Power trading system, power trading method, power trading device, control device, and program

Abstract

To suppress a cost of power procurement for retail electricity providers.SOLUTION: A power trading system according to one embodiment of the present disclosure that supports bidding by retail electricity providers, includes: an acquisition unit that acquires demand result information indicating the power demand result of consumers, charge / discharge result information indicating the charge / discharge result of a storage battery, and contract price result information indicating the contract price result of the power; a demand prediction unit that predicts power demand on the basis of the demand result information; a charge / discharge prediction unit that predicts the charge amount and the discharge amount of the storage battery on the basis of the charge / discharge result information; a contract price prediction unit that predicts the contract price of the power on the basis of the contract price result information; and a creation unit that creates control information for controlling the charging and discharging of the storage battery for suppressing power costs for the bidding of the retail electricity provider, and bidding information for enabling the retail electricity provider to place bids, on the basis of the predicted power demand, predicted charge / discharge amounts, and predicted contract price.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to an energy trading system, an energy trading method, an energy trading device, a control device, and a program. [Background technology]

[0002] Virtual Power Plant (VPP) systems are known for utilizing distributed energy resources (DERs), including electric vehicles (EVs), stationary storage batteries, and solar panels. The VPP system links distributed energy resources scattered across various locations under an aggregator system, making them function as if they were a single power plant. VPP aggregator operators control distributed energy resources by implementing centralized management via the cloud or other means for consumers, in accordance with requests from retail electricity operators and electricity transmission and distribution operators. Retail electricity operators supply electricity purchased from the wholesale electricity market to consumers in the VPP.

[0003] The distributed energy resource management device described in Patent Document 1 predicts the load power amount and power generation amount of solar power panels for each consumer using received power, power generation amount of solar power panels, actual charging and discharging values ​​of stationary storage batteries, actual charging and discharging values ​​of EVs, etc., and creates an hourly EV charging and discharging plan that minimizes the consumer's electricity bill using these predicted values, the specifications of the storage batteries installed in the EVs, and the usage status of the EV. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2022-50126 Summary of the Invention [Problem to be solved by the invention]

[0005] The distributed energy resource management device described in Patent Document 1 creates an hourly charging and discharging plan for EVs that minimizes electricity charges for consumers, and does not take into account the costs for retail electricity companies to procure electricity.

[0006] The present disclosure has been made in consideration of the above circumstances, and aims to provide an electricity trading system, an electricity trading method, an electricity trading device, a control device, and a program that can reduce the costs for electricity retailers to procure electricity. [Means for solving the problem]

[0007] The present disclosure has been made to solve the above-mentioned problems, and one aspect of the present disclosure is an electricity trading system that supports the bidding of electricity retailers that conduct electricity bidding and supply electricity to consumers and storage batteries, the electricity trading system comprising: an acquisition unit that acquires demand record information that indicates the actual electricity demand of the consumers, charge and discharge record information that indicates the charge and discharge record of the charging and discharging of the storage battery, and contract price record information that indicates the actual contract price of electricity; a demand prediction unit that predicts electricity demand based on the demand record information acquired by the acquisition unit; a charge and discharge prediction unit that predicts the charge and discharge amount of the storage battery based on the charge and discharge record information acquired by the acquisition unit; an agreement price prediction unit that predicts the agreement price of electricity based on the agreement price record information acquired by the acquisition unit; and a creation unit that creates control information for controlling the charging and discharging of the storage battery so as to reduce electricity costs for the bid of the electricity retailer, and bid information for the electricity retailer to conduct the bidding, based on the electricity demand predicted by the demand prediction unit, the charge and discharge amount predicted by the charge and discharge prediction unit, and the agreement price predicted by the agreement price prediction unit.

[0008] Another aspect of the present disclosure is an electricity trading method for supporting the bidding of an electricity retailer that conducts electricity bidding and supplies electricity to consumers and storage batteries, the electricity trading method having the steps of acquiring demand record information indicating the actual electricity demand of the consumer, charge / discharge record information indicating the charge / discharge record of the charging and discharging of the storage battery, and contract price record information indicating the actual contract price of electricity, predicting electricity demand based on the demand record information, predicting the charge and discharge amount of the storage battery based on the charge / discharge record information, predicting the contract price of electricity based on the contract price record information, and creating, based on the predicted electricity demand, the predicted charge and discharge amounts, and the predicted contract price, control information for controlling the charging and discharging of the storage battery so as to reduce electricity costs for the bid of the electricity retailer and bidding information for the electricity retailer to conduct the bidding.

[0009] Another aspect of the present disclosure is a program that causes a computer of an electricity trading device that conducts electricity bidding and supports the bidding of electricity retailers that supply electricity to consumers and storage batteries to execute the following steps: acquiring demand record information that indicates the actual electricity demand of the consumers, charge and discharge record information that indicates the charge and discharge record of the charging and discharging of the storage battery, and contract price record information that indicates the actual contract price of electricity; predicting electricity demand based on the demand record information; predicting the charge and discharge amount of the storage battery based on the charge and discharge record information; predicting the contract price of electricity based on the contract price record information; and creating, based on the predicted electricity demand, the predicted charge and discharge amounts, and the predicted contract price, control information for controlling the charging and discharging of the storage battery so as to reduce electricity costs for the bid of the electricity retailer and bidding information for the electricity retailer to conduct the bidding.

