Information processing device

Abstract

To provide an information processing apparatus which can make an electricity trading plan allowing for a procurement level of renewable energy electricity in P2P power trading.SOLUTION: An electricity market price prediction unit 106 predicts a trading price of electricity to be traded in a P2P power trading market. The trading price includes a price of renewable energy electricity and a price of non-renewable energy electricity. A renewable energy index setting unit 108 sets a renewable energy index showing a ratio of renewable energy electricity to electricity to be purchased in the P2P power trading market. A trading price setting unit 110 sets a desired trading price in an electricity trading plan in accordance with a prediction result of the trading price of electricity and the renewable energy index. A trading planning unit 114 makes the electricity trading plan on the basis of the desired trading price.SELECTED DRAWING: Figure 8

Description

[Technical field]

[0001] The present disclosure relates to an information processing device, and more particularly to an information processing device that creates an energy trading plan for an energy resource to trade energy through an energy trading market. [Background technology]

[0002] With the increase in renewable energy, the use of mobile objects equipped with batteries (electric vehicles, etc.) and facilities equipped with stationary batteries (houses, factories, etc.) as power resources to ensure the adjustment power necessary to maintain the balance between supply and demand of electricity is being considered. For example, JP 2020-78124 A (Patent Document 1) describes the creation of a charge and discharge plan for mobile objects equipped with batteries (power resources) according to the type of power, such as grid power or renewable energy power (see Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2020-78124 A Summary of the Invention [Problem to be solved by the invention]

[0004] With the liberalization of the electricity market, the introduction of P2P (Peer to Peer) electricity trading, in which individuals or corporations with electricity resources directly buy and sell electricity between themselves and other individuals or corporations, is being considered. In such electricity trading, an electricity trading plan (bidding plan) can be created by predicting the trading price in the electricity trading market. Here, when it is desired to adjust the degree of procurement of renewable energy electricity in electricity trading, the challenge is how to incorporate the desired degree of procurement of renewable energy electricity into such an electricity trading plan.

[0005] Therefore, an object of the present disclosure is to provide an information processing device capable of creating an energy trading plan that takes into account the procurement degree of renewable energy electricity in P2P energy trading. [Means for solving the problem]

[0006] The information processing device disclosed herein is an information processing device that creates an energy trading plan for an energy resource to trade energy through an energy trading market. The energy resource is configured to be able to receive energy at least from outside the energy resource. The information processing device includes a price prediction unit, an index setting unit, a trading price setting unit, and a trading plan creation unit. The price prediction unit predicts a trading price of energy traded in the energy trading market. The trading price includes a first price indicating the price of renewable energy electricity and a second price indicating the price of non-renewable energy electricity that does not fall under renewable energy electricity. The index setting unit sets a renewable energy index indicating the proportion of renewable energy electricity in the electricity purchased in the energy trading market. The trading price setting unit sets a desired trading price in the energy trading plan based on the prediction result of the price prediction unit and the renewable energy index. The trading plan creation unit creates an energy trading plan based on the desired trading price.

[0007] In this information processing device, the price of electricity (renewable energy electricity / non-renewable energy electricity) traded in the electricity trading market is predicted. Then, a desired trading price that takes into account the procurement level of renewable energy electricity is set based on the predicted electricity price and the set renewable energy index, and an electricity trading plan is created based on the desired trading price. In this way, the above-mentioned information processing device can create an electricity trading plan that takes into account the procurement level of renewable energy electricity.

[0008] The information processing device may further include a power generation prediction unit that predicts an amount of power generation of renewable energy power to be traded in the power trading market. The price prediction unit may predict the first price based on a prediction result of the power generation prediction unit.

[0009] The power generation prediction unit may predict the amount of power generated from renewable energy based on weather information for the area covered by the power trading market.

[0010] With the above configuration, it is possible to appropriately predict the price of renewable energy power based on the predicted amount of power generated from renewable energy power. As a result, the desired trading price is appropriately set, and an appropriate power trading plan can be created based on the desired trading price.

[0011] The information processing device may further include a power consumption prediction unit that predicts power consumption of the power resource. The trading plan creation unit may create an energy trading plan based on the desired trading price and a prediction result of the power consumption prediction unit.

[0012] This makes it possible to create an appropriate power trading plan that reflects the power consumption of the power resources.

[0013] The renewable energy index may be a percentage of the electricity purchased in the power trading market that is renewable energy electricity, set based on user input.

[0014] This makes it possible to create an electricity trading plan that reflects the user's desire for the above ratio of renewable energy electricity.

[0015] The index setting unit may set the renewable energy index based on a ratio of renewable energy electricity to electricity purchased in the electricity trading market during a predetermined period.

[0016] This allows an energy trading plan to be created based on the ratio of renewable energy power in a predetermined period of time in the past. For example, if the ratio of renewable energy power in a predetermined period of time is low, an energy trading plan can be created to increase the ratio.

[0017] The transaction price setting unit may set the desired transaction price based on the prediction result of the price prediction unit and the ratio of renewable energy power that is set according to the renewable energy index.

[0018] According to this information processing device, it is possible to create an electricity trading plan that takes into consideration the proportion of renewable energy electricity that is set according to the renewable energy index.

[0019] The index setting unit may set the renewable energy index based on a predetermined law or regulation that applies to the power resource.

[0020] This makes it possible to create an energy trading plan that reflects the laws and regulations that apply to the energy resources. For example, in a case where a renewable energy power usage ratio is stipulated by local ordinance as a condition for entering a certain area, it is possible to create an energy trading plan that satisfies the condition regarding the renewable energy power usage ratio.

[0021] The index setting unit may set the renewable energy index based on a predetermined tax system applied to the power resource.

