Patent ID: 12248982

DETAILED DESCRIPTION OF EMBODIMENTS

Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. The same or corresponding parts in the drawings are designated by the same reference signs and the description thereof will not be repeated.

First Embodiment

FIG.1is a diagram schematically showing a configuration example of an electric power transmission and distribution system for electric power to be traded using an information processing device according to a first embodiment. With reference toFIG.1, an electric power transmission and distribution system1includes multiple electric power resources, charge and discharge facilities6A to6H, an electric power company9, a transmission line network PL, a trading market server3, and a communication network10.

The multiple electric power resources include, for example, electrified vehicles5A to5E, a factory7A, a company7B, a commercial facility7C, a house7D, and a store7E. Each electric power resource is configured to be able to transfer and receive electric power to and from other electric power resources, either through the transmission line network PL or directly.

The number of electrified vehicles and the number of charge and discharge facilities are not limited to the numbers shown in the drawings. Further, the facilities such as the factory7A are not limited to those shown in the drawings. In the following, each of the electrified vehicles5A to5E may not be distinguished and be referred to as the “electrified vehicle5”, and each of the charge and discharge facilities6A to6H may not be distinguished and be referred to as the “charge and discharge facility6”. Further, each of the factory7A, the company7B, the commercial facility7C, the house7D, and the store7E may not be distinguished and be referred to as the “facility7”.

The electrified vehicle5is an electrified vehicle that can travel by using electric power stored in a battery, and is, for example, a battery electric vehicle (BEV), a plug-in hybrid electric vehicle (PHEV), or the like. In the following, the electrified vehicle5is referred to as the BEV. The electrified vehicle5is configured to be electrically connectable to the charge and discharge facility6, and can transfer and receive electric power to and from the transmission line network PL or the facility7through the charge and discharge facility6.

The facility7is electrically connected to the transmission line network PL, and can transfer and receive electric power to and from the transmission line network PL. The facility7is also electrically connected to the charge and discharge facility6, and can transfer and receive electric power to and from the electrified vehicle5connected to the charge and discharge facility6.

The charge and discharge facility6is electrically connected to the transmission line network PL or the facility7. The charge and discharge facility6is electrically connectable to the electrified vehicle5through an electric power cable, and the electrified vehicle5can transfer and receive electric power to and from the transmission line network PL or the facility7through the charge and discharge facility6that is a connection destination.

The electric power generated by an electric power plant managed by the electric power company9can be supplied to each facility7through the transmission line network PL (system electric power grid), and can also be supplied to the electrified vehicle5A connected to the charge and discharge facility6A. Conventionally, the electric power has been supplied to the facility7and the electrified vehicle5exclusively from the electric power plant of the electric power company9through the transmission line network PL as described above. In this electric power transmission and distribution system1, the electric power trading between individuals or corporations (each facility7or each electrified vehicle5), that is, the P2P electric power trading, can be conducted.

The trading market server3provides a platform for conducting such P2P electric power trading. The trading market server3is configured to be able to communicate with the electrified vehicle5, the charge and discharge facility6, and the facility7through the communication network10. When the facility7or the electrified vehicle5desires the P2P electric power trading, the facility7or the electrified vehicle5(specifically, an agent that conducts the electric power trading of the facility7or the electrified vehicle5(described below)) bids for the trading market server3that manages the P2P electric power trading market in which the electric power trading is desired, by specifying, for example, a time zone in which the electric power is desired to be sold or purchased, the electric energy to be sold or purchased for each unit time zone, the trading price, and the like as bidding conditions. The trading market server3uses any algorithm to activate a contract of the electric power trading between a seller and a buyer of which the bidding conditions match, and processes bidding in which the bidding conditions do not match as a non-contract trading. In addition, the “bidding” means an act of ordering the electric power trading (purchase or sale), or the order itself. The “contract” means an act of determining to conduct the electric power trading for which the agent has bid, or the determination itself.

FIG.2is a diagram schematically showing an example of the P2P electric power trading market. With reference toFIG.2, in the P2P electric power trading market, the “agent” who bids for the P2P electric power trading market creates and executes the bidding plan, manages the contract, creates a charge and discharge plan based on the contract, and the like. The agent is provided for each facility7or the electrified vehicle5, and in the first embodiment, there are multiple mobile body agents2A to2D corresponding to the electrified vehicles5, multiple operator agents2E to2H corresponding to the factory7A and the like, and multiple housing agents21and2J corresponding to the houses. For example, to explain the electrified vehicle5as a representative, the mobile body agent of the electrified vehicle5creates the electric power trading plan (bidding plan) for the P2P electric power trading market, and the mobile body agent bids for the P2P electric power trading market (trading market server3).

