Information processing apparatus, information processing method, and program

Abstract

To highly accurately obtain an appropriate bid amount of a transaction object in a market of electric power or the like.SOLUTION: The information processing apparatus includes a processing unit. The processor is configured to calculate, using a surplus amount that is a surplus of a trading amount of a trading target in one or more first markets and board information of a second market different from the first markets, a plurality of first trading amounts that are trading amounts distributed to each of a plurality of trading periods in the second market among the surplus amount. The processing unit calculates a bidding plan including a plurality of first trading amounts and a plurality of first bidding prices corresponding to the plurality of first trading amounts.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] An embodiment of the present invention relates to an information processing device, an information processing method, and a program. [Background technology]

[0002] There are known electricity trading markets for trading electricity generated by power generation companies and other entities. For example, in Japan, electricity is traded in multiple markets operated by the Japan Electric Power Exchange (JEPX). These multiple markets include, for example, spot markets and advance markets. The spot market is a market where bids are made up to the day before for electricity to be sold or purchased the next day, and the transaction is concluded. The advance market (intraday market) is a market that can be used up until just before actual supply and demand.

[0003] Electricity procured in the spot market may be stored in an energy storage device (energy storage facility) and managed according to a predetermined charging and discharging plan. Furthermore, the stored electricity may become surplus electricity due to deviations from the plan. It is desirable to efficiently utilize such surplus electricity by trading it in a market, such as the hourly market. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 6915233 Summary of the Invention [Problem to be solved by the invention]

[0005] An object of the present invention is to provide an information processing device, an information processing method, and a program that can more accurately determine an appropriate bid amount for a trading object in a market such as electricity. [Means for solving the problem]

[0006] An information processing device according to an embodiment includes a processing unit. The processing unit calculates, using a surplus volume, which is a surplus of the trading volume of a trading object in one or more first markets, and order book information in a second market different from the first market, a plurality of first trading volumes, which are trading volumes to be allocated from the surplus volume to each of a plurality of trading periods in the second market. The processing unit calculates a bidding plan including the plurality of first trading volumes and a plurality of first bid prices corresponding to the plurality of first trading volumes. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a block diagram of an information processing apparatus according to an embodiment. [Figure 2] FIG. 4 is a diagram showing an example of a data structure of power storage device information. [Figure 3] FIG. 2 is a diagram showing an example of a data structure of market information. [Figure 4] FIG. 4 is a diagram showing an example of a data structure of energy source information. [Figure 5] FIG. 10 is a diagram showing an example of output data. [Figure 6] 10 is a flowchart of a plan creation process according to an embodiment. [Figure 7] 10A to 10C are diagrams for explaining application examples of the embodiment. [Figure 8] FIG. 10 is a diagram showing an example of a bidding plan calculation process according to an embodiment. [Figure 9] FIG. 1 is a hardware configuration diagram of an information processing apparatus according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0008] A preferred embodiment of an information processing device according to the present invention will be described in detail below with reference to the accompanying drawings. In the following, an example will be described in which the market and the trading object in the market are an electricity trading market and electricity, but the market and trading object are not limited to these. In this example, the trading volume, which represents the amount of trading object (electricity) traded in the market, corresponds to the amount of electricity sold or purchased. In addition, in the following embodiment, surplus amount (surplus energy amount), which is the surplus amount of electricity, also becomes a trading object in the market.

[0009] As described above, power procured in the spot market may be stored in a power storage device and managed. In this embodiment, the power (storage amount) stored in the power storage device in this manner, or the power generated by transactions in the supply and demand balancing market, is sold as surplus power in the hourly market. The following problems may arise in the operation of the power storage device. (P1) Planning issues: When operating a power storage device, the charging and discharging schedule must be planned in advance. If the power stored in the power storage device is not used efficiently by the next charging time, the excess power is treated as an imbalance, which can result in economic losses. This reduces the operational efficiency of the power storage device and has a negative impact on profitability. (P2) Issues with trading efficiency in the market for stored energy: When trading energy from energy storage devices in the time-ahead market, if bids are made without taking into account power sources (energy sources) other than energy storage devices, the success rate of bids may decrease depending on market trends and the status of other energy sources. This leads to missed opportunities to make maximum use of the energy from energy storage devices and optimize revenues. (P3) Issues with competitiveness in the pre-hours market: The pre-hours market is a competitive intraday market. Therefore, if a bid is made without taking into account the activities of other players in the market, the risk of the bid not being executed increases. In addition, due to large price fluctuations in the market, even if a bid is executed, the expected profits are often not guaranteed. This leaves energy storage device operators at the mercy of market uncertainty.

