JP2020182299A - Server device and control method - Google Patents

Abstract

To prevent a reduction of prediction accuracy of forward flow power and backward flow power at a user and to report an adequate DR possible amount to an aggregation coordinator.SOLUTION: In an electric power system, a server device 100 connecting a user through a network has a control unit performing a control of suppressing variation of at least one of forward flow power and backward flow power at a target user, that is a user at which an occurrence of a predetermined event is detected, based on prediction accuracy of the forward flow power and the backward flow power at the user per time zone, when the occurrence of the predetermined event is detected.SELECTED DRAWING: Figure 2

Description

The present invention relates to a server device and a control method.

In VPP (Virtual Power Plant), the resource aggregator (RA: Resource Aggregator) needs to report the DR (Demand Response) possible amount to the aggregation coordinator (RC: Resource Aggregation Coordinator).

The aggregation coordinator determines the DR request amount according to the reported DR possible amount.

The resource aggregator predicts the demand power of the consumer (that is, the power required by the consumer) and obtains such a DR possible amount, but if the prediction is not met and the DR request amount cannot be achieved, a penalty is imposed. If the forecast accuracy of the required power is high for the consumer, the maximum feasible DR possible amount is reported, but if the forecast accuracy is low, the above forecast is made. Report a small amount of DR request considering the risk of deviation.

JP-A-2007-129873

However, in general, such prediction accuracy tends to increase as the amount of past data increases. Therefore, in the past, such as when a predetermined event such as participation of a new customer or a change in the equipment configuration of an existing customer occurs. When there is little data, there is a problem that such prediction accuracy cannot be ensured and it is not possible to calculate the risk of how much the prediction is wrong.

Therefore, the present invention has been made in view of the above-mentioned problems, and it is necessary to avoid a decrease in the prediction accuracy of power flow power and reverse power flow power in the consumer and report an appropriate DR possible amount to the aggregation coordinator. It is an object of the present invention to provide a server device and a control method that enable the above.

The first feature of the embodiment of the present invention is the server device, which is described above based on the prediction accuracy of power flow power and reverse power flow power in consumers for each time zone when the occurrence of a predetermined event is detected. The gist is to have a control unit that controls fluctuations in at least one of the power flow power and the reverse power flow power in the target customer who is the customer in which the occurrence of a predetermined event is detected.

The second feature of the embodiment of the present invention is a control method, which is based on the prediction accuracy of power flow power and reverse power flow power in consumers for each time zone when the occurrence of a predetermined event is detected. The gist is to have a method of controlling the fluctuation of at least one of the power flow power and the reverse power flow power in the target customer who is the customer in which the occurrence of the predetermined event is detected.

According to the embodiment of the present invention, a server device and a control method capable of avoiding a decrease in prediction accuracy of power flow power and reverse power flow power in a consumer and reporting an appropriate DR possible amount to an aggregation coordinator. Can be provided.

FIG. 1 is a diagram showing an example of the overall configuration of the electric power system 1 according to the embodiment. FIG. 2 is a diagram showing an example of a functional block of the server device 100 according to the embodiment. FIG. 3 is a diagram showing an example of control by the server device 100 according to the embodiment. FIG. 4 is a diagram showing an example of control by the server device 100 according to the embodiment. FIG. 5 is a diagram showing an example of control by the server device 100 according to the embodiment. FIG. 6 is a diagram showing an example of control by the server device 100 according to the embodiment. FIG. 7 is a diagram showing an example of control by the server device 100 according to the embodiment. FIG. 8 is a flowchart showing an example of the operation of the server device 100 according to the embodiment.

Hereinafter, the control system according to the embodiment of the present invention will be described with reference to the drawings. In the description of the drawings below, the same or similar parts are designated by the same or similar reference numerals.

(First Embodiment)
Hereinafter, the first embodiment of the present invention will be described with reference to FIGS. 1 to 8. FIG. 1 is a diagram showing an example of the configuration of the power system 1 according to the present embodiment.

As shown in FIG. 1, the electric power system 1 includes a server device 100, an aggregation coordinator 200, and a consumer 300A / 300B.

The server device 100 may be composed of one server device or a plurality of server devices. The server device 100 may be managed by a resource aggregator.

For example, a resource aggregator is an electric power company that provides reverse power flow to a power generation company, a power transmission and distribution company, a retail company, etc. in VPP, and an aggregation coordinator 200 is an entity that provides infrastructure such as an electric power system. For example, it is an electric power company such as a power generation company or a power transmission and distribution company.

