past one month as the power generation amount prediction value.

The equipment constraint calculation unit 205 calculates equipment constraints from the storage battery equipment information ( FIG. 5 ) and the storage battery performance value ( FIG. 6 ) included in the consumer information. For example, the SOC of the storage battery of consumer i (i=1, 2, 3) at time t is expressed as SOC(t, i), the amount of charge and discharge is expressed as variable EC(t, i), and the SOC of the storage battery of consumer i is expressed as Let SOC_MIN(i) be the lower limit, SOC_MAX(i) be the upper limit of SOC, η(i) be the discharge efficiency, and ε(i) be the charge efficiency. Representing (i), the SOC equipment constraint is expressed as follows. Here, times t=0, 1, 2, defined as 0=12:00, 1=12:30, 2=13:00. Also, SOC (t, i) is calculated by multiplying the storage battery capacity [kWh] in FIG. 5 by the SOC [%] in FIG. Also, the variable EC(t, i) is the amount of electric power for 30 minutes from time t, and a positive value means a discharged amount and a negative value means a charged amount. Note that EC(t, i) must be a value obtained by accumulating past charge/discharge amounts. can be used as the actual value of the charge/discharge amount.

The power receiving point constraint calculation unit 206 calculates a power receiving point constraint based on the predicted demand value calculated by the demand prediction unit 203 and the predicted power generation value calculated by the power generation prediction unit 204 . FIG. 11 schematically shows the flow of electric power between retailers and consumers. Variable Buy(t, i) is the amount of electricity purchased from the retailer by consumer i at time t, Demand(t, i) is the predicted demand amount, EC(t, i) is the amount of charge/discharge, and the predicted value of power generation amount. be Power(t,i), the power receiving point constraint can be calculated as follows.

Since the above-mentioned power purchase amount is the meter reading value of the smart meter, the consumer who received the DR request from the aggregator must set the power purchase amount to the DR request at the DR time (12:30 in the case of FIG. Must match the value. In the example shown above, if the storage battery is not charged or discharged at this time, the predicted value of the total power purchase amount of consumers 1 to 3 at 12:30 is the predicted demand value in FIG. 9 and the predicted power generation amount in FIG. From the value, it is calculated as (13.7-3.7) + (12.5-2.5) + (16.9-6.9) = 30.0 [kWh]. In this case, for example, in order to set the DR request value to 15 [kWh], the power purchase amount must be reduced by 15 [kWh] to match the DR request value.

The power purchase cost calculation unit 207 calculates the power purchase cost based on the charge system (charge unit price) included in the retailer information and the amount of power purchased from the retailer. If the charge unit price at time t is represented by Charge(t), the power purchase cost Buy_Cost is calculated as follows.

The DR cost calculator 208 calculates the DR cost based on the DR request value and the amount of power purchased from the retailer included in the retailer information. The DR cost is a cost corresponding to the degree of achievement of DR, and when the DR request value is represented as DR, the DR cost DR_Cost is calculated as follows. Here, as shown in FIG. 3, the DR request is issued only at 12:30, so only the power purchase amount at 12:30 (that is, t=1) is considered in calculating the DR cost.

The storage battery control command value calculation unit 209 calculates a storage battery control command value. The storage battery control command value calculated by the storage battery control command value calculation unit 209 is transmitted to the consumer EMS 102 by the storage battery control command value transmission unit 210 . The consumer's EMS 102 that has received the battery control command value controls charging and discharging of the consumer's battery in accordance with the battery control command value, thereby adjusting power supply and demand to achieve DR.

FIG. 12 shows an example of the storage battery control command value. In the table of FIG. 12, the first column represents the date and time in yyyy/MM/dd/hh:mm format, and the second to fourth columns show the data of consumers 1 to 3 in 30 minutes from the date and time shown in the first column. , respectively represent the storage battery control command values.

The calculation of the storage battery control command value is performed by solving an optimization problem with the sum of the DR cost and the power purchase cost as the objective function and with the equipment constraint and the power receiving point constraint as the constraint conditions. That is, the storage battery control command value is calculated as a value that minimizes the following objective function.

Since this optimization problem is a quadratic programming problem, it is solved using the interior point method or the conjugate gradient method. The solution in the above example is the storage battery control command value shown in FIG. Charge 5 kWh each, and discharge 9.0 kWh from the storage battery of customer 1 and 6.0 kWh from the storage battery of customer 2 between 12:30 and 13:00 when DR is requested. become. As a result, the predicted value of the total power purchase amount of consumers 1 to 3 from 12:30 to 13:00 is (13.7 - 9.0 - 3.7) + (12.5 - 6.0 −2.5)+(16.9−6.9)=15, and DR can be achieved.