[0022] This allows the creation of an energy trading plan that reflects a specific tax system applied to power resources. For example, in a case where the tax rate is set based on the usage rate of renewable energy power, it is possible to create an energy trading plan with a desired renewable energy power ratio that takes the tax rate into account. Effect of the Invention

[0023] According to the information processing device of the present disclosure, in P2P energy trading, it is possible to create an energy trading plan that takes into account the procurement degree of renewable energy electricity. [Brief description of the drawings]

[0024] [Figure 1] FIG. 1 is a diagram illustrating a schematic configuration example of an electricity transmission and distribution system for electricity traded using an information processing device according to a first embodiment. [Diagram 2] FIG. 1 is a diagram illustrating an example of a P2P energy trading market. [Diagram 3] FIG. 1 is a diagram illustrating an example of a bid in a general trading market for P2P energy trading. [Figure 4]FIG. 1 is a diagram illustrating an example of a bidding in a direct trading market for P2P energy trading. [Diagram 5] FIG. 2 is a diagram illustrating an example of a hardware configuration of an agent and a market trading server. [Figure 6] FIG. 4 is a diagram illustrating an example of resource information. [Figure 7] FIG. 11 is a diagram illustrating an example of agent information. [Figure 8] FIG. 2 is a block diagram functionally showing a configuration of an agent according to the first embodiment. [Figure 9] FIG. 1 is a diagram showing the relationship between the predicted amount of power generation of renewable energy electricity and the desired trading price (unit price) of renewable energy electricity. [Figure 10] 13 is a flowchart showing an example of a procedure of a process executed when an agent makes a bid in the P2P energy trading market. [Figure 11] FIG. 11 is a block diagram functionally showing a configuration of an agent according to a second embodiment. [Figure 12] 13 is a flowchart showing an example of a procedure of processes executed when an agent according to the second embodiment makes a bid in the P2P energy trading market. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0025] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are designated by the same reference characters and their description will not be repeated.

[0026] [Embodiment 1] Fig. 1 is a diagram illustrating a schematic configuration example of a power transmission and distribution system for trading using an information processing device according to embodiment 1. With reference to Fig. 1, power transmission and distribution system 1 includes a plurality of power resources, charging and discharging facilities 6A-6H, a power company 9, a power transmission line network PL, a trading market server 3, and a communication network 10.

[0027] The multiple power resources include, for example, electric vehicles 5A to 5E, a factory 7A, a company 7B, a commercial facility 7C, a residence 7D, and a store 7E. Each power resource is configured to be able to exchange power with the other power resources via the power transmission network PL or directly.

[0028] The number of electric vehicles and the number of charging / discharging facilities are not limited to those shown in the figure. Furthermore, facilities such as the factory 7A are not limited to those shown in the figure. Furthermore, hereinafter, the electric vehicles 5A to 5E may be referred to as "electric vehicles 5" without distinction, and the charging / discharging facilities 6A to 6H may be referred to as "charging / discharging facilities 6" without distinction. Furthermore, the factory 7A, the company 7B, the commercial facility 7C, the house 7D, and the store 7E may be referred to as "facilities 7" without distinction.

[0029] The electric vehicle 5 is an electric vehicle that can run using power stored in a battery, and is, for example, an electric vehicle (BEV: Battery Electric Vehicle) or a plug-in hybrid electric vehicle (PHEV: Plug-in Hybrid Electric Vehicle). In the following, the electric vehicle 5 is assumed to be a BEV. The electric vehicle 5 is configured to be electrically connectable to a charging / discharging facility 6, and can receive and transmit power to and from the power transmission network PL or a facility 7 through the charging / discharging facility 6.

[0030] The facility 7 is electrically connected to the power transmission line network PL and can exchange electric power with the power transmission line network PL. The facility 7 is also electrically connected to the charging / discharging equipment 6 and can exchange electric power with the electric vehicle 5 connected to the charging / discharging equipment 6.

[0031] The charging / discharging equipment 6 is electrically connected to the power transmission line network PL or a facility 7. The charging / discharging equipment 6 can be electrically connected to the electric vehicle 5 through a power cable, and the electric vehicle 5 can receive and transmit power to and from the power transmission line network PL or the facility 7 through the charging / discharging equipment 6 to which it is connected.

[0032] Electricity generated by power plants managed by the electric power company 9 is supplied to each facility 7 through a power transmission line network PL (grid power network), and can also be supplied to an electric vehicle 5A connected to a charging / discharging facility 6A. Conventionally, electricity has been supplied in this way exclusively from the power plant of the electric power company 9 to the facilities 7 and electric vehicles 5 through the power transmission line network PL. In this power transmission and distribution system 1, electricity buying and selling transactions between individuals or corporations (each facility 7 or each electric vehicle 5), that is, P2P (Peer to Peer) electricity transactions, can be carried out.

[0033] The market server 3 provides a platform for implementing such P2P energy trading. The market server 3 is configured to be able to communicate with the electric vehicle 5, the charging / discharging equipment 6, and the facility 7 through the communication network 10. When the facility 7 or the electric vehicle 5 wishes to carry out P2P energy trading, the facility 7 or the electric vehicle 5 (more specifically, an agent (described later) that executes the energy trading of the facility 7 or the electric vehicle 5) submits a bid to the market server 3 that manages the P2P energy trading market where the energy trading is to be carried out, with bidding conditions including, for example, a time period during which the energy is to be bought and sold, the amount of energy bought and sold per unit time period, and a trading price. The market server 3 issues an agreement for energy trading between a seller and a buyer who meet the bidding conditions by an arbitrary algorithm, and processes a bid for which no other party who meets the conditions is found as a non-contract. Note that the term "bidding" refers to the act of ordering an energy trade (purchase or sale), or the order itself. The term "contract" refers to the act of deciding to carry out the bidded energy trade, or the decision itself.