In the following, the mobile body agents2A to2D, the operator agents2E to2H, and the housing agents21and2J may not be distinguished and be simply referred to as the “agent2”. The agent2is an “information processing device” that creates the electric power trading plan for causing the corresponding electric power resource to conduct the electric power trading through the P2P electric power trading market.

In the P2P electric power trading market, there are a “general trading market” and a “direct trading market”. The general trading market is a market in which electric power transmitted through the transmission line network PL is traded, and an unspecified large number of agents2can participate in the electric power trading. In the general trading market, the contract of the electric power trading is made according to a rule set as appropriate by an administrator who manages the P2P electric power trading market (matching). As a matching rule, for example, there is a method of concluding the trading transaction on a first-come-first-served basis when the asking price of the seller and the asking price of the buyer match in a predetermined unit time zone. As another matching rule, a method can be also adopted in which the bidding (order) of the seller and the buyer that are made in the unit time zone is organized temporarily and then the trading transaction is concluded at an appropriate price.

FIG.3is a diagram illustrating an example of bidding in the general trading market for the P2P electric power trading. With reference toFIG.3, in the general trading market, for each predetermined unit time zone (1, 2, . . . n), an unspecified large number of sellers bid a set of selling price and electric energy (p, q), and an unspecified large number of buyers bid a set of purchase price and electric energy (P, Q). The unit time zone is a time width (for example, 30 minutes) set in the general trading market. The trading of the electric energy is conducted for each electric energy (electric power×unit time zone length) transmitted in the unit time zone.

With reference toFIG.2again, the direct trading market is a market in which the electrified vehicle5moves to the location of the facility7and the trading of the electric power transmitted without going through the transmission line network PL is conducted, and only an agent having identification (ID) of the direct trading market can participate in the electric power trading. In the direct trading market, one market is configured for the facility7in which the charge and discharge facility6is installed. A server provided for each facility7may manage one direct trading market, or a common server may manage multiple direct trading markets by multiple facilities7. In the direct trading market, the contract of the electric power trading is made according to a rule uniquely set as appropriate by an administrator in each market (matching). As the matching rule, the above method described in the general trading market can be adopted.

FIG.4is a diagram illustrating an example of bidding in the direct trading market for the P2P electric power trading. With reference toFIG.4, in the direct trading market, for each predetermined unit time zone (1, 2, . . . n), a seller proposes a set of selling price and electric energy (p, q), and multiple buyers having ID of the direct trading market bid a set of purchase price and electric energy (P, Q). The unit time zone is a time width set individually in the direct trading market. The trading of the electric energy is conducted for each electric energy (electric power×unit time zone length) transmitted in the unit time zone.

FIG.5is a diagram showing an example of hardware configurations of the agent2and the trading market server3. With reference toFIG.5, the agent2includes a processor21, a memory22, and a communication device23. The agent2is provided for each electric power resource such as the electrified vehicle5and the facility7(factory7A, house7D, etc.). The agent2may be provided in the corresponding electric power resource, or may be provided in the cloud capable of communicating with the corresponding electric power resource.

The processor21is an arithmetic unit (computer) that executes various processes by executing various programs. The processor21is composed of a central processing unit (CPU), a field-programmable gate array (FPGA), a graphics processing unit (GPU), and the like. The processor21may be configured by a processing circuitry.

The memory22stores programs and data for the processor21to execute various processes. The memory22is composed of a storage medium such as a read-only memory (ROM) and a random access memory (RAM). The memory22stores an arithmetic program221, resource information222, and external information223.

The arithmetic program221specifies processes executed by the processor21. For example, the arithmetic program221includes a program for making a bid regarding the electric power trading in the P2P electric power trading market managed by the trading market server3for the trading market server3.

The resource information222includes information on the electric power resource corresponding to the agent2(for example, the electrified vehicle5), and particularly includes information on bidding and the contract of the electric power trading.

FIG.6is a diagram showing an example of the resource information222. InFIG.6, as an example, the resource information222in the agent2(mobile body agent) of the electrified vehicle5is shown.