[0010] In this embodiment, the surplus amount generated by the operation of the power storage device is traded in the market, thereby making more efficient use of the surplus amount. In this case, in this embodiment, an appropriate bid amount for the surplus amount in the market is determined with high accuracy so that profitability can be improved.

[0011] This embodiment can also address the problem of a significant imbalance between power supply and demand that accompanies the increased introduction of renewable energy sources. That is, this embodiment effectively utilizes a power storage device to absorb fluctuations in power supply resulting from highly volatile renewable energy sources such as photovoltaic (PV) and wind power, thereby maintaining the supply-demand balance. This increases the stability of the entire electricity market and makes it possible to build a more reliable power supply system.

[0012] For example, the information processing apparatus according to the embodiment has the following functions. - Create a plan to allocate the electricity (storage capacity) stored in the power generation company's storage devices to multiple trading periods (products) in the time-ahead market, with the period until the next charging cycle as the limit, and sell it efficiently. - Drawing up a plan to supply the energy storage capacity to the market at the optimal bidding, taking into account market supply and demand trends and price fluctuations. When trading stored energy in the hour-ahead market, the system takes into account trading plans and market conditions from other energy sources, and adjusts power allocation and bidding plans based on this information to increase the success rate of bids and maximize profitability.

[0013] In this embodiment, the surplus amount to be bid on the time-ahead market is the amount of stored electricity obtained by storing the surplus amount of electricity sold in a power storage device. The stored electricity amount is, for example, the amount of electricity purchased directly from the JEPX spot market and charged in a power storage device. The surplus amount to be bid on the time-ahead market may be the surplus amount that occurs after bidding in the supply and demand balancing market. That is, in this embodiment, the surplus amount is the surplus amount of electricity trading volume in one or more markets MA (first markets) including the spot market and the supply and demand balancing market. Note that the time-ahead market is a market different from the market MA and corresponds to the market MB (second market) where the surplus amount is traded.

[0014] 1 is a block diagram showing an example of the configuration of an information processing device 100 according to an embodiment. As shown in FIG. 1, the information processing device 100 includes a storage unit 120, an acquisition unit 101, an output control unit 102, a trading volume calculation unit 110, and a plan calculation unit 130.

[0015] The storage unit 120 stores various types of information used by the information processing device 100. For example, the storage unit 120 stores power storage device information 121, market information 122, order book information 123, and energy source information .

[0016] The power storage device information 121, the market information 122, the board information 123, and the energy source information 124 correspond to information acquired (input) as input data by, for example, the acquisition unit 101. The power storage device information 121, the market information 122, the board information 123, and the energy source information 124 may be represented in any data structure, and are represented, for example, in a CSV (Comma Separated Value) file format.

[0017] The power storage device information 121 is information relating to a power storage device that will be a supplier of a surplus amount (amount of stored power) to be bid on the time-ahead market. FIG. 2 is a diagram showing an example of the data structure of the power storage device information 121.

[0018] As shown in FIG. 2, the power storage device information 121 includes a power storage device ID, a rated output, a capacity, a charge / discharge efficiency, a surplus amount, a confirmed sold power, and a confirmed procured power.

[0019] The energy storage device ID is identification information that identifies the energy storage device that is the subject of the calculation. The rated output represents the rated output of the PCS (Power Conditioning System) equipped in the energy storage device. The capacity represents the capacity of the energy storage device. The charge / discharge efficiency represents the charge / discharge efficiency of the energy storage device. The surplus amount represents the amount of surplus electricity (storage amount) stored in the energy storage device. The confirmed sales power represents the electricity stored in the energy storage device for which a sales (sale) contract has been confirmed. The confirmed procurement power represents the electricity for which a procurement (purchase) contract has been confirmed for storage in the energy storage device.

[0020] The type indicates the type (classification) of data for each item included in the power storage device information 121. The type includes, for example, a character string and a numerical value. In FIG. 2, the unit for the numerical value is also shown. These units are merely examples and are not limiting. The same applies to FIGS. 3 to 5 described later. The "30 minutes" in the unit corresponds to the target period (frame) for trading in the market.

[0021] Returning to the explanation of FIG. 1, market information 122 is information relating to the pre-hour market, and includes, for example, product information (frame information) in the pre-hour market. Product information is information about products in the market. For example, in the JEPX electricity trading market, a day is divided into 48 30-minute frames, and each frame is a product. A product can be interpreted as corresponding to a trading period in each electricity trading market.