[0034] FIG. 2 is a diagram showing a schematic diagram of an example of a P2P energy trading market. Referring to FIG. 2, in the P2P energy trading market, an "agent" that executes a bid on the P2P energy trading market plans and executes the bid, manages the agreement, creates a charge and discharge plan based on the agreement, and so on. An agent is provided for each facility 7 or electric vehicle 5, and in the present embodiment 1, there are a plurality of mobile agents 2A-2D corresponding to the electric vehicle 5, a plurality of business agent agents 2E-2H corresponding to the factory 7A, etc., and a plurality of residential agents 2I, 2J corresponding to the residential houses. For example, to explain the electric vehicle 5 as a representative example, the mobile agent of the electric vehicle 5 creates an energy trading plan (bidding plan) for the P2P energy trading market, and the mobile agent executes a bid on the P2P energy trading market (trading market server 3).

[0035] In the following, the mobile agents 2A to 2D, the business operators' agents 2E to 2H, and the residential agents 2I and 2J may be simply referred to as "agents 2" without distinction. The agents 2 are "information processing devices" that create an energy trading plan for corresponding energy resources to trade energy through the P2P energy trading market.

[0036] In addition, the P2P energy trading market is divided into a "general trading market" and a "direct trading market." The general trading market is a market that handles the trading of electricity transmitted through the power transmission line network PL, and an unspecified number of agents 2 can participate in the energy trading. In the general trading market, the energy trading is agreed (matching) according to arbitrary rules set by the operator who manages the P2P energy trading market. As a matching rule, for example, when the price offered by the seller and the price offered by the buyer match in a specified unit time period, the transaction is concluded on a first-come, first-served basis. As another matching rule, a method of concluding a transaction at an appropriate price after first sorting out the bids (orders) of the seller and the buyer made in the unit time period is also possible.

[0037] Fig. 3 is a diagram for explaining an example of bidding in a general trading market for P2P energy trading. With reference to Fig. 3, in the general trading market, an unspecified number of sellers bid a pair (p, q) of a selling price and an amount of energy for each predetermined unit time slot (1, 2, ... n), while an unspecified number of buyers bid a pair (P, Q) of a purchase price and an amount of energy. Note that the unit time slot is a time span (e.g., 30 minutes) set in the general trading market. The trading of the amount of energy is carried out for each amount of energy transmitted within the unit time slot (power x length of unit time slot).

[0038] Referring again to FIG. 2, the direct trading market is a market that handles trading of electricity transmitted when an electric vehicle 5 moves to a facility 7 without passing through a power grid PL, and only agents having an ID of the direct trading market can participate in electricity trading. In the direct trading market, one market is formed for each facility 7 where a charging / discharging facility 6 is installed. A server provided for each facility 7 may manage one direct trading market, or a plurality of direct trading markets by a plurality of facilities 7 may be managed by a common server. In the direct trading market, electricity trading is agreed upon (matching) according to any rules independently determined by the operator of each market. As the matching rules, the above-mentioned method described for the general trading market may be adopted.

[0039] Fig. 4 is a diagram for explaining an example of bidding in a direct trading market for P2P energy trading. With reference to Fig. 4, in the direct trading market, a seller presents a pair (p, q) of a selling price and an amount of energy for each predetermined unit time slot (1, 2, ... n), and multiple buyers having IDs of the direct trading market bid a pair (P, Q) of a purchase price and an amount of energy. The unit time slot is a time span that is individually set in the direct trading market. The trading of the amount of energy is carried out for each amount of energy (power x length of unit time slot) transmitted within the unit time slot.

[0040] Fig. 5 is a diagram showing an example of the hardware configuration of the agent 2 and the trading market server 3. Referring to Fig. 5, the agent 2 includes a processor 21, a memory 22, and a communication device 23. An agent 2 is provided for each power resource of the electric vehicle 5 and the facility 7 (factory 7A, house 7D, etc.). The agent 2 may be provided in the corresponding power resource, or may be provided in a cloud capable of communicating with the corresponding power resource.

[0041] The processor 21 is a computing entity (computer) that executes various processes by executing various programs. The processor 21 is composed of a CPU (Central Processing Unit), an FPGA (Field-Programmable Gate Array), a GPU (Graphics Processing Unit), etc. The processor 21 may be composed of a processing circuitry.

[0042] The memory 22 stores programs and data for the processor 21 to execute various processes. The memory 22 is configured with storage media such as a read only memory (ROM) and a random access memory (RAM). The memory 22 stores a calculation program 221, resource information 222, and external information 223.

[0043] The computing program 221 specifies the processing executed by the processor 21. For example, the computing program 221 includes a program for making a bid to the market server 3 for energy trading in the P2P energy trading market managed by the market server 3.

[0044] The resource information 222 includes information on the power resource (eg, electric vehicle 5) corresponding to the agent 2, and in particular includes information on bidding and contracting for power trading.

[0045] Fig. 6 is a diagram showing an example of the resource information 222. In Fig. 6, the resource information 222 in the agent 2 (mobile agent) of the electric vehicle 5 is shown as an example.

[0046] Referring to FIG. 6, the resource information 222 includes an ID, type information, trip information, SOC (State Of Charge) information, connection information, bidding information, contract information, a charge / discharge plan, and a charge / discharge record.