With reference toFIG.6, the resource information222includes ID, category information, trip information, state of charge (SOC) information, connection information, bidding information, contract information, the charge and discharge plan, and a charge and discharge record.

The ID includes identification information for identifying the electric power resource (electrified vehicle5in this example). The category information includes information on a category of the electric power resource, and includes, for example, information for identifying the electrified vehicle, the operator, the house, and the like. The trip information includes information on a travel history such as the past travel route and the travel time. The SOC information includes information on the electric energy currently stored in an electric power storage device. The connection information includes information for identifying whether the electrified vehicle5is currently connected to the charge and discharge facility6. The bidding information includes information on the past bidding history and information on the bidding currently in progress. The contract information includes information on the past contract history and information for identifying whether the contract is made for the bidding currently in progress. The charge and discharge plan includes information on the charge and discharge plan of the electric power resource based on the contract. The charge and discharge record includes information on a charge and discharge result for the above charge and discharge plan.

The trip information and the connection information are information used by the agent2(mobile body agent) of the electrified vehicle5, and as for the facility7(factory7A, house7D, etc.), the column for such information is left blank.

With reference toFIG.5again, the external information223includes a price of the system electric power provided by the electric power company9, weather information (amount of solar radiation, weather, wind speed, etc.) of an area of the P2P electric power trading market for bidding, and information on an electric power generation facility of the renewable energy in the market (solar power generation facility, wind power generation facility, hydroelectric power generation facility, etc.). The agent2acquires the external information223from an external server device (which may be the trading market server3) through the communication network10.

The communication device23transmits and receives various data to and from the trading market server3through the communication network10.

The trading market server3includes a processor31, a memory32, and a communication device33. The trading market server3is a device that manages the P2P electric power trading between the electric power resources in the P2P electric power trading market (general trading market and direct trading market), and executes a process related to the electric power trading.

The processor31is an arithmetic unit (computer) that executes various processes by executing various programs. The processor31is composed of a CPU, an FPGA, a GPU, and the like. The processor31may be configured by a processing circuitry.

The memory32stores programs and data for the processor31to execute various processes. The memory32is composed of a storage medium such as a ROM and a RAM. The memory32stores an arithmetic program321and agent information322.

The arithmetic program321specifies processes executed by the processor31. For example, the arithmetic program321includes a program for executing a bidding process for accepting the bidding from the multiple agents2and a contract process based on the bidding. The contract process is a process in which the contract of the electric power trading is activated between the seller and the buyer of which the bidding conditions match, and bidding in which the bidding conditions do not match is processed as a non-contract trading.

The agent information322includes information on the agent2participating in the P2P electric power trading market managed by the trading market server3, and particularly includes information on the bidding and the contract for the electric power trading for each agent2.

FIG.7is a diagram showing an example of the agent information322. With reference toFIG.7, the agent information322includes ID, category information, bidding information, and contract information.

The ID includes identification information for identifying the agent2participating in the P2P electric power trading market managed by the trading market server3. The category information includes information on a category of the electric power resource, and includes, for example, information for identifying the electrified vehicle, the operator, the house, and the like. The bidding information includes information on the past bidding history for each agent2and information on the bidding currently in progress. The contract information includes information on the past contract history for each agent2and information for identifying whether the contract is made for the bidding currently in progress.

With reference toFIG.5again, the communication device33transmits and receives various data to and from the agent2through the communication network10.

In the P2P electric power trading market composed of the agent2and the trading market server3described above, the agent2predicts use of the corresponding electric power resource (in the case of the electrified vehicle5, a user predicts use of the electrified vehicle5), and predicts an electric power trading price in the electric power trading market during the time zone when the agent2can participate in the electric power trading. Then, the agent2creates the electric power trading plan (bidding plan) that will be optimized in terms of cost under the constraint of the upper and lower limits of the SOC (chargeable and dischargeable range) to be satisfied in the electric power storage device of the corresponding electric power resource, and makes a bid regarding the electric power trading for the trading market server3.

Here, when the agent2creates the electric power trading plan, in addition to the viewpoint of cost optimization, there is a case in which it is desired to adjust the degree of procurement of the renewable energy electric power against the background of social needs for improving utilization of the renewable energy. For example, it is considered, when the renewable energy electric power (electric power derived from solar power generation, wind power generation, etc.) is surplus, the degree of procurement of the renewable energy electric power that is expected to reduce the cost is increased, and when the electric power generation amount of the renewable energy electric power is small, the degree of procurement of the renewable energy electric power that can increase the cost is reduced.