[0010] Another aspect of the present disclosure is an energy trading device that supports the bidding of an electricity retailer that conducts electricity bidding and supplies electricity to consumers and storage batteries, the energy trading device comprising: an acquisition unit that acquires demand record information indicating the electricity demand record of the consumer, charge / discharge record information indicating the charge / discharge record of the charging and discharging of the storage battery, and contract price record information indicating the contract price record of the electricity; a demand prediction unit that predicts electricity demand based on the demand record information acquired by the acquisition unit; a charge / discharge prediction unit that predicts the charge amount and discharge amount of the storage battery based on the charge / discharge record information acquired by the acquisition unit; an agreement price prediction unit that predicts the agreement price of electricity based on the agreement price record information acquired by the acquisition unit; and a creation unit that creates bidding information for the electricity retailer to conduct a bidding so as to reduce electricity costs for the bid of the electricity retailer, based on the electricity demand predicted by the demand prediction unit, the charge amount and discharge amount predicted by the charge / discharge prediction unit, and the agreement price predicted by the agreement price prediction unit.

[0011] Another aspect of the present disclosure is a control device for controlling a consumer and a storage battery, the control device comprising: an acquisition unit that acquires demand record information indicating the consumer's actual electricity demand, charge / discharge record information indicating the charge / discharge record of the charging and discharging of the storage battery, and agreement price record information indicating the actual agreement price of electricity; a demand prediction unit that predicts electricity demand based on the demand record information acquired by the acquisition unit; a charge / discharge prediction unit that predicts the charge and discharge amount of the storage battery based on the charge / discharge record information acquired by the acquisition unit; an agreement price prediction unit that predicts the agreement price of electricity based on the agreement price record information acquired by the acquisition unit; and a creation unit that creates control information for controlling the charging and discharging of the storage battery so as to reduce electricity costs for a bid by a retail electricity supplier, based on the electricity demand predicted by the demand prediction unit, the charge and discharge amount predicted by the charge / discharge prediction unit, and the agreement price predicted by the agreement price prediction unit.

[0012] Another aspect of the present disclosure is a program that causes a computer of an electricity trading device that conducts electricity bidding and supports the bidding of electricity retailers that supply electricity to consumers and storage batteries to execute the following steps: acquiring demand record information that indicates the actual electricity demand of the consumers, charge and discharge record information that indicates the charge and discharge record of the charging and discharging of the storage battery, and contract price record information that indicates the actual contract price of electricity; a demand prediction unit that predicts electricity demand based on the demand record information; predicting the charge and discharge amounts of the storage battery based on the charge and discharge record information; predicting the contract price of electricity based on the contract price record information; and creating bidding information for the electricity retailer to conduct the bidding based on the predicted electricity demand, the predicted charge and discharge amounts, and the predicted contract price, so as to reduce electricity costs for the bid of the electricity retailer.

[0013] The program causes a computer of a control device that controls consumers and storage batteries to execute the following steps: acquiring demand record information indicating the actual electricity demand of the consumers, charge / discharge record information indicating the charging and discharging record of the storage battery, and contract price record information indicating the actual contract price of electricity; predicting electricity demand based on the demand record information; predicting the charge and discharge amounts of the storage battery based on the charge / discharge record information; predicting the contract price of electricity based on the contract price record information; and creating control information for controlling the charging and discharging of the storage battery so as to reduce electricity costs for bids from retail electricity suppliers based on the predicted electricity demand, predicted charge and discharge amounts, and predicted contract price. Effect of the Invention

[0014] According to one aspect of the present invention, the cost for electricity retailers to procure electricity can be reduced. [Brief description of the drawings]

[0015] [Figure 1] FIG. 1 is a block diagram showing an example of an energy trading system 1 according to an embodiment. [Diagram 2] FIG. 2 is a sequence diagram showing a processing procedure performed by the energy trading system 1 according to the embodiment. [Diagram 3] FIG. 1 is a block diagram showing an example of a specific configuration of an energy trading system 1 according to an embodiment. [Figure 4] 5A to 5C are diagrams illustrating an example of actual information on EV entry and exit and actual information on remaining battery charge in the embodiment. [Diagram 5] FIG. 4 is a diagram showing an example of calendar data according to the embodiment. [Figure 6] 13 is a diagram showing an example of EV entrance / exit prediction information 122 and an EV exit power consumption prediction value 124 according to the embodiment. [Figure 7] 11 is a diagram showing an example of weather forecast data, power at a power receiving point [kW], charge / discharge power [kW] of an electric vehicle 200A, and power generation power [kW] of a solar power generation facility 200C in the embodiment. FIG. [Figure 8] FIG. 4 is a diagram showing an example of a predicted value [kW] of power demand and a predicted value [kW] of generated power for the next day in the embodiment. [Figure 9] 3A to 3C are diagrams illustrating an example of actual weather data, a history of electricity prices in the spot market, and a history of electricity prices in the ahead market in an embodiment. [Figure 10] FIG. 2 is a diagram showing an example of a predicted value of electricity price in the spot market and a predicted value of electricity price in the hourly market in the embodiment. [Figure 11] FIG. 4 is a diagram showing an example of a charge / discharge plan for an n-th electric vehicle 200A in the embodiment. [Figure 12] 1 is a diagram showing expected values ​​of bid volumes for the hourly market and bid volumes for the spot market in an embodiment. FIG. [Figure 13] FIG. 11 is a diagram showing an example of the charge / discharge amount of an n-th electric vehicle 200A in the embodiment. [Figure 14] 1 is a diagram showing expected values ​​of bid volumes for the hourly market and bid volumes for the spot market in an embodiment. FIG. [Figure 15] FIG. 13 is a block diagram showing a modified example of an energy trading system. [Figure 16] FIG. 13 is a block diagram showing an energy trading system according to a second modified example. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] An energy trading system, an energy trading method, an energy trading device, a control device, and a program to which the present invention is applied will be described below with reference to the drawings.

[0017] FIG. 1 is a block diagram showing an example of an energy trading system 1 according to an embodiment. The energy trading system 1 is a system that supports trading by an electricity retailer that carries out electricity bidding and supplies electricity to a consumer facility 200, an electric vehicle 200A, and a storage battery 200B. The energy trading system 1 includes, for example, an energy trading device 100, a VPP (Virtual Power Plant) including the consumer facility 200, an energy trading server device 300, and an information providing server device 400. The VPP includes a plurality of consumer facilities 200. The energy trading device 100, the consumer facility 200, the energy trading server device 300, and the information providing server device 400 each have a communication interface (not shown) such as a network interface card (NIC) or a wireless communication module for connecting to a network such as the Internet. The network may include, for example, a general-purpose network such as the Internet, and a private network such as local 5G or WiFi (registered trademark).

