Information processing device, information processing method, and program

Abstract

This invention provides an information processing device, an information processing method, and a program that accurately predict transaction information in the capacity market. [Solution] The information processing device 100 includes a reading unit 20 that reads from a storage unit 80 a bid prediction model for the capacity market, or a corrected bid prediction model obtained by correcting the bid prediction model using future prediction information, which is generated using wholesale power performance information including power output contracted in the wholesale power market, supply and demand adjustment performance information including power output contracted in the supply and demand adjustment market, and power information including power output from multiple power sources; and a prediction unit 10 that predicts future contract information for the capacity market using future purchase predictions for the capacity market and the bid prediction model read by the reading unit 20.

Description

[Technical Field]

[0001] The present invention relates to an information processing apparatus, an information processing method, and a program for predicting a contract price in a capacity market. [Background Art]

[0002] Attempts have been made conventionally to predict electricity prices in various markets. For example, Patent Document 1 discloses a power sales planning apparatus comprising: an adjustment power profit calculation unit that calculates an expected value of profit obtained from a supply-demand adjustment market for a part of electric power to be generated in the future by a renewable energy power source; a power sales profit calculation unit that calculates an expected value of profit obtained from a wholesale electricity market for the remaining part of the electric power to be generated in the future; and an output processing unit that determines a bid volume for the supply-demand adjustment market and a bid volume for the wholesale electricity market based on the expected value of profit obtained from the supply-demand adjustment market and the expected value of profit obtained from the wholesale electricity market. Paragraph

[0015] of Patent Document 1 discloses that transaction prices store current and past values of each parameter in the supply-demand adjustment market and the wholesale electricity market in time series, and also store future values of each parameter in time series. [Prior Art Literature] [Patent Literature]

[0003] [Patent Document 1] Japanese Unexamined Patent Publication No. 2021-174344 [Summary of the Invention] [Problem to be Solved by the Invention]

[0004] In Patent Document 1, although the supply-demand adjustment market and the wholesale electricity market are considered, the capacity market is not mentioned.

[0005] The present invention provides an information processing apparatus, an information processing method, and a program that accurately predict contract information in a capacity market. [Means for Solving the Problem]

[0006] [Concept 1] The information processing apparatus according to the present invention is A reading unit reads from a storage unit a bidding prediction model for the capacity market, which is generated using wholesale power performance information including power output contracted in the wholesale power market, supply and demand adjustment performance information including power output contracted in the supply and demand adjustment market, and power information including power output from multiple power sources. A prediction unit that predicts future trading information in the capacity market using future buying predictions in the capacity market and the bidding prediction model read out by the reading unit, It may be provided.

[0007] [Concept 2] In an information processing device based on Concept 1, The aforementioned wholesale electricity performance information includes estimated wholesale electricity revenue in the wholesale electricity market. The aforementioned supply and demand adjustment performance information includes estimated supply and demand adjustment revenue in the supply and demand adjustment market. The aforementioned bidding forecast model may be generated using the maintenance costs of the multiple power sources, the wholesale electricity revenue, and the supply and demand adjustment revenue.

[0008] [Concept 3] In an information processing device according to Concept 1 or 2, The aforementioned bidding prediction model may include information regarding the volume and price of bids in the capacity market.

[0009] [Concept 4] In an information processing device based on Concept 3, Future buying forecasts in the capacity market include the volume of bids and the price of bids. The prediction unit may also predict that the transaction will be executed at a selling bid quantity and selling bid price that are below the buying bid quantity and buying bid price.

[0010] [Concept 5] In an information processing device based on any one of concepts 1 to 4, The aforementioned power supply information includes area information relating to the area, The forecasting unit may also take the area information into consideration to predict future transaction information in the capacity market.

[0011] [Concept 6] In an information processing device based on any one of concepts 1 to 5, The forecasting unit may predict future trading information in a capacity market by reducing the amount of contracts from power sources in a predetermined area and adding the amount of contracts from power sources outside the predetermined area within the entire range of a capacity market.