[0047] The ID includes identification information for identifying the power resource (electric vehicle 5 in this example). The type information includes information on the type of power resource, for example, information for identifying an electric vehicle, a business, a house, etc. The trip information includes information on a driving history such as past driving routes and driving times. The SOC information includes information on the amount of power currently stored in the power storage device. The connection information includes information for identifying whether or not the device is currently connected to the charging / discharging equipment 6. The bidding information includes information on past bidding history and information on the bidding currently being conducted. The agreement information includes information on past agreement history and information for identifying whether or not the bidding currently being conducted has been agreed upon. The charging / discharging plan includes information on a charging / discharging plan for the power resource based on the agreement. The charging / discharging performance includes information on the results of charging / discharging according to the charging / discharging plan.

[0048] The trip information and connection information are information used by the agent 2 (mobile agent) of the electric vehicle 5, and are blank in the facility 7 (factory 7A, house 7D, etc.).

[0049] 5 again, the external information 223 includes the price of grid power provided by the power company 9, weather information (solar radiation, weather, wind speed, etc.) of the area of ​​the P2P power trading market where the bid is made, information on renewable energy power generation facilities (photovoltaic power generation facilities, wind power generation facilities, hydroelectric power generation facilities, etc.) in the market, etc. The agent 2 acquires this external information 223 from an external server device (which may be the trading market server 3) via the communication network 10.

[0050] The communication device 23 transmits and receives various data to and from the market trading server 3 via the communication network 10 .

[0051] The market server 3 includes a processor 31, a memory 32, and a communication device 33. The market server 3 is a device that manages P2P energy trading between power resources in the P2P energy trading market (the general trading market and the direct trading market), and executes processes related to the energy trading.

[0052] The processor 31 is a computing entity (computer) that executes various processes by executing various programs. The processor 31 is configured with a CPU, an FPGA, a GPU, etc. The processor 31 may be configured with an arithmetic circuit.

[0053] The memory 32 stores programs and data for the processor 31 to execute various processes. The memory 32 is configured with storage media such as ROM and RAM. The memory 32 stores an arithmetic program 321 and agent information 322.

[0054] The calculation program 321 specifies the processing to be executed by the processor 31. For example, the calculation program 321 includes a program for executing a bidding process for accepting bids from a plurality of agents 2, and a contract process based on the bids. The contract process effects a contract for an energy transaction between a seller and a buyer who meet the bidding conditions, and processes a bid for which no other party meeting the conditions is found as a non-contract.

[0055] The agent information 322 includes information about the agents 2 participating in the P2P energy trading market managed by the trading market server 3, and in particular includes information about the bids and agreements for energy trading for each agent 2.

[0056] Fig. 7 is a diagram showing an example of the agent information 322. Referring to Fig. 7, the agent information 322 includes an ID, type information, bid information, and contract information.

[0057] The ID includes identification information for identifying an agent 2 participating in the P2P energy trading market managed by the trading market server 3. The type information includes information on the type of power resource, such as information for identifying an electric vehicle, a business operator, a house, etc. The bidding information includes information on the past bidding history of each agent 2 and information on the currently conducted bidding. The contract information includes information on the past contract history of each agent 2 and information for identifying whether the currently conducted bidding has been contracted or not.

[0058] Referring back to FIG. 5, the communication device 33 transmits and receives various data to and from the agent 2 through the communication network 10.

[0059] In a P2P energy trading market configured by such an agent 2 and market server 3, the agent 2 predicts the usage of the corresponding power resource (in the case of an electric vehicle 5, it predicts the usage of the electric vehicle 5 by the user) and predicts the power trading price in the energy trading market during the time period when participation in the power trading is possible. The agent 2 then creates an energy trading plan (bidding plan) that is cost-optimal under the constraints of the upper and lower SOC limits (the range in which charging and discharging can be performed) that should be satisfied in the power storage device of the corresponding power resource, and submits a bid for the power trading to the market server 3.

[0060] Here, when creating an electricity trading plan in the agent 2, in addition to the viewpoint of cost optimization, it may be desirable to adjust the degree of procurement of renewable energy electricity in light of the social need for improved utilization of renewable energy. For example, when there is a surplus of renewable energy electricity (electricity derived from solar power generation, wind power generation, etc.), it is conceivable to increase the degree of procurement of renewable energy electricity, which is expected to reduce costs, and to decrease the degree of procurement of renewable energy electricity, which may become expensive, when the amount of renewable energy electricity generated is small.

[0061] Therefore, the agent 2 according to the first embodiment creates an electricity trading plan that can reflect the procurement degree of renewable energy electricity in addition to the viewpoint of cost optimization. This will be described in detail below.

[0062] Fig. 8 is a block diagram functionally showing a configuration of agent 2 according to embodiment 1. Referring to Fig. 8, agent 2 includes an external information acquisition unit 102, a renewable energy power generation amount prediction unit 104, a market electricity price prediction unit 106, a renewable energy index setting unit 108, a trading price setting unit 110, an electricity consumption prediction unit 112, and an electricity trading plan creation unit 114.

[0063] The external information acquisition unit 102 acquires weather information for the area of ​​the P2P energy trading market where the bid is to be placed from an external server device (not shown). The weather information is weather forecast information for the area, and includes forecast information such as solar radiation, weather, and wind speed for each time period. The P2P energy trading market where the bid is to be placed is an energy trading market in an area where the corresponding power resource desires to be charged / discharged based on P2P energy trading, and is determined based on the predicted usage of the corresponding power resource. For example, in the case of the agent 2 (mobile agent) of the electric vehicle 5, the weather information may be determined based on the predicted position (e.g., destination, etc.) of the electric vehicle 5.