[0018] The energy trading device 100 is an information processing device operated by a business operator who serves both as an aggregator business operator and an electricity retailer. The consumer facility 200 is a facility owned by a consumer. A distributed power source such as an electric vehicle (EV) 200A, a storage battery 200B, or a photovoltaic power generation facility (PV) 200C may be connected to the consumer facility 200. The distributed power source may be an energy resource distributed in a region such as a production facility, a private power generation facility, or a storage battery owned by an individual or a company, or a consumer-side energy management system that controls the energy resource. The energy trading server device 300 is a server device that operates a market in which electricity is traded. The energy trading server device 300 is, for example, a server device operated by the Japan Electric Power Exchange, but is not limited thereto. The energy trading server device 300 may be a server device operated by a power generation business operator that sells electricity to an electricity retailer. The information providing server device 400 is a server device that provides information used to predict the demand for electricity and the contract price of electricity, such as weather forecast data.

[0019] The energy trading device 100 is an information processing device that communicates with other devices and performs various processes. The energy trading device 100 includes, for example, an acquisition unit 101, a demand forecasting unit 102, a charge / discharge forecasting unit 103, an agreement price forecasting unit 104, and a creation unit 105. The acquisition unit 101, the demand forecasting unit 102, the charge / discharge forecasting unit 103, the agreement price forecasting unit 104, and the creation unit 105 are realized, for example, by a processor such as a CPU (Central Processing Unit) executing a program stored in a program memory.

[0020] The acquisition unit 101, the demand prediction unit 102, the charge / discharge prediction unit 103, the contract price prediction unit 104, and the creation unit 105 may be integrated and arranged in one device, or may be distributed and arranged in a plurality of devices. For example, the acquisition unit 101, the demand prediction unit 102, the charge / discharge prediction unit 103, and the contract price prediction unit 104 may be provided in one device, and the creation unit 105 may be provided in another device. For example, the acquisition unit 101, the demand prediction unit 102, the charge / discharge prediction unit 103, and the creation unit 105 may be provided in one device, and the contract price prediction unit 104 may be provided in another device.

[0021] The acquiring unit 101 acquires demand record information indicating the actual power demand of the customer facility 200, charge / discharge record information indicating the charge / discharge record of the storage battery facility 200B, and contract price record information indicating the contract price record of the power. The storage battery facility 200B may include a storage battery mounted on an electric vehicle 200A. The demand record information is, for example, information indicating the relationship between the date and time and the power consumption amount for each customer facility 200. The charge / discharge record is, for example, information indicating the relationship between the date and time and the charge amount and the power generation amount for each storage battery facility 200B. The contract price record is at least one of information indicating the relationship between the date and time and the contract price in the spot market and information indicating the relationship between the date and time and the contract price in the hour-ahead market. The demand forecasting unit 102 forecasts the power demand based on the demand record information acquired by the acquisition unit 101 . The charge / discharge prediction unit 103 predicts the charge amount and discharge amount of the storage battery 200B based on the charge / discharge record information acquired by the acquisition unit 101. The contract price prediction unit 104 predicts the contract price of electricity based on the contract price performance information acquired by the acquisition unit 101 . The creation unit 105 creates control information for controlling the charging and discharging of the storage battery 200B so as to suppress the power cost for the bid of the retail electricity supplier, and bidding information for the retail electricity supplier to carry out a bid, based on the power demand predicted by the demand prediction unit 102, the charge amount and discharge amount predicted by the charge and discharge prediction unit 103, and the contract price predicted by the contract price prediction unit 104. The power cost for the bid of the retail electricity supplier is determined by the contract unit price and the contracted amount of power. The control information is a charge and discharge plan and a control command value as described later. The charge and discharge plan is, for example, information that associates time with the charge amount and the discharge amount. The control command value indicates, for example, a charge and discharge start command, an end command, a charge and discharge voltage, and a charge and discharge current for operating the customer facility 200, the electric vehicle 200A, and the storage battery 200B. The bidding information is information indicating the time and amount of power to be bid on the spot market as described later, and information indicating the time and amount of power to be bid on the time-ahead market. The acquisition unit 101 may acquire power generation record information indicating the amount of power generated by the photovoltaic power generation facility 200C, and the charge / discharge prediction unit 103 may predict the amount of power generated.

[0022] FIG. 2 is a sequence diagram showing a processing procedure performed by the energy trading system 1 according to the embodiment. The energy trading device 100 performs the following process to create the charge / discharge plan and bidding information for the next day. The customer facility 200 transmits demand record information, charge / discharge record information, and power generation record information to the energy trading device 100 (step S10), and the acquisition unit 101 acquires the demand record information, charge / discharge record information, and power generation record information. The energy trading device 100 stores the contract price record including the bidding information and the contract information in the spot market. The demand forecast unit 102 predicts the power demand for the next day based on the demand record information, and the charge / discharge forecast unit 103 predicts the charge amount and the discharge amount of the storage battery 200B and the electric vehicle 200A for the next day based on the charge / discharge record information, and predicts the power generation amount for the next day based on the power generation record information (step S12). The contract price forecast unit 104 predicts the contract price for the next day based on the stored contract price record (step S12). The creation unit 105 creates a charge / discharge plan for the storage battery 200B and the electric vehicle 200A for the next day based on the power demand for the next day, the predicted charge and discharge amounts for the next day, and the power generation amount for the next day so as to suppress the power cost for the electricity retailer's bid to the spot market, and creates a bidding plan for the spot market as bidding information (step S14). The energy trading device 100 transmits bidding information to the energy trading server device 300 in accordance with the created bidding plan, and receives contract information indicating information on the contracted amount of power. The energy trading device 100 finalizes the charge / discharge plans for the storage battery 200B and the electric vehicle 200A based on the contracted amount of power (step S16). The charge / discharge plans for the storage battery 200B and the electric vehicle 200A for the next day are an example of control information for controlling the charging and discharging of the storage battery 200B and the electric vehicle 200A.