[0012] [Concept 7] In an information processing device based on Concept 6, The forecasting unit may predict market fragmentation and reduce the contracted volume from power sources in a predetermined area within the entire range of a certain capacity market, while increasing the contracted volume from power sources outside the predetermined area.

[0013] [Concept 8] The information processing method according to the present invention is The process involves reading from the storage unit a bidding prediction model for the capacity market, which is generated using wholesale power performance information including power output contracted in the wholesale power market, supply and demand adjustment performance information including power output contracted in the supply and demand adjustment market, and power information including power output from multiple power sources. The process involves a prediction unit predicting future purchases in the capacity market and using the auction prediction model read out by the reading unit to predict future transaction information in the capacity market. It may be provided.

[0014] [Concept 9] The program according to the present invention is A program for installation on an information processing device, On an information processing device where a program is installed, a function of reading, from a storage unit, a bid prediction model for a capacity market generated using wholesale power performance information including contracted power output in the wholesale power market, supply-demand adjustment performance information including contracted power output in the supply-demand adjustment market, and power source information including power output of a plurality of power sources; a function of predicting future contract information in the capacity market using future purchase forecasts in the capacity market and the bid prediction model read by the reading unit; may be implemented. Effects of the Invention

[0015] According to the present invention, it is possible to provide an information processing apparatus, an information processing method, and a program that accurately predict contract information in a capacity market. Brief Description of Drawings

[0016] [Figure 1] 1 is a conceptual diagram of an information processing system according to an embodiment of the present invention. [Figure 2] 2 is a block diagram of an information processing apparatus according to an embodiment of the present invention. [Figure 3] 3 is a graph simulating the relationship between bid volume and bid price in an embodiment of the present invention. [Figure 4] 4 is a graph showing bid volumes and bid prices predicted to be contracted when market splitting processing is not performed in an embodiment of the present invention. [Figure 5] 5 is a graph showing bid volumes and bid prices after reduction processing and additional contracting processing are performed in an embodiment of the present invention. [Figure 6] 6 is a diagram for explaining an aspect of generating a bid simulation graph matching the actual bid curve of bid prices and bid volumes for a capacity market, using information such as guidelines and institutional design in addition to wholesale power performance information, supply-demand adjustment performance information, power source information organized from public information, in an embodiment of the present invention. [Figure 7]This diagram illustrates how to generate bid price and bid volume bid forecast graphs (including buy bid forecast graphs) for the capacity market, using future wholesale power forecast information and supply-demand adjustment forecast information derived from future scenarios, future power source data compiled from publicly available information, and information such as guidelines and institutional design. [Modes for carrying out the invention]

[0017] Embodiment The following describes embodiments of the information processing apparatus and information processing method according to the present invention. In this embodiment, a program that can be installed on a computer such as a personal computer to enable the computer to execute the information processing method of this embodiment, and a recording medium on which the program is stored are also provided. In this embodiment, "or" is a concept that includes "and", and "A or B" is a concept that includes A only, B only, or both A and B.

[0018] The information processing device of this embodiment may be installed in any location, may be a server, or may be used in a cloud environment. The information processing device of this embodiment may consist of one device or multiple devices. Furthermore, if the information processing device consists of multiple devices, each device does not need to be located in the same room or other space, but may be located in different rooms, different buildings, different regions, etc. Also, if the information processing device consists of multiple devices, one organization may own and / or manage some of them, and another organization may own and / or manage the rest.

[0019] The program according to this embodiment is used to generate the information processing device described below, and the recording medium according to this embodiment is used to record the program. Furthermore, the information processing method according to this embodiment is performed by the information processing device on which the above program is installed. The information processing device may also perform the information processing method according to this embodiment by executing an application installed on the information processing device.

[0020] The electricity market in this embodiment includes a wholesale electricity market for buying and selling electricity, a supply and demand adjustment market for trading adjustment capacity for stable operation of the power grid, and a capacity market aimed at securing future supply capacity.