The power management device 200 of Embodiment 1 calculates the storage battery control command values for the consumers 1 to 3 in consideration of minimizing the sum of the DR cost and the power purchase cost. Even if only minimization is considered, the storage battery control command value that can achieve DR is calculated. When considering only the minimization of the DR cost, for example, between 12:00 and 12:30, the storage battery of the customer 2 is charged with 10.0 kWh, and the storage battery of the customer 3 is charged with 10.0 kWh. A storage battery control command value is calculated such that the storage battery of the customer 2 discharges 8.0 kWh and the storage battery of the customer 3 discharges 7.0 kWh from 30:30 to 13:00. As a result, the predicted value of the total power purchase amount of consumers 1 to 3 from 12:30 to 13:00 is (13.7-3.7) + (12.5-8.0-2.5 )+(16.9−7.0−6.9)=15, and DR can be achieved in this case as well.

However, the amount of power purchased from 12:00 to 12:30 was 10.0+7.5=17.5 [kWh] when considering minimization of the sum of the DR cost and the power purchase cost. , 10.0+10.0=20.0 [kWh] when only the minimization of the DR cost is considered. That is, when considering minimization of the sum of the DR cost and the power purchase cost, the power purchase amount can be reduced by 2.5 [kWh] compared to when only minimizing the DR cost is considered.

Thus, in the power management apparatus 200 of Embodiment 1, the aggregator can reduce the power purchase cost for achieving the DR by balancing power supply and demand. Therefore, it is possible to reduce the reward paid by the aggregator to the consumer in order to achieve the DR. In order to achieve this purpose, the aggregator does not need to allow power interchange between consumers, nor does it need to have a charging facility.

FIG. 13 is a flow chart showing the operation of the power management device 200 according to the first embodiment. The operation of the power management device 200 will be described below with reference to the flowchart of FIG. 13 .

When the power management device 200 is activated, first, the retailer information receiving unit 201 receives retailer information from the retailer server 101 (step ST1). The retailer information includes the DR request value from the retailer to the aggregator and information on the fee structure.

Next, the consumer information receiving unit 202 receives consumer information from the consumer EMS 102 of the consumer who has concluded the DR contract with the aggregator (step ST2). The consumer information includes information such as storage battery facility information, storage battery actual value, demand actual value, and power generation actual value.

Subsequently, the demand forecasting unit 203 calculates the demand forecast value of each customer from the actual demand value included in the customer information (step ST3). Further, the power generation amount prediction unit 204 calculates a power generation amount prediction value from the power generation amount actual value included in the consumer information (step ST4). Further, the equipment constraint calculation unit 205 calculates equipment constraints from the storage battery equipment information and the storage battery performance value included in the consumer information (step ST5). Also, the power receiving point constraint calculation unit 206 calculates the power receiving point constraint based on the predicted demand value calculated by the demand prediction unit 203 and the predicted power generation value calculated by the power generation prediction unit 204 (step ST6).

Next, the power purchase cost calculation unit 207 calculates the power purchase cost based on the charge system (charge unit price) included in the retailer information and the amount of power purchased from the retailer (step ST7). Also, the DR cost calculation unit 208 calculates the DR cost based on the DR request value included in the retailer information and the amount of power purchased from the retailer (step ST8).

Next, the storage battery control command value calculation unit 209 solves an optimization problem with the sum of the DR cost and the power purchase cost as the objective function and with the equipment constraint and the power receiving point constraint as the constraint conditions, thereby obtaining the storage battery control command value is calculated (step ST9). Then, storage battery control command value transmission section 210 transmits the storage battery control command value calculated by storage battery control command value calculation section 209 to consumer EMS 102 (step ST10). The consumer's EMS 102 that has received the battery control command value controls charging and discharging of the consumer's battery in accordance with the battery control command value, thereby adjusting power supply and demand to achieve DR.

<Embodiment 2>
When the aggregator achieves DR, the retailer pays the aggregator a reward, and the aggregator pays a consumer with a contractual relationship. However, since the power purchase cost and storage battery capacity on the customer side associated with the provision of supply and demand adjustment differ for each customer, the remuneration paid by the aggregator to the customer will be determined for each customer in consideration of these differences. Otherwise, injustice can occur.