[0023] The energy trading device 100 performs the following process to create the control command value and bidding information for the day. The customer facility 200 transmits the demand record information, the charge / discharge record information, and the power generation record information for the day to the energy trading device 100 (step S18), and the acquisition unit 101 acquires the demand record information, the charge / discharge record information, and the power generation record information for the day. The energy trading device 100 stores the bidding information and the contract price record including the contract information in the afore-hour market. The demand forecasting unit 102 predicts the power demand for the day based on the demand record information for the day, and the charge / discharge forecasting unit 103 predicts the charge amount and the discharge amount of the storage battery 200B and the electric vehicle 200A for the day based on the charge / discharge record information for the day, and predicts the power generation amount for the day based on the power generation record information (step S20). The contract price forecasting unit 104 predicts the contract price in the afore-hour market for the day based on the contract price record in the afore-hour market (step S20). The creation unit 105 creates control command values ​​for the storage battery 200B and the electric vehicle 200A based on the power demand for that day, the predicted charge and discharge amounts for that day, and the power generation amount for that day so as to suppress the imbalance cost based on the difference between the power demand for that day and the charge and discharge plans of the storage battery 200B and the electric vehicle 200A, and creates a bidding plan for the hour-ahead market as bidding information (step S22). The energy trading device 100 transmits bidding information to the energy trading server device 300 according to the created bidding plan, and receives contract information indicating the contracted amount of power. The creation unit 105 determines the control command values ​​for the storage battery 200B and the electric vehicle 200A based on the contracted amount of power (step S24). The control command values ​​for the storage battery 200B and the electric vehicle 200A for that day are an example of control information for controlling the charging and discharging of the storage battery 200B and the electric vehicle 200A. Energy trading device 100 acquires current state information of electric vehicle 200A and transmits a control command value based on the acquired state information to customer facility 200. The state information of electric vehicle 200A includes, for example, information on the presence or absence of electric vehicle 200A and information on the amount of charge. Customer facility 200 operates in accordance with the control command value and sends a response back to energy trading device 100.

[0024] Fig. 3 is a block diagram showing an example of a specific configuration of an energy trading system 1 according to an embodiment. The energy trading system 1 in Fig. 3 mainly charges and discharges an electric vehicle 200A. The energy trading system 1 includes, for example, an EV operation prediction unit 110, a PV power generation and demand prediction unit 112, an electricity market price prediction unit 114, an EV charge and discharge plan creation unit 116, and an EV charge and discharge command value creation unit 118. The EV operation prediction unit 110 is an example of the charge and discharge prediction unit 103, the PV power generation and demand prediction unit 112 is an example of the above-mentioned function of predicting power generation and the demand prediction unit 102, the electricity market price prediction unit 114 is an example of the contract price prediction unit 104, and the EV charge and discharge plan creation unit 116 and the EV charge and discharge command value creation unit 118 are examples of the creation unit 105.

[0025] The EV operation prediction unit 110, the PV power generation amount / demand prediction unit 112, the electricity market price prediction unit 114, the EV charge / discharge plan creation unit 116, and the EV charge / discharge command value creation unit 118 are realized by a processor such as a CPU executing a program stored in a program memory. Note that the EV operation prediction unit 110, the PV power generation amount / demand prediction unit 112, the electricity market price prediction unit 114, the EV charge / discharge plan creation unit 116, and the EV charge / discharge command value creation unit 118 may be integrated and arranged in one device, or may be distributed and arranged in multiple devices.

[0026] The energy trading device 100 performs various processes using various information stored in a storage device (not shown). The storage device stores, for example, EV performance information 120, EV entry / exit prediction information 122, EV power consumption prediction value during EV exit 124, demand / charging / discharging / power generation performance information 126, PV specification data 128, weather performance / prediction data 130, demand / power generation prediction value 134, power market price performance 132, power market price prediction value 136, EV specification data 138, EV charge / discharge plan information 140, spot market bid amount 142, target SOC (State Of Charge) / target time information 144, power retail parameters 146, constraint violation parameters 148, procured power amount 150, EV current state information 152, EV control command value 154, and time-ahead market bid amount 156. The storage device may be installed in the energy trading device 100, may be connected to the energy trading device 100 via a communication network NW or a private network, may be concentrated in one storage device, or may be distributed across any number of storage devices.

[0027] The EV operation prediction unit 110 makes predictions based on the EV entry / exit record information, remaining power record information, and calendar data included in the EV record information 120, and creates EV entry / exit prediction information 122 and EV exit power consumption prediction value 124. The EV entry / exit record information is information indicating the entry / exit record of the electric vehicle 200A. The EV entry / exit record information is information including, for example, the exit time when the electric vehicle 200A is disconnected from the charging connector, and the entry time when the electric vehicle 200A is connected to the charging connector. The remaining power record information is information indicating the record of the remaining power [kWh] of the electric vehicle 200A. The calendar data is information including, for example, the date, the day of the week, holidays, and daily schedule information. The EV entry / exit prediction information 122 is information predicting the presence or absence of the electric vehicle 200A. The EV exit power consumption prediction value 124 is information predicting the power consumption of the electric vehicle 200A while it is leaving the garage. Fig. 4 is a diagram showing an example of EV entry / exit record information and remaining power record information in the embodiment. Fig. 5 is a diagram showing an example of calendar data in the embodiment. Fig. 6 is a diagram showing an example of EV entry / exit prediction information 122 and EV exit power consumption prediction value 124 in the embodiment.