[0064] Furthermore, the external information acquisition unit 102 acquires information on renewable energy power generation facilities in the P2P energy trading market where the bidding is conducted from an external server device (not shown). The renewable energy power generation facilities are solar power generation facilities, wind power generation facilities, hydroelectric power generation facilities, etc. The information on the renewable energy power generation facilities includes information on the type and number of the above power generation facilities in the area covered by the P2P energy trading market, the rated output or maximum output of each power generation facility, etc. The information acquired by the external information acquisition unit 102 is stored in the memory 22 as external information 223.

[0065] The renewable energy power generation amount prediction unit 104 predicts the amount of renewable energy power generation in the P2P energy trading market where bidding is conducted, based on the weather information and power generation facility information acquired by the external information acquisition unit 102. For example, in the case of a solar power generation facility, if the time period is daytime, the weather is sunny, and there are many solar power generation facilities, the renewable energy power generation amount prediction unit 104 predicts that the amount of renewable energy generated from solar power generation will be large. On the other hand, if the weather is rainy or the time period is nighttime, the renewable energy power generation amount prediction unit 104 predicts that the amount of renewable energy generated from solar power generation will be small. Also, in the case of a wind power generation facility, if the wind is strong and there are many wind power generation facilities, the renewable energy power generation amount prediction unit 104 predicts that the amount of renewable energy generated from wind power generation will be large.

[0066] The market electricity price prediction unit 106 predicts the price (unit price) of electricity (purchased electricity and sold electricity) traded in the P2P electricity trading market where bidding is conducted. In the P2P electricity trading market in the first embodiment, renewable energy electricity derived from renewable energy power generation facilities is traded separately from non-renewable energy electricity (electricity derived from thermal power generation, etc.) that does not fall under renewable energy electricity. For example, when trading renewable energy electricity, a tag (renewable energy tag) indicating that the electricity being traded is renewable energy electricity can be attached to distinguish the renewable energy electricity from the non-renewable energy electricity. Alternatively, the P2P electricity trading market may be divided into a market that handles trading of renewable energy electricity and a market that handles trading of non-renewable energy electricity.

[0067] In the first embodiment, the market electricity price prediction unit 106 predicts the purchase price by distinguishing between the price of renewable energy electricity (first price) and the price of non-renewable energy electricity (second price). The price of renewable energy electricity is predicted based on the prediction result of the renewable energy power generation amount prediction unit 104.

[0068] For example, when the renewable energy power generation amount prediction unit 104 predicts that the amount of power generated from renewable energy is large, it is expected that a surplus of renewable energy power will occur, and therefore the market power price prediction unit 106 predicts that the price of renewable energy power will be low. On the other hand, when the renewable energy power generation amount prediction unit 104 predicts that the amount of power generated from renewable energy is small, the amount of renewable energy power in circulation is limited, and therefore the market power price prediction unit 106 predicts that the price of renewable energy power will be high. Note that high (low) may mean high (low) relative to a certain reference price, or high (low) relative to the price of non-renewable energy power.

[0069] The price of the non-renewable energy power can be predicted based on the price of grid power available from the power company 9, for example.

[0070] The renewable energy index setting unit 108 sets a "renewable energy index" indicating the percentage of renewable energy electricity in electricity purchased in the P2P energy trading market (purchased electricity). As described above, in the P2P energy trading market in the first embodiment, renewable energy electricity and non-renewable energy electricity can be traded separately, and the renewable energy index setting unit 108 can adjust the degree to which renewable energy electricity should be included when purchasing electricity.

[0071] In the first embodiment, a user of a corresponding power resource can set the ratio of renewable energy power in the purchased power (user's desired renewable energy rate) from an input device (not shown). The desired renewable energy rate set by the user may be the value of the renewable energy power ratio itself, or may be whether the renewable energy power ratio is to be higher or lower than a certain reference ratio. For example, if the user wants to increase the purchase amount of renewable energy power, the user can set a high desired renewable energy rate from the input device.

[0072] The renewable energy index is defined as an index that is larger as the ratio of renewable energy power in the purchased electricity is higher, and is smaller as the ratio of renewable energy power is lower. The renewable energy index setting unit 108 sets the renewable energy index based on the desired renewable energy rate set by the user.

[0073] The trading price setting unit 110 sets a desired trading price for bidding in the P2P energy trading market based on the prediction result of the energy trading price by the market electricity price prediction unit 106 and the renewable energy index set by the renewable energy index setting unit 108. Specifically, the trading price setting unit 110 changes the price of renewable energy electricity (first price) predicted by the market electricity price prediction unit 106 according to the renewable energy index. Hereinafter, a description will be given with reference to FIG. 9.

[0074] Fig. 9 is a diagram showing the relationship between the predicted amount of power generation of renewable energy power and the desired trading price (unit price) of renewable energy power. Referring to Fig. 9, line k1 indicates the price of renewable energy power predicted by the market electricity price prediction unit 106 based on the amount of power generation of renewable energy power predicted by the renewable energy power generation amount prediction unit 104. As described above, when the amount of power generation of renewable energy is predicted to be large, the price of renewable energy power is predicted to be low. On the other hand, when the amount of power generation of renewable energy is predicted to be small, the price of renewable energy power is predicted to be high.

[0075] The line k2 indicates the desired trading price of renewable energy power set by the trading price setting unit 110 when the renewable energy index is large (the desired renewable energy rate is high). The line k2 is obtained by changing the line k1 so that the price fluctuation based on the predicted power generation amount of renewable energy power becomes large with respect to the predicted price of renewable energy power indicated by the line k1. That is, the trading price setting unit 110 sets the desired trading price of renewable energy power lower than the predicted price when the predicted power generation amount of renewable energy power is large with respect to the predicted price of renewable energy power indicated by the line k1, and sets the desired trading price of renewable energy power higher than the predicted price when the predicted power generation amount of renewable energy power is small. As a result, in the power trading plan described later, a trading plan is created in which renewable energy power is actively purchased during the time period when the power generation amount of renewable energy power is large.