Therefore, in the agent2according to the first embodiment, the electric power trading plan on which the degree of procurement of the renewable energy electric power can be reflected is created in addition to the viewpoint of cost optimization. Hereinafter, detailed description will be made.

FIG.8is a block diagram functionally showing a configuration of the agent2according to the first embodiment. With reference toFIG.8, the agent2includes an external information acquisition unit102, a renewable energy electric power generation amount predicting unit104, a market electric power price predicting unit106, a renewable energy index setting unit108, and a trading price setting unit110, an electric power consumption predicting unit112, and an electric power trading plan creating unit114.

The external information acquisition unit102acquires weather information of the area of the P2P electric power trading market for bidding from an external server device (not shown). The weather information is information on the weather forecast of the above area, and includes the forecast information such as the amount of solar radiation, the weather, and the wind speed for each time zone. The P2P electric power trading market for bidding is an electric power trading market in an area where the corresponding electric power resource is desired to be charged and discharged based on the P2P electric power trading, and is determined based on the usage prediction of the corresponding electric power resource. For example, in the case of the agent2(mobile body agent) of the electrified vehicle5, the P2P electric power trading market for bidding can be determined based on the predicted position (for example, the destination) of the electrified vehicle5.

Further, the external information acquisition unit102acquires information on the electric power generation facility of the renewable energy in the P2P electric power trading market for bidding from then external server device (not shown). The electric power generation facility of the renewable energy includes the solar power generation facility, the wind power generation facility, the hydroelectric power generation facility, and the like. Information on the electric power generation facility of the renewable energy includes information on the category and the number of the electric power generation facilities, the rated output or the maximum output of each electric power generation facility in the area covered by the P2P electric power trading market, and the like. The information acquired by the external information acquisition unit102is stored in the memory22as the external information223.

The renewable energy electric power generation amount predicting unit104predicts the electric power generation amount of the renewable energy in the P2P electric power trading market for bidding based on the weather information and the electric power generation facility information acquired by the external information acquisition unit102. For example, in the case of the solar power generation facility, when the time zone is daytime, the weather is sunny, and there are many solar power generation facilities, the renewable energy electric power generation amount predicting unit104predicts that the electric power generation amount of the renewable energy derived from the solar power generation is large. On the other hand, when the weather is rainy or the time zone is nighttime, the renewable energy electric power generation amount predicting unit104predicts that the electric power generation amount of the renewable energy derived from the solar power generation is small. Further, in the case of the wind power generation facility, when the wind is strong and there are many wind power generation facilities, the renewable energy electric power generation amount predicting unit104predicts that the electric power generation amount of the renewable energy derived from the wind power generation is large.

The market electric power price predicting unit106predicts the price (unit price) of the electric power (purchased electric power and sold electric power) traded in the P2P electric power trading market for bidding. In the P2P electric power trading market according to the first embodiment, the renewable energy electric power derived from the electric power generation facility of the renewable energy and the non-renewable energy electric power (electric power derived from a thermal power generation, etc.) which is not applicable to the renewable energy electric power are separately traded. For example, when the renewable energy electric power is traded, a tag (renewable energy tag) indicating that the traded electric power is the renewable energy electric power is attached, so that the renewable energy electric power can be distinguished from the non-renewable energy electric power. Alternatively, within the P2P electric power trading market, the market dealing with the trading of the renewable energy electric power and the market dealing with the trading of the non-renewable energy electric power may be separated.

Then, in the first embodiment, the market electric power price predicting unit106separately predicts the price of the renewable energy electric power (first price) and the price of the non-renewable energy electric power (second price) as for the purchase price. The price of the renewable energy electric power is predicted based on the prediction result of the renewable energy electric power generation amount predicting unit104.

For example, when the renewable energy electric power generation amount predicting unit104predicts that the electric power generation amount of the renewable energy is large, it is expected that a surplus of the renewable energy electric power is generated. Therefore, the market electric power price predicting unit106predicts that the price of the renewable energy electric power is low. On the other hand, when the renewable energy electric power generation amount predicting unit104predicts that the electric power generation amount of the renewable energy is small, the circulation amount of the renewable energy electric power is limited. Therefore, the market electric power price predicting unit106predicts that the price of the renewable energy electric power is high. The high price (low price) may be high (low) with respect to a certain standard price, or may be high (low) with respect to the price of the non-renewable energy electric power.