[0028] EV operation prediction unit 110 is realized, for example, by executing a machine learning engine. The machine learning engine learns, for example, using previously acquired EV performance information 120 as learning data. EV operation prediction unit 110 inputs the latest EV entry / exit performance information, remaining power performance information, and calendar data stored at the time of prediction to the machine learning engine, and predicts the presence or absence of electric vehicle 200A and power consumption while it is leaving the facility based on the information output from the machine learning engine.

[0029] The PV power generation and demand prediction unit 112 makes a prediction based on the demand, charge / discharge, and power generation record information 126, the PV specification data 128, and the weather record and forecast data 130, and creates a demand and power generation forecast value 134. The demand, charge / discharge, and power generation record information 126 includes the power demand record at the power receiving point (customer facility 200), the charge / discharge record of the electric vehicle 200A, and the power generation record of the photovoltaic power generation facility 200C. The PV specification data 128 includes data such as the power generation capacity, installation angle, overload rate, and power generation efficiency of the photovoltaic power generation facility 200C. The weather record and forecast data 130 is data such as weather, temperature, and solar radiation intensity. The demand and power generation forecast value 134 is the forecast value [kW] of the power demand for the time and the forecast value [kW] of the power generation amount of the photovoltaic power generation facility 200C. Fig. 7 is a diagram showing an example of weather forecast data, power at receiving point [kW], charge / discharge power [kW] of electric vehicle 200A, and generated power [kW] of solar power generation facility 200C in the embodiment. Fig. 8 is a diagram showing an example of a predicted value of power demand [kW] and a predicted value of generated power [kW] for the next day in the embodiment. The predicted value of power demand is a value that predicts the true power demand in customer facility 200, taking into account the power at receiving point, the charge / discharge amount of electric vehicle 200A, and the power generation amount of solar power generation facility 200C.

[0030] The PV power generation and demand prediction unit 112 is realized, for example, by executing a machine learning engine. The machine learning engine learns, for example, previously acquired demand, charge and discharge, and power generation record information 126 and PV specification data 128 as learning data. The PV power generation and demand prediction unit 112 inputs the latest demand, charge and discharge, and power generation record information 126, PV specification data 128, and weather record and forecast data 130 stored at the time of prediction to the machine learning engine, and creates a demand and power generation prediction value 134 based on the information output from the machine learning engine.

[0031] The electricity market price prediction unit 114 makes a prediction based on the weather record / forecast data 130 and the electricity market price record 132, and creates an electricity market price prediction value 136. The electricity market price record 132 includes a history of electricity prices in the spot market and a history of electricity prices in the hour-ahead market. The electricity price in the hour-ahead market may be a representative value obtained by averaging the prices that fluctuated within one hour, for example. The electricity market price prediction value 136 includes a predicted value of the electricity price in the spot market for the time and a predicted value of the electricity price in the hour-ahead market. Fig. 9 is a diagram showing an example of actual weather data, a history of electricity prices in the spot market, and a history of electricity prices in the afore-hours market in an embodiment. Fig. 10 is a diagram showing an example of a predicted value of electricity prices in the spot market and a predicted value of electricity prices in the afore-hours market in an embodiment.

[0032] The electricity market price prediction unit 114 is realized, for example, by executing a machine learning engine. The machine learning engine learns, for example, previously acquired weather record / forecast data 130 and electricity market price record 132 as learning data. The electricity market price prediction unit 114 inputs the latest weather record / forecast data 130 and electricity market price record 132 stored at the time of prediction to the machine learning engine, and creates an electricity market price prediction value 136 based on information output from the machine learning engine.

[0033] The EV charge / discharge plan creation unit 116 creates EV charge / discharge plan information 140 and spot market bid amount 142 based on the power market price forecast value 136, EV specification data 138, target SOC / target time information 144, power retail parameters 146, constraint violation parameters 148, and procured power amount 150. The EV specification data 138 includes, for example, a charge / discharge output upper limit value, an SOC operation upper limit value and a SOC operation lower limit value, a charge / discharge efficiency, a PCS (power conditioner) conversion efficiency, a charge output suppression parameter, and a charge cycle upper limit value. The target SOC / target time information 144 is data indicating a target SOC of the electric vehicle 200A for a target time. The power retail parameters 146 are parameters related to the spot market and the time-ahead market. The constraint violation parameters 148 include information that is a violation of constraints such as SOC upper and lower limit constraints, target SOC constraints, and cycle charging constraints. The procured power amount 150 is data indicating the amount of power already procured by the retail electricity business operator. The EV charge / discharge plan information 140 indicates a charge / discharge plan that indicates the charge and discharge amounts of the electric vehicle 200A with respect to time. The spot market bid amount 142 indicates the amount of power (bid amount) with respect to the time of bidding in the spot market.

[0034] Fig. 11 is a diagram showing an example of a charge / discharge plan for the n-th electric vehicle 200A in the embodiment. Fig. 12 is a diagram showing an expected value of the bid amount for the hour-ahead market and the bid amount for the spot market in the embodiment. The EV charge / discharge plan creation unit 116 creates a charge / discharge plan for the day as shown in Fig. 11, for example, and creates an expected value of the bid amount for the hour-ahead market required for the charge / discharge plan for the day. The EV charge / discharge plan creation unit 116 creates a bidding plan indicating the bid amount for the spot market based on the charge / discharge plan from the current time onwards on the next day and the expected value of the bid amount for the hour-ahead market.

[0035] The EV charging / discharging plan creation unit 116 may optimize the charging / discharging plan of electric vehicle 200A for the next day and the bidding plan for the spot market so as to suppress the power cost for bidding for the spot market. Specifically, as shown in the following formulas 1 to 5, a mathematical optimization problem is formulated that minimizes the power procurement costs of the electricity retailer for the current day, the next day, and the day after that. The EV charging / discharging plan creation unit 116 optimizes the charging / discharging plan of electric vehicle 200A and the bid amount for the spot market by solving formulas 1 to 5 using a mathematical optimization solver.