In FIG. 1, two consumers 300A / 300B are illustrated as the consumers 300, but usually, such a power system 1 is provided with three or more consumers 300. Each consumer corresponds to a facility connected to the power grid (not shown).

In the following, the flow of electric power from the electric power system to the consumer 300 will be referred to as power flow, and the flow of electric power from the consumer 300 to the electric power system will be referred to as reverse power flow. The power from the power system to the consumer 300 is sometimes referred to as demand power.

The consumer 300A has a power storage device 301, a load device 303, and an EMS (Energy Management System) 304, and the consumer 300B has a power storage device 301, a distributed power supply 302, a load device 303, and an EMS. It has (Energy Management System) 304.

The power storage device 301 is a device that charges and discharges electric power under the control of EMS 304. For example, the power storage device 301 is a lithium ion power storage device, a lead power storage device, a nickel / hydrogen power storage device, or the like.

The electric power discharged by the power storage device 301 may be supplied to the load device 303 in the consumer 300 or may be supplied to the electric power system. Further, in the present embodiment, the electric power generated by the power generation device may be sold and operated in the "push-up mode" in which the load device 303 in the consumer 300 is covered by the discharge of the power storage device 301. The power storage device 301 can charge, for example, the power supplied by the power system or the surplus power of the power generation device.

The distributed power supply 302 may be a fuel cell device that generates power using fuel. A fuel cell device is a device that uses fuel to generate electricity. For example, the fuel cell apparatus may be a solid oxide fuel cell (SOFC: Solid Oxide Fuel Cell), a solid polymer fuel cell (PEFC: Molten Electrolite Fuel Cell), or a phosphoric acid type fuel cell. It may be a fuel cell (PAFC: Phosphoric Acid Fuel Cell) or a molten carbonate fuel cell (MCFC: Molten Carbonate Fuel Cell). Further, the distributed power supply 302 may be a power generation device that generates power using natural energy such as solar power, wind power, hydraulic power, and geothermal power.

The distributed power source 302 may be a fuel cell device that generates electricity using fuel. A fuel cell device is a device that uses fuel to generate electricity. For example, the fuel cell apparatus may be a solid oxide fuel cell (SOFC: Solid Oxide Fuel Cell), a solid polymer fuel cell (PEFC: Molten Electrolite Fuel Cell), or a phosphoric acid type fuel cell. It may be a fuel cell (PAFC: Phosphoric Acid Fuel Cell) or a molten carbonate fuel cell (MCFC: Molten Carbonate Fuel Cell). Further, the distributed power source 302 may be a power generation device that generates power using natural energy such as solar power, wind power, hydraulic power, and geothermal power.

The load device 303 is a device that consumes electric power. For example, the load device 303 is an air conditioner device, a lighting device, an AV (Audio Visual) device, or the like.

The EMS 304 is a power management device that manages the power of the consumer 300. The EMS 304 may control the operating states of the distributed power supply 302 and the load device 303. EMS304 is an example of VEN (Virtual End Node).

As shown in FIG. 2, the server device 100 includes a detection unit 101, a storage unit 102, a calculation unit 103, and a control unit 104.

The detection unit 101 is configured to detect the occurrence of a predetermined event in a plurality of consumers. Specifically, the detection unit 101 may be configured to detect the participation of a new customer 300, a change in the device configuration of an existing customer 300, or the like as the occurrence of a predetermined event. Here, the change in the device configuration means the addition, new installation, removal, model change, etc. of the power storage device 301, the distributed power source 302, and the load device 303 in the customer 300.

The storage unit 102 is composed of a storage medium such as a non-volatile memory and / and HDD, and predicts accuracy of power flow power and reverse power flow power in the consumer 300 such as past power flow power and reverse power flow power in each customer 300. It is configured to store the data necessary for calculating (hereinafter, the prediction accuracy of the consumer 300).

Here, the tidal current electric power and the reverse tidal current electric power in the consumer 300 are synonymous with the electric power for sale and the electric power for purchase in the consumer 300, respectively. Further, the tidal current power of the consumer 300 may be referred to as the demand power of the consumer 300.

For example, the storage unit 102 may be configured to store the charge / discharge electric energy, the remaining amount (SOC), and the operation mode in the power storage device 301 as the above-mentioned data, or may store the power generation amount in the photovoltaic power generation device. It may be configured to memorize, may be configured to memorize the trading power amount acquired by the smart meter, and may be configured to memorize the power consumption of each device or distribution board branch detected by the CT sensor. It may be configured to store the quantity.

The calculation unit 103 is configured to calculate predetermined information by referring to the data or the like stored in the storage unit 102.