The price of the non-renewable energy electric power can be predicted based on, for example, the price of the system electric power available from the electric power company9.

The renewable energy index setting unit108sets a “renewable energy index” indicating the degree of the renewable energy electric power in the electric power purchased in the P2P electric power trading market (purchased electric power). In the P2P electric power trading market according to the first embodiment, as described above, the renewable energy electric power and the non-renewable energy electric power can be traded separately, and the renewable energy index setting unit108can adjust the degree at which the renewable energy electric power is included at the time of purchasing the electric power.

In the first embodiment, the user of the corresponding electric power resource can set the ratio of the renewable energy electric power in the purchased electric power (desired renewable energy ratio by the user) from an input device (not shown). As for setting of the desired renewable energy ratio by the user, a value of the ratio of the renewable energy electric power may be used as it is or the ratio of the renewable energy electric power may be increased or reduced with respect to a certain reference ratio. The user can set a high desired renewable energy ratio from the input device, for example, when the user wishes to increase the purchase amount of the renewable energy electric power.

The renewable energy index is defined as, for example, an index that increases as the ratio of the renewable energy electric power in the purchased electric power increases and decreases as the ratio of the renewable energy electric power in the purchased electric power decreases. The renewable energy index setting unit108sets the renewable energy index based on the desired renewable energy ratio set by the user.

The trading price setting unit110sets a desired trading price for bidding for the P2P electric power trading market from the prediction result of the electric power trading price by the market electric power price predicting unit106and the renewable energy index set by the renewable energy index setting unit108. Specifically, the trading price setting unit110changes the price (first price) of the renewable energy electric power predicted by the market electric power price predicting unit106according to the renewable energy index. Hereinafter, description will be made with reference toFIG.9.

FIG.9is a diagram showing a relationship between a predicted electric power generation amount of the renewable energy electric power and a desired trading price (unit price) of the renewable energy electric power. With reference toFIG.9, a line k1shows the price of the renewable energy electric power predicted by the market electric power price predicting unit106based on the electric power generation amount of the renewable energy electric power predicted by the renewable energy electric power generation amount predicting unit104. As described above, when it is predicted that the electric power generation amount of the renewable energy is large, it is predicted that the price of the renewable energy electric power is low. On the other hand, when it is predicted that the electric power generation amount of the renewable energy is small, it is predicted that the price of the renewable energy electric power is high.

A line k2indicates the desired trading price of the renewable energy electric power set by the trading price setting unit110when the renewable energy index is large (the desired renewable energy ratio is high). The line k2is obtained by changing the line k1such that the price fluctuation based on the predicted electric power generation amount of the renewable energy electric power increases with respect to the predicted price of the renewable energy electric power indicated by the line k1. That is, when the predicted electric power generation amount of the renewable energy electric power is large with respect to the predicted price of the renewable energy electric power indicated by the line k1, the trading price setting unit110sets the desired trading price of the renewable energy electric power to be lower than the predicted price. When the predicted electric power generation amount of the renewable energy electric power is small, the trading price setting unit110sets the desired trading price of the renewable energy electric power to be higher than the predicted price. As a result, in an electric power trading plan described below, a trading plan is created in which the renewable energy electric power is actively purchased during the time zone when the electric power generation amount of the renewable energy electric power is large.

A line k3indicates the desired trading price of the renewable energy electric power set by the trading price setting unit110when the renewable energy index is small (the desired renewable energy ratio is low). The line k3is obtained by changing the line k1such that the price fluctuation based on the predicted electric power generation amount of the renewable energy electric power decreases with respect to the predicted price of the renewable energy electric power indicated by the line k1. That is, the trading price setting unit110sets the desired trading price such that the dependence of the electric power generation amount of the renewable energy electric power on the trading price of the renewable energy electric power becomes small. As a result, in the electric power trading plan described below, a trading plan is not created in which the renewable energy electric power is actively purchased as in the case where the renewable energy index is large.

The desired trading price of the non-renewable energy electric power is set to the predicted price predicted by the market electric power price predicting unit106.

With reference toFIG.8again, the electric power consumption predicting unit112predicts the electric power consumption in the electric power storage device of the corresponding electric power resource. For example, in the case of the agent2(mobile body agent) of the electrified vehicle5, the electric power consumption predicting unit112predicts the electric power consumption of the battery mounted on the electrified vehicle5due to the use (travel) of the electrified vehicle5. The prediction result of the electric power consumption predicting unit112is used to set constraint conditions of the upper and lower limits of the SOC to be satisfied in the electric power storage device of the corresponding electric power resource when the electric power trading plan described below is created.