[0036] Equation 1 is an equation obtained by adding the power procurement cost (contract price) and the violation constraint penalty. Equation 2 is an equation for calculating the remaining battery charge of electric vehicle 200A. Equations 3 and 4 are equations for calculating the supply and demand balance constraint. Equation 5 is an equation for calculating the constraint on the target SOC at the target time. The EV charge and discharge plan creation unit 116 calculates the remaining battery charge bat n (t), power consumption at customer facility 200(m) d m use (t), and the amount of reverse power flow in the customer facility 200 d m send (t) is an auxiliary variable, the amount of electricity to be bid tr(t) is the amount of charge e at time t in the n-th electric vehicle 200A, n cha (t) and discharge amount e n dis The calculation is performed with the EV charge / discharge plan creation unit 116 setting the bid amount of power tr(t) and the charging amount e n cha (t) and discharge amount e n dis Calculate to optimize (t).

number

[0037] F epx(t) is the predicted value of the contract price at time t. tr(t) indicates the amount of power to be bid. T is the period for which the contract price is predicted. bat(t) is the remaining battery charge of the n-th electric vehicle 200A. e n cha (t) and e n dis (t) is the charge and discharge amount of the n-th electric vehicle 200A at time t. η cha and η dis indicates the charge and discharge efficiency, and E n dri (t) is the amount of power consumed by the n-th electric vehicle 200A at time t while the electric vehicle 200A is leaving the parking lot. m use (t), d m send (t) is the power consumption and reverse power flow rate of the customer facility 200 or (m) at time t. P m true (t) is the true demand power of the customer facility 200(m) at time t. P m ev (t) is the amount of power generated by the photovoltaic power generation facility 200C of the customer facility 200(m) at time t. G m EV indicates a set of electric vehicles 200A owned by customer equipment 200(m). sec (t) is the amount of electricity procured at time t. G cons denotes a set of customer facilities 200. send denotes the loss rate of the wheeling. n,m and SOC n,m are the m-th target time and the target SOC in the n-th electric vehicle 200A. n is the rated capacity of the storage battery mounted on the n-th electric vehicle 200A. n,m The SOC is the amount of violation of the constraints of the mth target time and the target SOC in the nth electric vehicle 200A.

[0038] In addition, the formula is not limited to formulas 1 to 5, and formulas such as a formula for calculating SOC, upper and lower limit values ​​of SOC, a formula for suppressing charge / discharge output according to SOC, upper and lower limit values ​​of charge / discharge output reflecting the current state of electric vehicle 200A and a prediction of whether electric vehicle 200A is present or absent, and an upper limit of the total daily charge amount taking into account the cycle life of the storage battery installed in electric vehicle 200A may be added.

[0039] EV charge / discharge command value creation unit 118 creates EV control command value 154 and time-ahead market bid amount 156 based on EV entry / exit prediction information 122, EV power consumption during exit prediction value 124, demand / power generation prediction value 134, electricity market price prediction value 136, EV specification data 138, target SOC / target time information 144, electricity retail parameters 146, constraint violation parameters 148, procured energy amount 150, and EV current state information 152. EV current state information 152 is information indicating the current state of electric vehicle 200A. EV current state information 152 includes, for example, the SOC of a storage battery mounted on electric vehicle 200A and information indicating the presence or absence of electric vehicle 200A.

[0040] Fig. 13 is a diagram showing an example of the charge / discharge amount of the nth electric vehicle 200A in the embodiment. Fig. 14 is a diagram showing expected values ​​of the bid amount for the afore-hour market and the bid amount for the spot market in the embodiment. As shown in Fig. 13, the EV charge / discharge command value creation unit 118 creates EV control command values ​​from the control target time to the current day (0:00) at the current time. The EV charge / discharge command value creation unit 118 creates a plan for the bid amount for the afore-hour market from immediately after gate close (GC) to the current day at the current time.

[0041] EV charge / discharge command value creation unit 118 creates a control command value for electric vehicle 200A and a bidding plan for the time-ahead market so as to suppress the imbalance fee based on the difference between the amount of power bid in the spot market and the power demand on the day and the power cost for bidding in the time-ahead market. Specifically, as shown in the following formulas 6, 2, 3, 7, and 5, a mathematical optimization problem is formulated to minimize the imbalance fee and the power cost for bidding in the time-ahead market. EV charge / discharge command value creation unit 118 optimizes the control command value for electric vehicle 200A and the bidding plan for the time-ahead market by solving formulas 6, 2, 3, 7, and 5 using a mathematical optimization solver.

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[0042] Equation 6 is the sum of the power procurement cost (contract price) and the violation constraint penalty in addition to equation 1, which adds the shortage imbalance amount s dem- (t) and the shortfall imbalance settlement price F imb- (t), surplus imbalance amount s dem+ (t) and the liquidation price of the excess imbalance F imb+ This is a formula that takes into account the most recent charge amount e n cha (t) and discharge amount e n dis The optimal value of (t) is set as the control command value for electric vehicle 200A. Equation 7 is a calculation formula for the supply and demand balance constraint, and the amount of shortage imbalance s at time t dem- (t) and the amount of excess imbalance s dem+ The amount of energy to be bid, tr(t), in Equation 7 is calculated so as to be the optimal value at the time immediately before the gate closes, and the calculated amount of energy is set as the bid amount for the hourly market.

[0043] Note that the formulas are not limited to formula 6, formula 2, formula 3, formula 7, and formula 5, and formulas such as a formula for calculating SOC, upper and lower limit values ​​of SOC, a formula for suppressing charge / discharge output according to SOC, upper and lower limit values ​​of charge / discharge output reflecting the current state of electric vehicle 200A and a prediction of whether electric vehicle 200A is present or absent, and an upper limit of the total daily charge amount taking into account the cycle life of the storage battery installed in electric vehicle 200A may be added.