[0022] FIG. 3 is a diagram showing an example of the data structure of market information 122. As shown in FIG. 3, market information 122 includes the electricity delivery date, product ID, minimum selling price, maximum purchasing price, the latest contract price in the aforesaid market, the time remaining until gate closure, and the time until the next calculation. Market information 122 corresponds to information that clarifies which product is the subject of trading and the trading conditions. Market information 122 can be obtained, for example, from a market management entity (such as JEPX).

[0023] The electricity delivery date indicates the date on which electricity will be delivered. The product ID is identification information that identifies the product. When the product is a 30-minute unit as described above, for example, 48 strings from "01" to "48" are used as the product ID. The minimum selling price indicates the minimum price at which sales will be made. The maximum buying price indicates the maximum price at which purchases will be made. The latest contract price indicates the latest contract price in the pre-hour market. The remaining time until gate closure indicates the time until the gate closure (closing) of the pre-hour market. The time until the next calculation indicates the time until the calculation process for the surplus bid amount is next executed.

[0024] Returning to the explanation of FIG. 1, the depth information 123 is depth information for each commodity in the pre-hours market. The depth information 123 includes, for example, for each commodity, the latest execution performance value, transaction summary information, and buying and selling information during bidding. The execution performance value includes, for example, the execution volume and execution price. The summary information includes, for example, the execution volume, the lowest selling price, the highest buying price, and the average execution price. The buying and selling information during bidding includes, for example, the selling bid volume, selling bid price, buying bid volume, and buying bid price during bidding.

[0025] The energy source information 124 is information stored when a power generation company owns an energy source ES other than a power storage device. The energy source ES is, for example, a renewable energy source such as PV or wind power generation. FIG. 4 is a diagram showing an example of the data structure of the energy source information 124. Note that FIG. 4 shows an example of the energy source information 124 when PV and wind power generation are provided as the energy sources ES. As shown in FIG. 4, the energy source information 124 includes a predicted amount of power from PV and a predicted amount of power from wind power generation. The predicted amount of power is a predicted value of the amount of power supplied from the energy source.

[0026] The storage unit 120 can be configured from any commonly used storage medium, such as a flash memory, a memory card, a RAM (Random Access Memory), an HDD (Hard Disk Drive), or an optical disk.

[0027] Some or all of the data stored in the memory unit 120 (power storage device information 121, market information 122, order book information 123, energy source information 124) may be stored in physically different storage media, or may be stored in different storage areas of the same physically identical storage medium.

[0028] The acquisition unit 101 acquires various types of information used in the information processing device 100. For example, the acquisition unit 101 acquires input data such as power storage device information 121, market information 122, order book information 123, and energy source information 124. The acquisition unit 101 stores the acquired input data in the storage unit 120.

[0029] The acquisition unit 101 may acquire information by any method, for example, a method of receiving information from an external device via a network, or a method of reading information from a storage medium.

[0030] The trading volume calculation unit 110 calculates multiple trading volumes TA (first trading volumes) which are surplus volumes to be allocated to each of multiple commodities in the pre-hour market (market MB). For example, the trading volume calculation unit 110 uses the surplus volume and order book information 123 including bid prices of trading targets in the pre-hour market to calculate the amount of electricity sold (trading volume TA) to be allocated to each of multiple commodities in the pre-hour market from the surplus volume. Hereinafter, the amount of electricity sold (trading volume TA) to be allocated to each of multiple commodities may be referred to as the allocation volume.

[0031] The trading volume calculation unit 110 includes a maximum volume calculation unit 111 and an allocation calculation unit 112.

[0032] The maximum amount calculation unit 111 uses the order book information 123 to calculate a maximum contractable amount, which is the maximum amount of power that can be contracted for multiple products. Furthermore, the maximum amount calculation unit 111 uses the power storage device information 121, information on the energy source ES, and the maximum contractable amount to calculate a maximum allocable amount, which is the maximum amount of power sold, for each of the multiple products. The allocation calculation unit 112 calculates an allocation amount for each of the multiple products under a constraint that the maximum allocable amount must not be exceeded. Details of the processing by the maximum amount calculation unit 111 and the allocation calculation unit 112 will be described later.

[0033] The plan calculation unit 130 calculates a bidding plan for the surplus amount for the time-ahead market. The plan calculation unit 130 calculates multiple bid prices PA corresponding to each of the multiple allocation amounts calculated for the multiple products. For example, the plan calculation unit 130 calculates the bid price PA for each of the multiple products using the latest contract price in the time-ahead market included in the market information 122. The plan calculation unit 130 may be configured to calculate the bid price PA for each of the multiple products using an estimation model that has been trained to input the allocation amount and output the bid price. The plan calculation unit 130 calculates a bidding plan that includes the allocation amount calculated by the allocation calculation unit 112 and the bid price PA.