For example, as shown in FIG. 3, the calculation unit 103 is configured to calculate the prediction accuracy of the power flow power and the reverse power flow power of the entire consumer for each time zone (hereinafter, the prediction accuracy of the entire consumer). ..

Further, the calculation unit 103 is configured to calculate the prediction accuracy of the power flow power and the reverse power flow power in the target customer for each time zone (hereinafter, the prediction accuracy of the target customer). Here, the target consumer is the consumer 300 in which the occurrence of a predetermined event is detected.

In addition, the calculation unit 103 is configured to calculate the prediction accuracy of the power flow power and the reverse power flow power of all the consumers other than the target customer for each time zone (hereinafter, the prediction accuracy of all the consumers other than the target customer). It may have been done.

Here, the unit of the time zone may be any unit. For example, as shown in FIG. 3, the unit of the time zone may be a load-followable time (3 hours in the example of FIG. 3) estimated from the capacity of the power storage device 301 of each consumer 300.

When the detection unit 101 detects the occurrence of a predetermined event, the control unit 104 determines at least one fluctuation of the power flow power and the reverse power flow power in the target customer based on the prediction accuracy of the customer 300 for each time zone. It is configured to perform suppression control.

For example, as shown in FIG. 3, the control unit 104 determines at least the tidal current power and the reverse tidal current power of the target consumer in the time zone from 9:00 to 12:00 when the prediction accuracy of the entire consumer for each time zone is low. It is configured to control one of the fluctuations.

Further, the control unit 104 instructs the target consumer (for example, the consumer 300A) who has the power storage device 301 and does not have the distributed power source 302 to perform load tracking control in the target time zone. It is configured to do.

Here, the target time zone indicates a time zone in which the above-mentioned control is performed, such as a time zone in which the prediction accuracy of the entire consumer is low (or a time zone in which the prediction accuracy of the entire consumer other than the target customer) is low.

For example, as shown in FIG. 4, in the target time zone, the power storage device 301 and the EMS 304 such as the load tracking control automatically set the power storage device 301 and the EMS 304 for the customer 300A, which is the target customer, in the target time zone. Instruct to perform control to keep the demand power constant.

In the example of FIG. 4, in the time zone from 9:00 to 12:00, the trading power (tide power and reverse power) of the customer 300 becomes 0 regardless of the change in the life pattern of the customer 300, and the past It is not necessary to make a prediction using the data of the trading power of the consumer 300.

Further, the control unit 104 sells all the electric power generated by the distributed power source 302 to the target consumer (for example, the customer 300B) having the power storage device 301 and the distributed power source 302 in the target time zone. It is configured to instruct you to do so.

For example, as shown in FIG. 5, the control unit 104 makes the target consumer 300B cover the power consumption of the customer 300B by discharging the power storage device 301 in the target time zone, and distributes the power supply 302. Instruct to sell all the electricity generated by.

According to this configuration, the amount of power generated by the photovoltaic power generation device (PV power generation amount) of the distributed power sources 302 depends on the specifications of the panel and the amount of sunshine in the area where the panel is installed. At least the data of the past power flow power and the reverse power flow power can improve the prediction accuracy of the target consumer 300B.

Further, the control unit 104 may be configured to instruct the target consumer to keep the amount of electric power purchased constant during the target time zone.

Further, the control unit 104 may be configured not to perform the above-mentioned control when the prediction accuracy of the target consumer exceeds a predetermined threshold value.

For example, as shown in FIG. 6, the control unit 104 described above in a time zone (for example, 12:00 to 15:00) when the prediction accuracy of the target consumer is equal to or higher than a predetermined threshold value (for example, 90%). It is configured so that it does not control.

In general, the fluctuation of power consumption is small during the time when the resident of the consumer 300 is out or sleeping, so the past data necessary for predicting the past power flow power and the reverse power flow power of the target consumer 300B. Is few. Therefore, the control unit 104 is configured to exclude the time zone in which the prediction accuracy of the target consumer is equal to or higher than the predetermined threshold value from the target time zone, and set another time zone as the target time zone. Then, the control unit 104 is configured to exclude the target consumer 300 from the target customer when the prediction accuracy of the target consumer exceeds a predetermined threshold value in all time zones.

Further, for example, as shown in FIG. 7, the control unit 104 causes the target consumer to charge the power storage device 301 in the midnight time zone (0:00 to 8:00), and 9:00 to 12:00. You may instruct to perform load tracking control in the time zone of.

Hereinafter, an example of the operation of the server device 100 according to the embodiment will be described with reference to FIG.