[0044] (Effects of the embodiment) As described above, the energy trading system 1 according to the embodiment creates control information for controlling the charging and discharging of the storage battery (electric vehicle 200A and storage battery 200B) so as to reduce the power cost for the electricity retailer's bid, and bid information for the electricity retailer to conduct a bid, based on the predicted power demand, the predicted charge and discharge amounts, and the predicted contract price, so that the cost of procuring electricity by the electricity retailer can be reduced. Furthermore, the energy trading system 1 according to the embodiment can distribute to consumers a profit according to the reduced power procurement cost by the electricity retailer. The energy trading system 1 can distribute a profit to consumers who have the electric vehicle 200A and storage battery 200B that are subject to control in order to reduce the power procurement cost of the electricity retailer, for example. According to the energy trading system 1 of the embodiment, a charging / discharging plan for the electric vehicle 200A and the storage battery 200B for the next day and a bidding plan for the spot market are created so as to reduce the electricity costs for bidding on the spot market, thereby reducing the costs incurred by the retail electricity supplier to procure electricity from the spot market. Furthermore, according to the energy trading system 1 of the embodiment, control command values ​​for the electric vehicle 200A and the storage battery 200B and a bidding plan for the hour-ahead market are created so as to reduce the imbalance fee based on the amount of energy bid in the spot market and the electricity demand for the day, and the electricity fee for bids in the hour-ahead market, thereby making it possible to reduce the cost for electricity retailers to procure electricity from the hour-ahead market. Furthermore, according to the energy trading system 1 of the embodiment, the entry / exit times of electric vehicle 200A and the power consumption while it is leaving the facility are predicted based on actual entry / exit information and actual remaining power information of electric vehicle 200A, and control information and bidding information are created based on the predicted entry / exit times of electric vehicle 200A and the power consumption while it is leaving the facility, so that the remaining power of electric vehicle 200A can be used to reduce the costs for electricity retailers to procure electricity.

[0045] (First Modification) FIG. 15 is a block diagram showing an energy trading system according to a first modified example. The energy trading system of the first modification includes an energy trading device 100A that creates bidding information and a control device 100B that creates control information. The energy trading device 100A is, for example, an information processing device operated by an electricity retailer. The control device 100B is, for example, an information processing device operated by an aggregator. The bidding information creation unit 105A of the energy trading device 100A has a function of creating the bidding information of the above-mentioned creation unit 105. The energy trading device 100A uses the bidding information to hold electricity bids and support the bids of electricity retailers that supply electricity to the consumer facility 200, the electric vehicle 200A, and the storage battery 200B. The control information creation unit 105B of the control device 100B has a function of creating the control information of the above-mentioned creation unit 105. The control device 100B uses the control information to control the consumer facility 200, the electric vehicle 200A, and the storage battery 200B. Both the energy trading device 100A and the control device 100B are equipped with an acquisition unit 101, a demand prediction unit 102, a charge / discharge prediction unit 103, and an agreement price prediction unit 104, but are not limited to this. One may be equipped with the acquisition unit 101, the demand prediction unit 102, the charge / discharge prediction unit 103, and the agreement price prediction unit 104, and the other may acquire the prediction results of the demand prediction unit 102, the charge / discharge prediction unit 103, and the agreement price prediction unit 104.

[0046] (Second Modification) FIG. 16 is a block diagram showing an energy trading system according to a second modified example. The second modified example includes a price signal setting unit 104# instead of the contract price prediction unit in the energy trading system 1 according to the embodiment. The price signal setting unit 104# sets price signal information indicating the unit price of electricity based on, for example, an operation by an electricity retailer. The unit price of electricity may be a price desired by the electricity retailer. The creation unit 105 creates bidding information and control information using the price signal information instead of the contract price predicted by the contract price prediction unit 104.

[0047] Although the embodiments and variants have been described above, these are merely examples and are not intended to be limiting. For example, any of the embodiments or variants, or a part of each embodiment or a part of each variant, may be combined with one or more other embodiments or one or more other variants to realize one aspect of the present invention. [Explanation of symbols]

[0048] 1...Energy trading system, 100, 100A...Energy trading device, 100B...Control device, 101...Acquisition unit, 102...Demand forecasting unit, 103...Charge / discharge forecasting unit, 104...Agreement price forecasting unit, 104#...Price signal setting unit, 105...Creation unit, 105A...Bidding information creation unit, 105B...Control information creation unit, 110...EV operation prediction unit, 112...PV power generation / demand forecasting unit, 114...Electricity market price prediction unit, 116...EV charge / discharge plan creation unit, 118...EV charge / discharge command value creation unit, 200A...Electric vehicle, 200B...Storage battery, 200C...Photovoltaic power generation facility, 300...Energy trading server device, 400...Information provision server device

Claims

1. An electricity trading system that supports the bidding of electricity retailers that conduct electricity bidding and supply electricity to consumers and storage batteries, comprising: an acquisition unit that acquires demand record information indicating an actual power demand of the customer, charge / discharge record information indicating a charge / discharge record of the storage battery, and contract price record information indicating a contract price record of the power; a demand forecasting unit that forecasts an electric power demand based on the demand record information acquired by the acquisition unit; a charge / discharge prediction unit that predicts a charge amount and a discharge amount of the storage battery based on the charge / discharge performance information acquired by the acquisition unit; an agreement price prediction unit that predicts an electricity agreement price based on the agreement price actual result information acquired by the acquisition unit; a creation unit that creates control information for controlling charging and discharging of the storage battery so as to reduce the electricity cost for the bid of the retail electricity supplier, and bidding information for the retail electricity supplier to conduct a bid, based on the electricity demand predicted by the demand prediction unit, the charging and discharging amount predicted by the charging and discharging prediction unit, and the contract price predicted by the contract price prediction unit; and An energy trading system comprising:

2. The energy trading system according to claim 1 , wherein the creation unit creates a charging / discharging plan for the storage battery and a bidding plan for the spot market for the next day so as to reduce electricity costs for bids in the spot market.