[0034] The output control unit 102 controls the output of various information used in the information processing device 100. For example, the output control unit 102 outputs the bidding plan calculated by the plan calculation unit 130.

[0035] 5 is a diagram showing an example of output data that is output. As shown in FIG. 5, the output data includes a time stamp, a power storage device ID, a power delivery date, a product ID, an amount of power to be sold, an amount of power to be sold, and a bid price.

[0036] The planned amount of electricity to be sold is the amount of electricity planned to be sold for each product, and corresponds to the allocation amount described above. The amount of electricity to be sold and bought represents the optimal value of the amount of electricity to be sold and bought within the time until the next calculation process. For example, the amount of electricity to be sold and bought is a negative value in the case of a sale, and a positive value in the case of a purchase. The bid price represents the recommended bid price, and corresponds to the bid price PA calculated by the plan calculation unit 130.

[0037] The output data shown in FIG. 5 is output for each of the multiple products. The bidding plan is, for example, data including the output data for the multiple products. The output data (bidding plan) may be expressed in any data structure, for example, in a CSV file format. Each line of the CSV file represents the output data for one product.

[0038] The output control unit 102 may output information in any manner, including, for example, displaying the information on a display device, or transmitting the information to an external device via a network.

[0039] The network for connecting to an external device may be of any type, and may be configured, for example, as the Internet, etc. The network for connecting to an external device may be a wired network, a wireless network, or a network in which wired and wireless networks are mixed.

[0040] At least a part of each of the above units (acquisition unit 101, output control unit 102, trading volume calculation unit 110, and plan calculation unit 130) may be realized by one or more processing units. Each of the above units is realized, for example, by one or more processors. For example, each of the above units may be realized by having a processor such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit) execute a program, that is, by software. Each of the above units may be realized by a processor such as a dedicated IC (Integrated Circuit), that is, by hardware. Each of the above units may be realized by a combination of software and hardware. When multiple processors are used, each processor may realize one of the units, or may realize two or more of the units.

[0041] Furthermore, the information processing device 100 may be physically configured as one device or may be physically configured as multiple devices. For example, the information processing device 100 may be constructed in a cloud environment. Furthermore, each unit within the information processing device 100 may be distributed across multiple devices.

[0042] Next, a description will be given of a plan creation process performed by the information processing apparatus 100 according to the embodiment. Fig. 6 is a flowchart showing an example of the plan creation process according to the embodiment.

[0043] The acquisition unit 101 acquires input data (power storage device information 121, market information 122, order book information 123, and energy source information 124) and stores the data in, for example, the storage unit 120 (step S101).

[0044] The maximum amount calculation unit 111 of the transaction amount calculation unit 110 calculates the maximum contractable amount and the maximum allocable amount for each commodity (step S102). The allocation calculation unit 112 calculates the allocation amount for each commodity using the input data and the maximum allocable amount (step S103).

[0045] The plan calculation unit 130 calculates a bidding plan for each product (step S104). For example, the plan calculation unit 130 calculates a bid price for each product and calculates a bidding plan that includes the calculated input price and the allocation amount calculated by the allocation calculation unit 112.

[0046] The output control unit 102 generates and outputs a bidding plan that summarizes the bidding plans for each product (step S105), and ends the plan creation process.

[0047] Next, a detailed description will be given of the processing of the maximum amount calculation unit 111 and the allocation calculation unit 112. First, the maximum amount calculation unit 111 will be described.

[0048] The maximum amount calculation unit 111 calculates the maximum contractable amount for each of a plurality of commodities. First, the maximum amount calculation unit 111 acquires the order book information 123 for each commodity. As described above, the order book information 123 includes the following information. -Latest execution results: execution volume and execution price Transaction summary information: trade volume, lowest ask price, highest bid price, and average trade price - Current bidding information: current selling bid volume, selling bid price, buying bid volume, buying bid price

[0049] The maximum quantity calculation unit 111 uses such order book information 123 to perform analysis to calculate the maximum contractable quantity. When placing a sell bid, information on buy bids is important. The maximum quantity calculation unit 111 focuses on the buy bid quantity and buy bid price, and excludes (filters) buy bids with low buy bid prices. For example, the maximum quantity calculation unit 111 calculates the maximum contractable quantity according to the following procedure. Filtering buy bids: Buy bids offering sufficient prices are selected in order from the highest buy price. At this time, bids with excessively low prices are not considered. For example, the maximum quantity calculation unit 111 selects buy bids whose buy bid prices are equal to or greater than a threshold. The threshold may be a value specified in advance, or may be a value calculated using the order book information 123. · Calculation of maximum contractable volume: Calculate the sum of the selected buy bid volumes, and set the calculated value as the maximum contractable volume, which is the maximum volume of sell bids.