[0076] Line k3 indicates the desired trading price of renewable energy electricity set by the trading price setting unit 110 when the renewable energy index is small (desired renewable energy rate is low). Line k3 is obtained by changing line k1 so that the price fluctuation based on the predicted power generation amount of renewable energy electricity becomes smaller with respect to the predicted price of renewable energy electricity indicated by line k1. In other words, the trading price setting unit 110 sets the desired trading price so that the dependency of the power generation amount of renewable energy electricity on the trading price of renewable energy electricity becomes smaller. As a result, in the power trading plan described below, a trading plan for actively purchasing renewable energy electricity, as in the case where the renewable energy index is large, is not created.

[0077] The desired trading price of non-renewable energy electricity is set to the predicted price predicted by the market electricity price prediction unit 106.

[0078] 8 again, the power consumption prediction unit 112 predicts the amount of power consumed in the power storage device of the corresponding power resource. For example, in the case of the agent 2 (mobile agent) of the electric vehicle 5, the power consumption prediction unit 112 predicts the amount of power consumed by the battery mounted on the electric vehicle 5 due to the use (travel) of the electric vehicle 5. The prediction result of the power consumption prediction unit 112 is used to set constraint conditions of the SOC upper and lower limits to be satisfied in the power storage device of the corresponding power resource when creating an energy trading plan, which will be described later.

[0079] The energy trading plan creation unit 114 creates an energy trading plan (bidding plan) for conducting energy trading in the P2P energy trading market, based on the desired trading price set by the trading price setting unit 110 and the energy consumption of the energy resource predicted by the energy consumption prediction unit 112. As an example, the energy trading plan creation unit 114 creates an energy trading plan that is optimal in terms of cost under the constraints of upper and lower SOC limits (the range in which charging and discharging can be performed) that should be satisfied in the energy storage device of the corresponding energy resource.

[0080] Specifically, an objective function Fcost is set to calculate the cost in the power buying and selling transaction, and the amount of power to be traded that minimizes the objective function Fcost is searched for under the constraint conditions of the upper and lower SOC limits (the range in which charging and discharging can be performed) that should be satisfied in the storage device of the corresponding power resource. As an example, the objective function Fcost can be set as shown in the following formula.

[0081]

number

[0082] Here, k (i to i+n, i is the current unit time slot) is the code of the unit time slot, and r(k) is a variable that is "1" if the power resource procures power through the P2P energy trading market in unit time slot k, and is "0" otherwise. F(k) is the cost when the power resource procures power through the P2P energy trading market in unit time slot k, and is given by the following formula.

[0083]

number

[0084] Here, Pr(k) is the desired trading price (unit price) of renewable energy electricity set by the trading price setting unit 110, and Qbr(k) and Qsr(k) are the amount of electricity desired to be purchased and sold of renewable energy electricity in unit time slot k, respectively. Pn(k) is the desired trading price (unit price) of non-renewable energy electricity set by the trading price setting unit 110, that is, the predicted price of non-renewable energy electricity predicted by the market electricity price prediction unit 106. Qbn(k) and Qsn(k) are the amount of electricity desired to be purchased and sold of non-renewable energy electricity in unit time slot k, respectively.

[0085] On the other hand, the SOC of the power storage device of the power resource is given by the following equation.

[0086]

number

[0087] Here, Qtrip(k) is a predicted value of the power consumption of the power resource in unit time slot k. When the power resource is an electric vehicle 5, Qtrip(k) is a predicted value of the power consumption due to the running of the electric vehicle 5 in unit time slot k, and is calculated from the electricity consumption of the electric vehicle 5, etc. C is a conversion coefficient for converting the amount of power into SOC.

[0088] An upper limit value SOC_upper and a lower limit value SOC_lower are set for the SOC, and the constraint is that the SOC satisfies the following formula.

[0089]

number

[0090] In this way, for the objective function Fcost shown in formula (1), a condition is searched for that minimizes the objective function Fcost while satisfying the SOC constraint condition shown in formula (4) (optimization of objective function Fcost). Any calculation method such as linear programming or convex optimization can be used for the optimization calculation of the objective function Fcost.

[0091] As described above, in the first embodiment, a renewable energy index indicating the procurement degree of renewable energy power is set, and a desired trading price is set taking into account the renewable energy index. Then, an energy trading plan is created based on an objective function Fcost using the desired trading price taking into account the renewable energy index. This makes it possible to reflect the procurement degree of renewable energy power in the energy trading plan, and to create an energy trading plan taking into account the procurement degree of renewable energy power.

[0092] Fig. 10 is a flowchart showing an example of a procedure of a process executed when the agent 2 makes a bid in the P2P energy trading market. Referring to Fig. 10, the agent 2 (processor 21) acquires external information related to the P2P energy trading market in which the bid is to be made from an external server device through the communication network 10 (step S10). The external information includes weather information (solar radiation, weather, wind speed, etc.) of the area covered by the market, information on renewable energy power generation facilities (photovoltaic power generation facilities, wind power generation facilities, hydroelectric power generation facilities, etc.) in the market, the price of grid power provided by the power company 9, etc.

[0093] Next, the agent 2 predicts the amount of renewable energy power generation in the P2P power trading market where bidding will be conducted, based on the weather information and information on the renewable energy power generation facilities acquired in step S10 (step S20).