For example, in the case of a lower DR that suppresses demand by discharging when supply and demand is tight, it is necessary to charge in advance in preparation for discharging when supply and demand is tight, but demand that receives a charge control command during a time period when the unit price is high Households have a higher cost of power purchase than consumers who receive a charging control command during times when the unit price is low, so it is not fair to pay the same amount of remuneration to these consumers.

In Embodiment 2, the power management apparatus 200 is provided with a function of calculating a fair amount of remuneration in consideration of the difference in the amount of adjustment for each consumer. FIG. 14 is a diagram showing the configuration of power management apparatus 200 according to the second embodiment. The configuration of the power management apparatus 200 in FIG. 14 is obtained by adding a DR reward distribution amount calculation section 301 to the configuration in FIG.

The operation of the power management apparatus 200 of the second embodiment to adjust the supply and demand of power according to the DR request received from the retailer server 101 is the same as that of the first embodiment. However, in the second embodiment, after the power supply and demand are adjusted, the retailer information receiving unit 201 receives from the retailer server 101 a remuneration amount (hereinafter referred to as “DR remuneration amount”) according to the degree of achievement of the DR. ). FIG. 15 shows an example of the DR reward amount. In the table of FIG. 15, the first column represents the date in yyyy/MM/dd format, and the second column represents the DR reward amount from the retailer to the aggregator on the date indicated by the first column.

The DR reward distribution amount calculation unit 301 calculates the DR reward distribution amount, which is the DR reward amount for each consumer. Here, the power management apparatus 200 adjusts the power supply and demand as exemplified in the first embodiment (adjusting the power supply and demand from 12:30 to 13:00 on January 1, 2019). At 15:00 on the first day of the month, the retailer information receiving unit 201 receives the DR remuneration amount shown in FIG. A case of calculating the amount of remuneration is shown. FIG. 16 shows an example of the DR reward distribution amount in this case. In the table of FIG. 16, the first column represents the date in yyyy/MM/dd format, and the second to fourth columns are the DR reward amounts (DR reward distribution amounts) of consumers 1 to 3, respectively.

For example, the following criteria (a) and (b) are provided as a fair method of determining the DR reward distribution amount.
(a) Customers who receive more charging control commands during times when the unit price is high will have higher purchase costs than consumers who receive charging commands during times when the unit price is low, so they will receive more compensation. (b) Customers who receive more discharge control commands during times when the unit price is low save less power purchase cost by discharging than consumers who receive discharge commands during times when the unit price is high. to receive more rewards

A variable F(i) representing the amount of DR remuneration for consumer i (i=1, 2, 3) can be defined, for example, as follows based on criteria (a) and (b). That is, let Charge(t) be the charge unit price at time t, EC(t, i) be the storage battery control command value for consumer i at time t, and Avg_Charge be the average charge unit price. is expressed as Here, time t=0, .

If the DR reward amount from the retailer to the aggregator is represented as Incentive, the reward amount Incentive(i) for consumer i can be calculated as follows, for example. Note that the denominator of the fraction on the right side of this equation is a normalization term for calculating the allocation ratio.

In the case of this example, from FIG. 4, the average value of the charge unit price is Avg_Charge={(10.0×20)+(12.0×10)+(10.0×18)}/48≈10.4167. Become. The unit price for charging from 12:00 to 12:30 is Charge(0)=12.0 yen/kWh, and the unit price for discharging from 12:30 to 13:00 is Charge(1). = 12.0. Furthermore, since the charge/discharge amount of each consumer corresponds to the storage battery control command value, from FIG. kWh], the charge/discharge amount of consumer 1 from 12:30 to 13:00 is EC (1, 1) = -9 [kWh], and the charge/discharge amount of consumer 2 from 12:00 to 12:30 is The discharge amount is EC (0, 2) = 7.5 [kWh], and the charge/discharge amount of consumer 2 from 12:30 to 13:00 is -6 [kWh] for EC (1, 2). Become. In addition, since the charge/discharge amount from 12:00 to 12:30 and the charge/discharge amount from 12:30 to 13:00 of the consumer 3 are both 0, EC (0, 3) = 0 [kWh ], EC (1, 3)=0 [kWh].