[0050] An example of calculating the maximum contractable volume will be described. For example, it is assumed that the order book information 123 includes the following data. Buying bid B1: Buying bid price 10 yen / kWh, buying bid quantity 2MWh Buying bid B2: Buying bid price 9 yen / kWh, buying bid quantity 3MWh Buying bid B3: Buying bid price 8 yen / kWh, buying bid amount 1MWh

[0051] In this case, if the seller wishes to sell at a minimum price of 9 yen / kWh or more, a buying bid is selected with a threshold of 9 yen / kWh. That is, the maximum quantity calculation unit 111 selects buying bids B1 and B2 whose buying bid prices are equal to or greater than the threshold of 9 yen / kWh. In addition, the maximum quantity calculation unit 111 calculates the total buying bid quantity of buying bids B1 and B2, 5 MWh (2 MWh + 3 MWh), as the maximum contractable quantity.

[0052] The maximum amount calculation unit 111 calculates and outputs the maximum contractable amount for each product. The maximum contractable amount for each product is referenced by the allocation calculation unit 112 when calculating the allocation amount of the surplus amount, and by the plan calculation unit 130 when calculating the bid price.

[0053] The maximum amount calculation unit 111 further calculates the maximum allocable amount for each of the multiple products.

[0054] First, the maximum quantity calculation unit 111 checks the specifications of the energy storage device that should be taken into consideration when bidding for products in the time-ahead market. An important specification of the energy storage device is the output limit imposed by the PCS. Trading must be conducted within this output limit. For example, the maximum quantity calculation unit 111 calculates the maximum allocable quantity for each product in the time-ahead market, taking into account the rated output and charge / discharge efficiency of the energy storage device. Furthermore, if the power generation company owns an energy source ES other than the energy storage device, it is required to prioritize the supply of power from the energy source ES. This is because renewable energy sources are prone to fluctuation and usually have low operating costs. Therefore, when setting the trading quantity of the energy storage device, the maximum quantity calculation unit 111 takes into account the supply quantity of the energy source ES and adjusts it so that trading of power supplied from the energy source ES is prioritized.

[0055] For example, the maximum amount calculation unit 111 calculates the maximum allocable amount in accordance with the following procedure. Confirmation of rated output and charge / discharge efficiency of the power storage device: For each product in the pre-sale market, the maximum amount of power that can be supplied from the power storage device is calculated based on the rated output and charge / discharge efficiency of the power storage device. For example, the maximum amount calculation unit 111 calculates the maximum amount of power by multiplying the rated output by the charge / discharge efficiency. The maximum amount calculation unit 111 may calculate the maximum amount of power using only the rated output. · Checking the supply amount of energy sources ES: Obtain the predicted amount of power supplied from energy sources ES such as PV and wind power. Calculation of maximum allocable amount: For each product, the supply from the energy source ES is limited in order to provide the supply from the energy source ES to the market on a priority basis. Specifically, the maximum allocable amount is calculated by subtracting the supply amount of the energy source ES from the amount of electricity that can be supplied from the energy storage device. Adjustment based on maximum contractable volume: If the maximum allocable volume exceeds the maximum allocable volume, the maximum allocable volume will be calculated as the maximum allocable volume.

[0056] An example of calculating the maximum allocable amount will be described below. For example, it is assumed that the input data (electricity storage device information 121, information on the energy source ES) includes the following data. Rated output of the storage device: 10MW · PV estimated power generation: 1MWh Estimated wind power: 2MWh

[0057] In this case, the maximum amount calculation unit 111 calculates the maximum allocable amount for each product (30-minute frame) as the maximum amount of power 5 MWh (10 MW×0.5 h) of the power storage device minus the supply amount of energy source ES (3 MWh) = 2 MWh.

[0058] Next, a detailed description will be given of the processing of the allocation calculation unit 112. The allocation calculation unit 112 formulates, for example, a problem of allocating the amount of electricity stored in an electricity storage device to a plurality of products in the ahead market as an optimization problem and solves it.