As shown in FIG. 8, in step S101, the server device 100 detects the participation of a new customer 300 or the change of the device configuration in the existing customer 300 as the occurrence of a predetermined event. Here, the consumer 300 in which the occurrence of the predetermined event is detected is defined as the "target consumer A".

In step S102, the server device 100 calculates the prediction accuracy of all the consumers other than the target consumer A for each time zone. Here, each time zone in which the prediction accuracy is calculated is referred to as "time zone T".

Hereinafter, the server device 100 performs the processes of steps S103 to S108 for all the target consumers A.

In step S103, the server device 100 calculates the prediction accuracy of the target consumer A for each time zone.

In step S104, the server device 100 calculates the duration of the power storage device 301 of the target consumer A.

Hereinafter, the server device 100 arranges the time zones T in the order of poor prediction accuracy of the target consumer A, and performs the processes of steps S105 to S108 for all the time zones T.

In step S105, the server device 100 determines whether or not there is a planned remaining amount of the power storage device 301 of the target consumer A. In the case of Yes, this operation proceeds to step S106, and in the case of No, this operation ends the processing for the current target customer A and starts the processing for the next target customer A.

In step S106, the server device 100 determines whether or not the prediction accuracy of the target consumer A is equal to or greater than a predetermined threshold value. If No, this operation proceeds to step S107, and if Yes, this operation ends the processing for the current time zone T and starts the processing for the next time zone T.

In step S107, the server device 100 creates a charge / discharge plan for the target consumer A in the time zone T as a control plan for the target consumer A in the time zone T. For example, the server device 100 satisfies the limits of the remaining amount of the power storage device 301 and the rated output with respect to the predicted amount of power consumption and the predicted amount of photovoltaic power generation for each demand time period, and the optimum electricity charge is the DR possible amount. The charge / discharge plan of the target consumer A may be created so as to be. Here, the time particle size of the charge / discharge plan may be larger or smaller than the demand time limit.

In step S108, the server device 100 updates the planned remaining amount of the power storage device 301 of the target consumer A. Here, the server device 100 instructs the target customer A who does not have the distributed power supply 302 to perform load tracking control in the time zone T, and the target demand having the distributed power supply 302. The house A is instructed to sell all the power generated by the distributed power supply 302 (that is, it is instructed to control the total power sale).

Here, the server device 100 updates the planned remaining amount of the power storage device 301 of the target customer A so as to reflect the change in the remaining amount of the power storage device 301 due to the load tracking control and the total power sale control described above.

According to the power system 1 according to the present embodiment, the server device 100 can avoid a decrease in the prediction accuracy of the consumer 300 and report an appropriate DR possible amount to the aggregation coordinator 200.

Further, according to the electric power system 1 according to the present embodiment, the prediction accuracy of the consumer 300 can be improved without preparing a complicated algorithm having a high calculation cost and a wide variety of learning data.

1 ... Electric power system 10 ... Communication network 100 ... Server device 101 ... Detection unit 102 ... Storage unit 103 ... Calculation unit 104 ... Control unit 200 ... Aggregation coordinator 300, 300A, 300B ... Consumer 301 ... Power storage device 302 ... Distributed power supply 303 ... Load device 304 ... EMS

Claims (7)

When the occurrence of a predetermined event is detected, the power flow power of the target consumer who is the consumer who detected the occurrence of the predetermined event based on the prediction accuracy of the power flow power and the reverse power flow power of the consumer by time zone. A server device having a control unit that controls fluctuations in at least one of reverse power flow. The server device according to claim 1, wherein the predetermined event includes at least one of participation of a new consumer and change of equipment configuration in an existing consumer. The control unit instructs the target consumer who has a power storage device and does not have a distributed power source to perform load tracking control in the target time zone for performing the control, claim 1 or 2. The server device according to 2. The control unit instructs the target consumer who has the power storage device and the distributed power source to sell all the electric power generated by the distributed power source in the target time zone for performing the control. The server device according to any one of claims 1 to 3. The server according to any one of claims 1 to 4, wherein the control unit instructs the target consumer to keep the amount of power to be purchased constant during the target time zone for performing the control. apparatus. The server device according to any one of claims 1 to 5, wherein the control unit does not perform the control when the prediction accuracy of the power flow power and the reverse power flow power in the target consumer exceeds a predetermined threshold value. When the occurrence of a predetermined event is detected, the power flow power of the target consumer who is the consumer who detected the occurrence of the predetermined event based on the prediction accuracy of the power flow power and the reverse power flow power of the consumer by time zone. And a control method having a method of performing control for suppressing fluctuation of at least one of reverse power flow power.

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