3. 2. The energy trading system according to claim 1, wherein the creation unit creates a control command value for the storage battery and a bidding plan for the hour-ahead market so as to suppress an imbalance fee based on an amount of energy bid in the spot market and an electricity demand on that day, and an energy fee for bids in the hour-ahead market.

4. The acquisition unit acquires in-and-out record information indicating a record of in-and-out of an electric vehicle and remaining power record information indicating a record of remaining power of the electric vehicle, The charge / discharge prediction unit predicts the entrance / exit times of the electric vehicle and the power consumption during the exit based on the entrance / exit record information and the remaining power record information, the creation unit creates the control information and the bidding information based on the entrance / exit times of the electric vehicle and the power consumption during the exit, predicted by the charge / discharge prediction unit.

2. The energy trading system of claim 1.

5. An electricity trading method for supporting the bidding of electricity retailers that supply electricity to consumers and storage batteries, comprising: acquiring demand record information indicating an actual power demand of the customer, charge / discharge record information indicating a charge / discharge record of the storage battery, and contract price record information indicating a contract price record of the power; predicting an electric power demand based on the demand record information; predicting a charge amount and a discharge amount of the storage battery based on the charge / discharge performance information; predicting an electricity contract price based on the contract price performance information; creating control information for controlling charging and discharging of the storage battery so as to suppress the electricity cost for the bid of the retail electricity supplier based on the predicted electricity demand, the predicted charging and discharging amounts, and the predicted contract price, and creating bidding information for the retail electricity supplier to conduct the bidding; The power trading method comprises:

6. A computer of an energy trading device that carries out electricity bidding and supports the bidding of electricity retailers that supply electricity to consumers and storage batteries, acquiring demand record information indicating an actual power demand of the customer, charge / discharge record information indicating a charge / discharge record of the storage battery, and contract price record information indicating a contract price record of the power; predicting an electric power demand based on the demand record information; predicting a charge amount and a discharge amount of the storage battery based on the charge / discharge performance information; predicting an electricity contract price based on the contract price performance information; creating control information for controlling charging and discharging of the storage battery so as to suppress the electricity cost for the bid of the retail electricity supplier based on the predicted electricity demand, the predicted charging and discharging amounts, and the predicted contract price, and creating bidding information for the retail electricity supplier to conduct the bidding; A program to execute.

7. An energy trading device that carries out electricity bidding and supports bidding by electricity retailers that supply electricity to consumers and storage batteries, comprising: an acquisition unit that acquires demand record information indicating an actual power demand of the customer, charge / discharge record information indicating a charge / discharge record of the storage battery, and contract price record information indicating a contract price record of the power; a demand forecasting unit that forecasts an electric power demand based on the demand record information acquired by the acquisition unit; a charge / discharge prediction unit that predicts a charge amount and a discharge amount of the storage battery based on the charge / discharge performance information acquired by the acquisition unit; an agreement price prediction unit that predicts an electricity agreement price based on the agreement price actual result information acquired by the acquisition unit; a creation unit that creates bidding information for the electricity retailer to conduct a bidding so as to reduce the electricity cost for the bid of the electricity retailer based on the electricity demand predicted by the demand prediction unit, the charging and discharging amount predicted by the charging and discharging prediction unit, and the contract price predicted by the contract price prediction unit; and An energy trading device comprising:

8. A control device for controlling a consumer and a storage battery, an acquisition unit that acquires demand record information indicating an actual power demand of the customer, charge / discharge record information indicating a charge / discharge record of the storage battery, and contract price record information indicating a contract price record of the power; a demand forecasting unit that forecasts an electric power demand based on the demand record information acquired by the acquisition unit; a charge / discharge prediction unit that predicts a charge amount and a discharge amount of the storage battery based on the charge / discharge performance information acquired by the acquisition unit; an agreement price prediction unit that predicts an electricity agreement price based on the agreement price actual result information acquired by the acquisition unit; a creation unit that creates control information for controlling charging and discharging of the storage battery so as to reduce electricity costs for bids from retail electricity suppliers, based on the power demand predicted by the demand prediction unit, the charge and discharge amount predicted by the charge and discharge prediction unit, and the contract price predicted by the contract price prediction unit; and A control device comprising:

9. A computer of an energy trading device that carries out electricity bidding and supports the bidding of electricity retailers that supply electricity to consumers and storage batteries, acquiring demand record information indicating an actual power demand of the customer, charge / discharge record information indicating a charge / discharge record of the storage battery, and contract price record information indicating a contract price record of the power; a demand forecasting unit that forecasts an electric power demand based on the demand record information; predicting a charge amount and a discharge amount of the storage battery based on the charge / discharge performance information; predicting an electricity contract price based on the contract price performance information; A step of creating bidding information for the electricity retailer to conduct a bidding so as to suppress the electricity cost for the bid of the electricity retailer based on the predicted electricity demand, the predicted charging amount and discharging amount, and the predicted contract price; A program to execute.

10. The computer of the control device that controls the consumer and the storage battery acquiring demand record information indicating an actual power demand of the customer, charge / discharge record information indicating a charge / discharge record of the storage battery, and contract price record information indicating a contract price record of the power; predicting an electric power demand based on the demand record information; predicting a charge amount and a discharge amount of the storage battery based on the charge / discharge performance information; predicting an electricity contract price based on the contract price performance information; A step of creating control information for controlling charging and discharging of the storage battery so as to suppress the electricity cost for the bid of the retail electricity supplier based on the predicted electricity demand, the predicted charging and discharging amounts, and the predicted contract price; A program to execute.

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