[0059] The variables are defined as follows: Storage capacity of the storage device: E (MWh) Number of products available for trading on the market: n Latest contract price of each product: p1,...,p n (yen / kWh) ·Maximum allocation amount of each product: l1,···,l n (MWh) Amount of electricity allocated to each product (allocation amount): e1,...,e n (MWh) Imbalance: b (MWh) Imbalance unit cost: q (yen / kWh)

[0060] As described above, the imbalance corresponds to a surplus amount that occurs when the amount planned in the next charging schedule cannot be charged due to remaining energy in the power storage device.

[0061] The objective of the optimization problem is to find the allocation amount e1,...,e nThe objective is to determine the total revenue and maximize the total profit. This profit includes the profit obtained from the sale of the amount of electricity allocated to each product and the amount of imbalance settlement. The optimization problem is formulated as follows:

number

number

number

number

[0062] Equation (1) represents the objective function that maximizes the total revenue, including the revenue obtained from the sale of the amount of energy allocated to each product in the pre-hour market and the imbalance settlement amount. Equation (2) is a constraint that indicates that the sum of the amount allocated to each product in the pre-hour market and the imbalance is smaller than the amount of energy stored in the energy storage device. Equation (3) is a constraint that indicates that the amount of energy allocated to each product does not exceed the maximum allocable amount, which corresponds to the upper limit of trading. Equation (4) is a non-negative constraint on the imbalance.

[0063] Such an optimization problem can be solved, for example, using a linear programming (LP) method. This is because both the objective function and the constraints are linear and fit into the LP framework. The allocation calculation unit 112 calculates the allocation amount for each of the multiple products by solving the optimization problem formulated as above using, for example, a linear programming solver.

[0064] Next, a detailed description will be given of the processing of the plan calculation unit 130. The plan calculation unit 130 calculates a bidding plan, for example, by the following procedure. (S1) Determining the bid amount (S2) Acquisition of data to be used (S3) Setting a limit price (S4) Calculation of bid price

[0065] Each of the above steps will be explained. In (S1), the plan calculation unit 130 determines the allocation amount for each product in the ahead market calculated by the allocation calculation unit 112 as the bid amount as is. As described above, the allocation amount is calculated taking into consideration the rated output of the power storage device and the supply amount from the energy source ES (renewable energy source).

[0066] In (S2), the plan calculation unit 130 acquires the minimum selling price, the maximum purchasing price, and the latest contract price included in the market information 122, for example.

[0067] In (S3), the plan calculation unit 130 sets the following limit price. ·Minimum selling price: No sale will be made below the minimum selling price. · Maximum Purchase Price: Do not purchase at a price greater than the maximum purchase price.

[0068] In (S4), the plan calculation unit 130 calculates the bid price for each product using the limit price. By taking the limit price into consideration, it is possible to calculate a bidding plan that avoids disadvantageous transactions. For example, if the latest contract price is within a range defined by the limit price, the plan calculation unit 130 calculates the latest contract price as the bid price. The range defined by the limit price is, for example, a range equal to or greater than the minimum selling price and equal to or less than the maximum purchasing price. If the latest contract price is outside the range (the latest contract price is less than the minimum selling price or greater than the maximum purchasing price), there is a high possibility that the transaction will be disadvantageous, so the plan calculation unit 130 sets the bid quantity for the corresponding product to 0. Note that since the bid quantity is 0, there is no need to calculate a bid price.

[0069] An example of calculating a bidding plan will be described below. For example, assume that the following information is obtained for a product in a certain time-ahead market. Allocation amount: 5MWh Latest contract price: 9 yen / kWh Minimum selling price: 8 yen / kWh Maximum purchase price: 12 yen / kWh

[0070] In this case, since the latest contract price is within the limit price range, the plan calculation unit 130 calculates the bid price at 9 yen / kWh and sets the amount of power to be sold at the allocation amount of 5 MWh. The plan calculation unit 130 calculates a bidding plan that includes the amount of power to be sold and the bid price.

[0071] In the above example, assume that the latest contract price is 6 yen / kWh. In this case, since the latest contract price is less than the minimum selling price of 8 yen / kWh, the plan calculation unit 130 sets the bid quantity to 0. For example, the plan calculation unit 130 calculates a bidding plan indicating that the bid quantity is 0 for the product.

[0072] Through the above procedure, a bidding plan that enables efficient and profitable transactions can be calculated. A final bidding plan including bidding plans for multiple products is output and reflected in transactions in the market.

[0073] An application example of the embodiment will be described with reference to Fig. 7. Fig. 7 is a diagram for explaining an application example of the embodiment.

[0074] The horizontal axis at the top of Figure 7 represents the change over time in the amount of electricity procured from the balancing market and stored in the energy storage device. The horizontal axis at the bottom of Figure 7 represents the change over time in the amount of electricity bid into the time-ahead market. The scale on each horizontal axis corresponds to a product (trading period, time). In the example of Figure 7, the current time is 9:15.