Therefore, the variable F(i) representing the amount of DR remuneration for consumer i (i=1, 2, 3) is F(1)=10.4167/12.0×9+12.0/10. 4167×10≈19.3325, F(2)=10.4167/12.0×6+12.0/10.4167×7.5≈13.8483, F(3)=0. From FIG. 15, since Incentive=100000 [yen], the DR reward distribution amount Incentive(i) for consumer i (i=1, 2, 3) is Incentive(1) as shown in FIG. =100000×19.3325/(19.3325+13.8483)≈58264 [yen], Incentive(2)=100000×13.8483/(19.3325+13.8483)≈41736 [yen], Incentive(3)≈0 [Yen]. In this way, the more the amount of adjustment is provided to the customer, the larger the amount of remuneration will be, making it possible to distribute the amount of DR remuneration fairly.

FIG. 17 is a flowchart showing operations of the power management device 200 according to the second embodiment. The flow of FIG. 17 is obtained by adding steps ST11 and ST12 to the end of the flow of FIG. Since the processes of steps ST1 to ST10 are the same as those in FIG. 13, descriptions thereof are omitted here.

After the power supply and demand of each consumer is adjusted by the processing of steps ST1 to ST10, the retailer information receiving unit 201 receives the DR reward amount from the retailer server 101 according to the degree of achievement of the DR. Receive (step ST11). Then, the DR reward distribution amount calculation unit 301 calculates the DR reward distribution amount for each consumer based on the DR reward amount received by the retailer information receiving unit 201 and the adjustment amount provided by each consumer. (Step ST12). Since the DR reward distribution amount calculation unit 301 calculates the DR reward distribution amount of each consumer so as to correspond to the adjustment amount provided by the consumer, a fair distribution of the DR reward amount is performed.

In the above description, the storage battery actual value, the demand actual value, and the power generation actual value included in the consumer information received by the consumer information receiving unit 202, the demand forecast value calculated by the demand forecast unit 203, and The power generation amount prediction value calculated by the power generation amount prediction unit 204 is set to a value for each 30 minutes, because it is assumed that the imbalance between power supply and demand is determined every 30 minutes. However, the imbalance determination cycle is not limited to 30 minutes, and the storage battery actual value, the demand actual value, the power generation actual value, the demand forecast value, the power generation forecast value, and the storage battery control command calculated from these values The cycle of values, DR reward amounts, etc. can be changed according to the imbalance determination cycle.

In addition, within the scope of the invention, each embodiment can be freely combined, and each embodiment can be appropriately modified or omitted.

101 retailer server, 102 consumer EMS, 200 power management device, 201 retailer information receiving unit, 202 consumer information receiving unit, 203 demand prediction unit, 204 power generation amount prediction unit, 205 facility constraint calculation unit, 206 207 power purchase cost calculation unit 208 DR cost calculation unit 209 storage battery control command value calculation unit 210 storage battery control command value transmission unit 301 DR reward distribution amount calculation unit.

Claims (2)

a retailer information receiving unit that receives retailer information including DR (demand response) request value and fee system information from the retailer;
a consumer information receiving unit that receives, from at least one or more consumers, consumer information including information on storage battery facility information, storage battery actual values, demand actual values, and power generation actual values of each consumer;
a demand prediction unit that calculates a predicted demand value of each consumer based on the actual demand value of each consumer;
a power generation amount prediction unit that calculates a predicted power generation amount value for each consumer based on the actual power generation amount value for each consumer;
an equipment constraint calculation unit that calculates equipment constraints of each consumer based on the storage battery equipment information and the actual value of the storage battery of each consumer;
a power receiving point constraint calculation unit that calculates a power receiving point constraint for each consumer based on the predicted demand value and the predicted power generation value for each consumer;
a power purchase cost calculation unit that calculates a power purchase cost based on the rate system and the amount of power purchased by each of the consumers from the retailer;
a DR cost calculation unit that calculates a DR cost based on the DR request value and the power purchase amount of each consumer from the retailer;
Storage battery control for each customer by solving an optimization problem with the sum of the DR cost and the power purchase cost as an objective function and with the facility restrictions and the power receiving point restrictions of each customer as constraints. a storage battery control command value calculation unit that calculates a command value;
a storage battery control command value transmission unit that transmits the storage battery control command value to each of the consumers;
A power management device comprising: Further comprising a DR reward distribution amount calculation unit that calculates a reward amount to be paid to each of the consumers based on the adjustment amount provided by each of the consumers to achieve the DR when there are a plurality of the consumers,
The power management device according to claim 1.

Images