[0094] Then, the agent 2 predicts the price (unit price) of renewable energy power to be traded in the market based on the amount of power generation of renewable energy power predicted in step S20 (step S30). Specifically, as shown by the line k1 in Fig. 9, when the amount of power generation of renewable energy is predicted to be large, the agent 2 predicts the price of renewable energy power to be low, and when the amount of power generation of renewable energy is predicted to be small, the agent 2 predicts the price of renewable energy power to be high.

[0095] Next, the agent 2 acquires the desired renewable energy rate set by the user of the corresponding power resource from the input device, and sets the renewable energy index based on the desired renewable energy rate (step S40). As described above, the renewable energy index is an index indicating the proportion of renewable energy power in the power purchased (purchased power) in the P2P power trading market where bidding is conducted.

[0096] Then, the agent 2 sets a desired trading price in the P2P energy trading market where bidding is performed based on the price of renewable energy electricity predicted in step S30 and the renewable energy index set in step S40 (step S50). Specifically, as described in Fig. 9, the desired trading price of renewable energy electricity is set by changing the price of renewable energy electricity predicted in step S30 according to the renewable energy index. The desired trading price of non-renewable energy electricity is set based on the price of grid electricity acquired in step S10.

[0097] Next, the agent 2 predicts the amount of power consumption in the power storage device of the corresponding power resource (step S60). If the agent 2 is an agent (mobile agent) of the electric vehicle 5, the agent 2 predicts the amount of power consumption of the battery due to the running of the electric vehicle 5 based on the past electricity consumption.

[0098] Then, the agent 2 creates an optimal energy trading plan by searching for a condition that minimizes the objective function Fcost shown in the above formula (1) under the constraint of the SOC of the power storage device of the corresponding resource shown in the above formula (4) (step S70). That is, the agent 2 executes a cost optimization calculation using formulas (1) to (4) and creates a bidding plan for the P2P energy trading market.

[0099] When the energy trading plan (bidding plan) is created in step S70, the agent 2 executes a bid in the P2P energy trading market (trading market server 3) based on the energy trading plan (step S80).

[0100] As described above, in this first embodiment, the price of electricity (renewable energy electricity / non-renewable energy electricity) traded in the P2P energy trading market is predicted. In addition, a renewable energy index indicating the proportion of renewable energy electricity in the electricity purchased in the P2P energy trading market is set. Then, a desired trading price taking into account the procurement degree of renewable energy electricity is set from the predicted electricity price and the set renewable energy index, and an energy trading plan is created based on the desired trading price. In this way, according to this first embodiment, an energy trading plan taking into account the procurement degree of renewable energy electricity can be created.

[0101] In addition, in the first embodiment, the amount of renewable energy power to be traded in the P2P energy trading market is predicted based on weather information of the area handled by the market, and the price of renewable energy power is predicted based on the prediction result. Therefore, the price of renewable energy power can be appropriately predicted. As a result, the desired trading price is appropriately set, and an appropriate energy trading plan can be created based on the desired trading price.

[0102] Furthermore, in the first embodiment, the power consumption of the power resource is predicted, and the power trading plan is created based on the prediction result and the desired trading price. Therefore, an appropriate power trading plan can be created based on the prediction of the power consumption of the power resource.

[0103] In the first embodiment, the renewable energy index is the ratio of renewable energy power to the total power purchased in the power trading market, which is set based on a user's input. Therefore, it is possible to create an electricity trading price that reflects the user's preference regarding the ratio of renewable energy power.

[0104] [Embodiment 2] In the above-mentioned first embodiment, a user of a corresponding power resource sets the ratio of renewable energy power in the purchased power (desired renewable energy rate) from an input device, and the renewable energy index is set based on the desired renewable energy rate. In this second embodiment, the renewable energy index is set based on the ratio of renewable energy power (renewable energy usage ratio) in the power previously purchased in the P2P power trading market.

[0105] Fig. 11 is a block diagram functionally showing a configuration of an agent according to embodiment 2. Referring to Fig. 11, agent 2# further includes a renewable energy use ratio calculation unit 116 and includes a renewable energy index setting unit 108A instead of renewable energy index setting unit 108 in the configuration of agent 2 according to embodiment 1 shown in Fig. 8.

[0106] The renewable energy use ratio calculation unit 116 calculates the ratio of renewable energy power (renewable energy use ratio) to the power purchased through the P2P power trading market during a predetermined past period. The predetermined period can be set appropriately, for example, to several months. Then, the renewable energy use ratio calculation unit 116 sets the ratio of renewable energy power in the power trading subject to the current bid (traded renewable energy ratio) based on the calculated past renewable energy use ratio. For example, when the past renewable energy use ratio is lower than a reference ratio that is appropriately set, the renewable energy use ratio calculation unit 116 sets the traded renewable energy ratio to a value higher than the past renewable energy use ratio in order to increase the renewable energy use ratio.

[0107] Then, the renewable energy index setting unit 108A sets the renewable energy index based on the trading renewable energy ratio set in the renewable energy use ratio calculation unit 116. Specifically, the renewable energy index is appropriately set so that the higher the trading renewable energy ratio, the larger the renewable energy index, and the lower the trading renewable energy ratio, the smaller the renewable energy index.

[0108] Other functions of agent 2# are the same as those of agent 2 according to the first embodiment shown in FIG.

[0109] 12 is a flowchart showing an example of a procedure of a process executed when agent 2# according to the second embodiment places a bid in the P2P energy trading market. This flowchart corresponds to the flowchart of FIG. 10 described in the first embodiment.

[0110] 12, the processes in steps S110 to S130 and S150 to S180 are the same as the processes in steps S10 to S30 and S50 to S80 in the flowchart shown in FIG.