The electric power trading plan creating unit114creates the electric power trading plan (bidding plan) for conducting the electric power trading in the P2P electric power trading market based on the desired trading price set by the trading price setting unit110and the electric power consumption of the electric power resource predicted by the electric power consumption predicting unit112. As an example, the electric power trading plan creating unit114creates a cost-optimized electric power trading plan under the constraint of the upper and lower limits of the SOC (chargeable and dischargeable range) to be satisfied in the electric power storage device of the corresponding electric power resource.

Specifically, the objective function Fcost for calculating the cost in the electric power trading is set, and under the constraint condition (chargeable and dischargeable range) of the upper and lower limits of the SOC to be satisfied in the electric power storage device of the corresponding electric power resource, electric energy to be traded for minimizing the objective function Fcost is searched. As an example, the objective function Fcost as shown in the following formula can be set.

[Formula⁢1]Fcost⁢(i,n)=∑k=ii+n{r⁡(k)·F⁡(k)}(1)

Here, k (i to i+n, i is the current unit time zone) is a code of the unit time zone, and r(k) is a variable that becomes “1” when the electric power resource procures the electric power through the P2P electric power trading market in the unit time zone k, and becomes “0” in other cases. F(k) is a cost when the electric power resource procures the
[Formula 2]
F(k)={Qbr(k)−Qsr(k)}·Pr(k)+{Qbn(k)−Qsn(k)}·Pn(k)  (2)

Here, Pr(k) is a desired trading price (unit price) of the renewable energy electric power set by the trading price setting unit110, and Qbr(k) and Qsr(k) are electric energy desired to be purchased and electric energy desired to be sold in the renewable energy electric power in the unit time zone k, respectively. Pn(k) is a desired trading price (unit price) of the non-renewable energy electric power set by the trading price setting unit110, that is, Pn(k) is a predicted price of the non-renewable energy electric power predicted by the market electric power price predicting unit106. Qbn(k) and Qsn(k) are electric energy desired to be purchased and electric energy desired to be sold in the non-renewable energy electric power in the unit time zone k, respectively.

On the other hand, the SOC of the electric power storage device of the electric power resource is given by the following formula.

[Formula⁢3]SOC⁡(i,n)=SOC⁡(i)+∑k=ii+n{Qbr⁡(k)+Qbn⁡(k)-Qsr⁡(k)-Qsn⁡(k)-Qtrip⁡(k)}/C(3)

Here, Qtrip(k) is a predicted value of the electric power consumption of the electric power resource in the unit time zone k. When the electric power resource is the electrified vehicle5, Qtrip(k) is a predicted value of the electric power consumption due to the travel of the electrified vehicle5in the unit time zone k, and is calculated from the electricity cost and the like of the electrified vehicle5. C is a conversion coefficient for converting the electric energy into the SOC.

Then, the upper limit value SOC_upper and the lower limit value SOC_lower are set for the SOC, and the constraint condition is set such that the SOC satisfies the following formula.
[Formula 4]
SOC_lower≤SOC(k)≤SOC_upper  (4)

As described above, for the objective function Fcost represented by the formula (1), a condition in which the objective function Fcost is minimized is searched while the SOC constraint condition represented by the formula (4) is satisfied (optimization of the objective function Fcost). For the optimization calculation of the objective function Fcost, any arithmetic method such as a linear programming method or a convex optimization method can be used.

As described above, in the first embodiment, the renewable energy index indicating the degree of procurement of the renewable energy electric power is set, and the desired trading price in consideration of the renewable energy index is set. Then, the electric power trading plan is created based on the objective function Fcost using the desired trading price in consideration of the renewable energy index. As a result, the degree of procurement of the renewable energy electric power can be reflected on the electric power trading plan, and the electric power trading plan in consideration of the degree of procurement of the renewable energy electric power can be created.

FIG.10is a flowchart showing an example of a processing procedure executed when the agent2bids for the P2P electric power trading market. With reference toFIG.10, the agent2(processor21) acquires external information on the P2P electric power trading market for bidding from the external server device through the communication network10(step S10). The external information includes weather information (amount of solar radiation, weather, wind speed, etc.) of the area covered by the market, information on the electric power generation facility of the renewable energy in the market (solar power generation facility, wind power generation facility, hydroelectric power generation facility, etc.), and a cost and the like of the system electric power provided by the electric power company9.