[0075] Charging periods 701 and 702 represent periods during which charging is performed on the power storage device. Discharge amount 711 represents the amount of power discharged from the amount of power stored in the power storage device. Surplus amount 712 represents the surplus amount of the power storage device in the past (before 9:15). Contract amount 713 represents the amount of power contracted in the aforesaid market from the aforesaid market. In the example of FIG. 7, contract amount 713 is traded in the aforesaid market between 10:00 and 10:30.

[0076] The surplus amount 714 corresponds to the amount of power obtained by subtracting the contracted amount 713 from the surplus amount 712. The surplus amount 715 represents the current (9:15) surplus amount of the power storage device. The surplus amount 714 and the surplus amount 715 will be the subject of bidding within the range of frames that will be the subject of bidding next (bidding frame range).

[0077] The overall flow of the bidding plan calculation process according to this embodiment will be described with reference to Fig. 8. Fig. 8 is a diagram showing an example of the bidding plan calculation process according to this embodiment.

[0078] Input data including power storage device information 121, market information 122, order book information 123, and energy source information 124 is input.

[0079] The trading volume calculation unit 110 uses the input data to calculate the allocation amount of the stored power of the power storage device for each commodity in the before-hours market. In Fig. 8, allocation amounts D1 to D4 for four commodities are illustrated as an example, but the number of commodities (allocation amounts) is not limited to four.

[0080] When the allocation amount (sale amount) for each product is calculated, the plan calculation unit 130 calculates a bidding plan including a recommended bid amount (amount of power to be sold) and bid price for each product.

[0081] Through these steps, a final bidding plan in which the bidding plans for each product are integrated is output as output data.

[0082] In this way, the information processing device of the embodiment can more accurately determine an appropriate bid amount for a trading object in a market such as electricity.

[0083] Next, the hardware configuration of the information processing apparatus according to the embodiment will be described with reference to Fig. 9. Fig. 9 is an explanatory diagram illustrating an example of the hardware configuration of the information processing apparatus according to the embodiment.

[0084] The information processing device of the embodiment includes a control device such as a CPU (Central Processing Unit) 51, a storage device such as a ROM (Read Only Memory) 52 and a RAM (Random Access Memory) 53, a communication I / F 54 that connects to a network and communicates, and a bus 61 that connects each part.

[0085] The programs executed by the information processing apparatus according to the embodiment are provided in advance in the ROM 52 or the like.

[0086] The program executed by the information processing device of the embodiment may be configured to be provided as a computer program product by being recorded in an installable or executable format on a computer-readable recording medium such as a CD-ROM (Compact Disk Read Only Memory), a flexible disk (FD), a CD-R (Compact Disk Recordable), or a DVD (Digital Versatile Disk).

[0087] Furthermore, the program executed by the information processing apparatus of the embodiment may be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network. Also, the program executed by the information processing apparatus of the embodiment may be provided or distributed via a network such as the Internet.

[0088] The programs executed by the information processing device of the embodiment can cause a computer to function as each of the above-mentioned parts of the information processing device. In this computer, the CPU 51 can read the programs from a computer-readable storage medium onto a main storage device and execute them.