[0111] In this flowchart, in step S130, when the price (unit price) of renewable energy electricity to be traded in the P2P electricity trading market where bidding is being conducted is predicted, agent 2# calculates the trading renewable energy ratio in the electricity trading subject to the current bid based on the renewable energy usage ratio in a specified period in the past, and sets a renewable energy index based on the trading renewable energy ratio (step S140).

[0112] Then, once the renewable energy index has been set, agent 2# transitions to step S150, where the desired trading price in the P2P energy trading market where bidding takes place is set based on the price of renewable energy electricity predicted in step S130 and the renewable energy index set in step S140.

[0113] As described above, in the second embodiment, the renewable energy ratio in the electricity trading subject to the current bid is calculated based on the renewable energy usage ratio in a predetermined period in the past, and the renewable energy index is set based on the renewable energy ratio. Therefore, an electricity trading plan can be created based on the renewable energy usage ratio in a predetermined period in the past. For example, if the renewable energy ratio in the predetermined period is low, an electricity trading plan can be created to increase the ratio.

[0114] [Variations] As described above, the renewable energy index, which indicates the proportion of renewable energy electricity in the electricity purchased (purchased electricity) in the P2P energy trading market, is set based on the user's desired renewable energy rate in the first embodiment, and is set based on the trading renewable energy rate according to the renewable energy usage rate in a specified period in the past in the second embodiment. However, the renewable energy index may be set based on other parameters.

[0115] Specifically, the renewable energy index may be set based on a predetermined law or regulation that applies to the corresponding power resource. For example, when the corresponding power resource is the electric vehicle 5, and the renewable energy usage ratio is stipulated by a local ordinance or the like for the electric vehicle 5 to enter a certain area (such as a nature conservation area), the renewable energy index may be set based on the renewable energy usage ratio stipulated by the local ordinance.

[0116] Alternatively, the renewable energy index may be set based on a predetermined tax system applied to the corresponding power resource. For example, when the corresponding power resource is the electric vehicle 5, in a case where a tax rate such as an environmental tax is determined based on a renewable energy usage ratio determined according to the manufacturing year of the electric vehicle 5, the renewable energy index may be set based on the renewable energy usage ratio applied to the electric vehicle 5.

[0117] The embodiments disclosed herein should be considered to be illustrative and not restrictive in all respects. The technical scope of the present disclosure is defined by the claims, not by the description of the embodiments described above, and is intended to include all modifications within the meaning and scope of the claims. [Explanation of symbols]

[0118] 1 Power transmission and distribution system, 2,2# Agent, 2A-2D Mobile agent, 2E-2H Business agent, 2I,2J Housing agent, 3 Trading market server, 5,5A-5E Electric vehicle, 6,6A-6H Charging and discharging equipment, 7 Facility, 7A Factory, 7B Company, 7C Commercial facility, 7D House, 7E Store, 9 Power company, 10 Communication network, 21,31 Processor, 22,32 Memory, 23,33 Communication device, 102 External information acquisition unit, 104 Renewable energy power generation forecast unit, 106 Market electricity price forecast unit, 108,108A Renewable energy index setting unit, 110 Trading price setting unit, 112 Power consumption forecast unit, 114 Power trading plan creation unit, 116 Renewable energy usage ratio calculation unit, 221,321 Calculation program, 222 Resource information, 223 External information, 322 Agent information, PL power grid.

Claims

1. An information processing device that creates an energy trading plan for an electric power resource to trade electric power through an energy trading market, the electric power resource being configured to be able to receive electric power at least from an external source of the electric power resource; a price prediction unit that predicts a trading price of electricity to be traded in the electricity trading market, The transaction price is A first price indicating a price of renewable energy electricity; A second price indicating a price of non-renewable energy electricity not corresponding to the renewable energy electricity, an index setting unit that sets a renewable energy index indicating a proportion of the renewable energy electricity in the electricity purchased in the electricity trading market; a transaction price setting unit that sets a desired transaction price in the electricity trading plan based on a prediction result of the price prediction unit and the renewable energy index; a trading plan creation unit that creates the power trading plan based on the desired trading price; a power generation prediction unit that predicts an amount of power generated by the renewable energy power to be traded in the power trading market, the price prediction unit predicts the first price based on a prediction result of the power generation prediction unit; When the renewable energy index is large, the trading price setting unit sets a first desired trading price indicating the desired trading price of the renewable energy electricity lower than the predicted first price for when the predicted amount of power generation is large and when the amount of power generation is small, compared to when the renewable energy index is small.

2. The information processing device of claim 1, wherein the transaction price setting unit sets the first desired transaction price higher than the predicted first price when the amount of power generation is large when the renewable energy index is small, compared to when the renewable energy index is large, and sets the first desired transaction price lower than the predicted first price when the amount of power generation is small.

3. The information processing device according to claim 1 , wherein the power generation prediction unit predicts the amount of power generation of the renewable energy power based on weather information of a region handled by the power trading market.

4. a power consumption prediction unit that predicts the power consumption of the power resource; The information processing device according to claim 1 , wherein the trading plan creation unit creates the power trading plan based on the desired trading price and a prediction result of the power consumption prediction unit.

5. The information processing device according to claim 1 , wherein the renewable energy index is a ratio of the renewable energy power to the power purchased in the power trading market, the ratio being set based on a user input.

6. The information processing device according to claim 1 , wherein the index setting unit sets the renewable energy index based on a ratio of the renewable energy power to the power purchased in the power trading market during a predetermined period.

7. The information processing device according to claim 1 , wherein the index setting unit sets the renewable energy index based on a predetermined law or regulation that is applied to the power resource.

8. The information processing device according to claim 1 , wherein the index setting unit sets the renewable energy index based on a predetermined tax system applied to the power resource.

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