Next, the agent2predicts the electric power generation amount of the renewable energy electric power in the P2P electric power trading market for bidding based on the weather information acquired in step S10and the information on the electric power generation facility of the renewable energy (step S20).

Then, the agent2predicts the price (unit price) of the renewable energy electric power traded in the market based on the electric power generation amount of the renewable energy electric power predicted in step S20(step S30). Specifically, as shown by the line k1inFIG.9, when it is predicted that the electric power generation amount of the renewable energy is large, the agent2predicts that the price of the renewable energy electric power is low, and when it is predicted that the electric power generation amount of the renewable energy is small, the agent2predicts that the price of the renewable energy electric power is high.

Next, the agent2acquires the desired renewable energy ratio set by the user of the corresponding electric power resource from the input device, and sets the renewable energy index based on the desired renewable energy ratio (step S40). As described above, the renewable energy index is an index indicating the degree of the renewable energy electric power in the electric power purchased in the P2P electric power trading market for bidding (purchased electric power).

Then, the agent2sets the desired trading price in the P2P electric power trading market for bidding from the price of the renewable energy electric power predicted in step S30and the renewable energy index set in step S40(step S50). Specifically, as described with reference toFIG.9, the price of the renewable energy electric power predicted in step S30is changed according to the renewable energy index, so that the desired trading price of the renewable energy electric power is set. The desired trading price of the non-renewable energy electric power is set based on the price of the system electric power acquired in step S10.

Next, The agent2predicts the electric power consumption in the electric power storage device of the corresponding electric power resource (step S60). When the agent2is an agent (mobile body agent) of the electrified vehicle5, the agent2predicts the electric power consumption of the battery due to the travel of the electrified vehicle5based on the past electricity cost.

Then, the agent2searches for the condition in which the objective function Fcost represented by the above formula (1) is minimized under the constraint of the SOC in the electric power storage device of the corresponding electric power resource represented by the above formula (4), so that the optimum electric power trading plan is created (step S70). That is, the agent2executes the cost optimization calculation using the formulas (1) to (4) and creates the bidding plan for the P2P electric power trading market.

When the electric power trading plan (bidding plan) is created in step S70, the agent2bids for the P2P electric power trading market (trading market server3) based on the electric power trading plan (step S80).

As described above, in the first embodiment, the price of electric power (renewable energy electric power/non-renewable energy electric power) traded in the P2P electric power trading market is predicted. Further, the renewable energy index indicating the degree of the renewable energy electric power in the electric power purchased in the P2P electric power trading market is set. Then, the desired trading price in consideration of the degree of procurement of the renewable energy electric power is set from the predicted electric power price and the set renewable energy index, and the electric power trading plan is created based on the desired trading price. As described above, according to the first embodiment, it is possible to create the electric power trading plan in consideration of the degree of procurement of the renewable energy electric power.

Further, in the first embodiment, the electric power generation amount of the renewable energy electric power traded in the market is predicted based on the weather information of the area covered by the P2P electric power trading market, and the price of the renewable energy electric power is predicted based on the prediction result. Therefore, the price of the renewable energy electric power can be appropriately predicted. As a result, the desired trading price is appropriately set, and the appropriate electric power trading plan can be created based on the desired trading price.

Further, in the first embodiment, the electric power consumption of the electric power resource is predicted, and the electric power trading plan is created from the prediction result and the desired trading price. Therefore, the appropriate electric power trading plan can be created based on the prediction of the electric power consumption of the electric power resource.

Further, in the first embodiment, the renewable energy index is a ratio of the renewable energy electric power in electric power purchased in the electric power trading market, the ratio of the renewable energy electric power being set based on the input from the user. Therefore, it is possible to create the electric power trading price on which the user's wish is reflected for the above ratio of the renewable energy electric power.

Second Embodiment

In the first embodiment described above, the user of the corresponding electric power resource sets the ratio of the renewable energy electric power (desired renewable energy ratio) in the purchased electric power from the input device, and the renewable energy index is set based on the desired renewable energy ratio. In a second embodiment, the renewable energy index is set based on the ratio of the renewable energy electric power in the electric power purchased in the P2P electric power trading market in the past (renewable energy usage ratio).