[0089] A configuration example of the embodiment will be described below. (Configuration example 1) calculating a plurality of first trading volumes, which are trading volumes to be allocated to each of a plurality of trading periods of the second market, from the surplus volume, using a surplus volume, which is a surplus of the trading volume of the trading object in one or more first markets, and order book information of a second market different from the first market; calculating a bidding plan including a plurality of the first transaction volumes and a plurality of first bid prices corresponding to the plurality of first transaction volumes; Processing section An information processing device comprising: (Configuration example 2) The trading object is electricity, The trading volume is the amount of electricity sold, The surplus amount is a storage amount of the surplus amount of the power sold stored in the power storage device. The information processing device according to configuration example 1. (Configuration example 3) The processing unit Using the order book information, a maximum allocable amount is calculated, which is a maximum value of the amount of electricity sold over a plurality of the trading periods; calculating the first trading volume under a constraint that does not exceed the maximum allocable volume; The information processing device according to configuration example 2. (Configuration Example 4) The processing unit calculating the maximum allocable amount using energy source information including an amount of power supplied from an energy source different from the power storage device and the board information; The information processing device according to configuration example 3. (Configuration Example 5) The processing unit calculating the bidding plan including the contract price as the first bid price using market information including the contract price in the second market; The information processing device according to any one of configuration examples 1 to 4. (Configuration Example 6) The processing unit If the contract price is within a range determined by a limit price, calculate the bidding plan including the contract price as the first bid price. The information processing device according to configuration example 5. (Configuration Example 7) The processing unit calculating a plurality of first bid prices corresponding to the plurality of first trading volumes calculated for the plurality of trading periods using an estimation model trained to input the trading volumes for each of the plurality of trading periods and output bid prices for each of the plurality of trading periods; The information processing device according to any one of configuration examples 1 to 6. (Configuration Example 8) The processing unit outputting the calculated bidding plan; The information processing device according to any one of configuration examples 1 to 7. (Configuration Example 9) An information processing method executed by an information processing device, a step of calculating, using a surplus volume, which is a surplus of the trading volume of the trading object in one or more first markets, and order book information of a second market different from the first market, a plurality of first trading volumes, which are trading volumes to be allocated to each of a plurality of trading periods of the second market, from the surplus volume; calculating a bidding plan including a plurality of the first transaction volumes and a plurality of first bid prices corresponding to the plurality of first transaction volumes; An information processing method including: (Configuration Example 10) On the computer, a step of calculating, using a surplus volume, which is a surplus of the trading volume of the trading object in one or more first markets, and order book information of a second market different from the first market, a plurality of first trading volumes, which are trading volumes to be allocated to each of a plurality of trading periods of the second market, from the surplus volume; calculating a bidding plan including a plurality of the first transaction volumes and a plurality of first bid prices corresponding to the plurality of first transaction volumes; A program to execute.

[0090] Although several embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be embodied in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, and are also included in the scope of the invention and its equivalents as defined in the claims. [Explanation of symbols]

[0091] 100 Information processing device 101 Acquisition Department 102 Output control section 110 Trading volume calculation unit 111 Maximum amount calculation section 112 Allocation Calculation Unit 120 Storage section 121 Energy Storage Device Information 122 Market Information 123 Board information 124 Energy Source Information 130 Planning Calculation Department

Claims

1. calculating a plurality of first trading volumes, which are trading volumes to be allocated to each of a plurality of trading periods of the second market, from the surplus volume, using a surplus volume, which is a surplus of the trading volume of the trading object in one or more first markets, and order book information of a second market different from the first market; calculating a bidding plan including a plurality of the first transaction volumes and a plurality of first bid prices corresponding to the plurality of first transaction volumes; Processing section An information processing device comprising:

2. The trading object is electricity, The trading volume is the amount of electricity sold, The surplus amount is a storage amount of the surplus amount of the power sold stored in the power storage device. The information processing device according to claim 1 .

3. The processing unit Using the order book information, a maximum allocable amount is calculated, which is a maximum value of the amount of electricity sold over a plurality of the trading periods; calculating the first trading volume under a constraint that the first trading volume does not exceed the maximum allocable volume; The information processing device according to claim 2 .

4. The processing unit calculating the maximum allocable amount using energy source information including an amount of power supplied from an energy source different from the power storage device and the board information; The information processing device according to claim 3 .

5. The processing unit calculating the bidding plan including the contract price as the first bid price using market information including the contract price in the second market; The information processing device according to claim 1 .

6. The processing unit If the contract price is within a range determined by a limit price, calculate the bidding plan including the contract price as the first bid price. The information processing device according to claim 5 .

7. The processing unit calculating a plurality of first bid prices corresponding to the plurality of first trading volumes calculated for the plurality of trading periods using an estimation model that is trained to input the trading volumes for each of the plurality of trading periods and output bid prices for each of the plurality of trading periods; The information processing device according to claim 1 .

8. The processing unit outputting the calculated bidding plan; The information processing device according to claim 1 .

9. An information processing method executed by an information processing device, a step of calculating a plurality of first trading volumes, which are trading volumes to be allocated to each of a plurality of trading periods of the second market, from the surplus volume, using a surplus volume, which is a surplus of the trading volume of the trading object in one or more first markets, and order book information of a second market different from the first market; calculating a bidding plan including a plurality of the first transaction volumes and a plurality of first bid prices corresponding to the plurality of first transaction volumes; An information processing method including:

10. On the computer, a step of calculating a plurality of first trading volumes, which are trading volumes to be allocated to each of a plurality of trading periods of the second market, from the surplus volume, using a surplus volume, which is a surplus of the trading volume of the trading object in one or more first markets, and order book information of a second market different from the first market; calculating a bidding plan including a plurality of the first transaction volumes and a plurality of first bid prices corresponding to the plurality of first transaction volumes; A program to execute.

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