FIG.11is a block diagram functionally showing a configuration of an agent according to the second embodiment. With reference toFIG.11, an agent2# further includes a renewable energy usage ratio calculating unit116in the configuration of the agent2according to the first embodiment shown inFIG.8, and includes a renewable energy index setting unit108A instead of the renewable energy index setting unit108.

The renewable energy usage ratio calculating unit116calculates the ratio of the renewable energy electric power in the electric power purchased through the P2P electric power trading market in the past predetermined period (renewable energy usage ratio). The predetermined period can be set as appropriate, and is, for example, several months. Then, the renewable energy usage ratio calculating unit116sets the ratio of the renewable energy electric power (trading renewable energy ratio) in the electric power trading to be bid for this time based on the calculated past renewable energy usage ratio. For example, when the past renewable energy usage ratio is lower than the appropriately set reference ratio, the renewable energy usage ratio calculating unit116sets the trading renewable energy usage ratio to a higher value than the past renewable energy usage ratio in order to increase the renewable energy usage ratio.

Then, the renewable energy index setting unit108A sets the renewable energy index based on the trading renewable energy ratio set by the renewable energy usage ratio calculating unit116. Specifically, the renewable energy index is set as appropriate such that the higher the trading renewable energy ratio is, the larger the renewable energy index is, and the lower the trading renewable energy ratio is, the smaller the renewable energy index is.

Other functions of the agent2# are the same as those of the agent2according to the first embodiment shown inFIG.8.

FIG.12is a flowchart showing an example of a processing procedure executed when the agent2# according to the second embodiment bids for the P2P electric power trading market. This flowchart corresponds to the flowchart ofFIG.10described in the first embodiment.

With reference toFIG.12, the processes of steps S110to S130and S150to S180are the same as the processes of steps S10to S30and S50to S80of the flowchart shown inFIG.10, respectively.

In this flowchart, when the price (unit price) of the renewable energy electric power traded in the P2P electric power trading market for bidding is predicted in step S130, the agent2# calculates the trading renewable energy ratio in the electric power trading to be bid for this time based on the renewable energy usage ratio in the past predetermined period, and sets the renewable energy index based on the trading renewable energy ratio (step S140).

Then, when the renewable energy index is set, the agent2# shifts the process to step S150, and the desired trading price in the P2P electric power trading market for bidding is set from the price of the renewable energy electric power predicted step S130and the renewable energy index set in step S140.

As described above, in the second embodiment, the trading renewable energy ratio in the electric power trading to be bid for this time is calculated based on the renewable energy usage ratio in the past predetermined period, and the renewable energy index is set based on the trading renewable energy ratio. Therefore, it is possible to create the electric power trading plan based on the renewable energy usage ratio in the past predetermined period. For example, when the above ratio of renewable energy electric power in the predetermined period is low, the electric power trading plan can be created such that the ratio is increased.

Modification

As described above, in the first embodiment, the renewable energy index indicating the degree of the renewable energy electric power in the electric power purchased in the P2P electric power trading market (purchased electric power) is set based on the desired renewable energy ratio of the user. In the second embodiment, the renewable energy index indicating the degree of the renewable energy electric power in the electric power purchased in the P2P electric power trading market (purchased electric power) is set based on the trading renewable energy ratio according to the renewable energy usage ratio in the past predetermined period. However, the renewable energy index may be set based on other parameters.

Specifically, the renewable energy index may be set based on a predetermined law applied to the corresponding electric power resource. For example, in a case where the corresponding electric power resource is the electrified vehicle5, and the usage ratio of the renewable energy used when the electrified vehicle5enters a certain area (nature conservation area, etc.) is stipulated by the ordinance and the like, the renewable energy index may be set based on the renewable energy usage ratio specified in the ordinance.

Alternatively, the renewable energy index may be set based on a predetermined tax system applied to the corresponding electric power resource. For example, when the corresponding electric power resource is the electrified vehicle5, and the tax rate such as the environmental tax is set based on the usage ratio of the renewable energy determined according to the year of manufacture of the electrified vehicle5, the renewable energy index may be set based on the renewable energy usage ratio applied to the electrified vehicle5.

The embodiments disclosed this time should be considered to be exemplary and not restrictive in all respects. The technical scope of the present disclosure is determined based on the statements in the scope of claims rather than the description of the embodiments described above, and is intended to include all modifications within the meaning and scope equivalent to the scope of claims.