[0021] The wholesale electricity market is a market where electricity is bought and sold between electricity suppliers, such as power generators, and electricity consumers, such as retail electricity companies, based on predetermined transaction units and transaction periods. It includes spot transactions, advance transactions, forward transactions, and other similar transaction forms. The wholesale electricity market is a market where "electricity quantities" for the near future, such as today or tomorrow, are bought and sold.

[0022] The supply and demand adjustment market is a market where trading takes place regarding the securing of adjustment capacity provided by power generation facilities, demand facilities, or energy storage facilities, etc., in order to maintain the supply and demand balance in the power grid, and the adjustment of output based on such capacity. The supply and demand adjustment market is a market that secures "adjustment capacity (increasing or decreasing output)" in real time.

[0023] A capacity market is a market in which the supply capacity of power generation facilities, demand reduction capacity, or energy storage facilities is traded, with the aim of securing the electricity supply capacity required for a certain period in the future, and payment is made for the provision of such capacity. The capacity market is a market for securing supply capacity several years in advance (for example, four years from now).

[0024] As shown in Figure 2, the information processing device 100 of this embodiment may include: a generation unit 50 that generates a bidding prediction model in the capacity market using wholesale power performance information including power output contracted in the wholesale power market, supply and demand adjustment performance information including power output contracted in the supply and demand adjustment market, and power information including power output from multiple power sources; a prediction unit 10 that predicts future contract information in the capacity market using future purchase predictions and the bidding prediction model in the capacity market; a storage unit 80 that stores various information; an output unit 85 that outputs various information; and a communication unit 90 that communicates with an external device such as a user terminal 200 shown in Figure 1. In this embodiment, the information processing device 100 is described using an embodiment in which the generation unit 50 is included, but it is not limited to this, and the generation unit may utilize an external device such as a generation AI such as ChatGPT or Gemini provided by a third party. In this embodiment, long-term predictions such as 10 years or 20 years in the future may be performed. By performing long-term predictions in this way, they can be used as material for investment decisions, etc.

[0025] When generating a bidding forecast model for the capacity market, it is also possible to identify power sources that are actually operating by comparing the power output contracted in the wholesale electricity market and the supply and demand adjustment market with the power output of multiple power sources obtained from publicly available information, and then generate a bidding forecast model for the capacity market based on the identified power sources.

[0026] As shown in Figure 1, the user terminal 200 has an operation unit 210 for inputting operations and a display unit 220 for displaying information. The information output by the output unit 85 may be displayed on the display unit 220 of the user terminal 200. The user terminal 200 may be a personal computer, tablet, smartphone, etc., and the touch panel of a smartphone or tablet will serve the functions of both the operation unit 210 and the display unit 220.

[0027] The information output by the output unit 85 is displayed on the display unit 220 of the user terminal 200 via the communication unit 90. Information transmitted from the user terminal 200 is acquired by the acquisition unit 40 via the communication unit 90.

[0028] Wholesale power performance information, supply and demand adjustment performance information, and power information for multiple power sources are stored in the storage unit 80. The reading unit 20 may read from the storage unit 80 a bid prediction model for the capacity market, which is generated using wholesale power performance information including power output agreed in the wholesale power market, supply and demand adjustment performance information including power output agreed in the supply and demand adjustment market, and power information including power output for multiple power sources.

[0029] The bidding prediction model may include information on the quantity and price of bids in the capacity market. The bidding prediction model includes a simulated bidding graph using the quantity and price of bids, and the output unit 85 may output the simulated bidding graph (see Figure 3). The simulated bidding graph may be generated by identifying power sources that are actually operating by comparing the power output contracted in the wholesale electricity market and the supply and demand adjustment market with the power output of multiple power sources obtained from publicly available information, and based on the identified power sources. In this case, the simulated bidding graph and the actual results may be compared, and the prediction of operating power sources may be repeatedly performed so that the agreement rate between the two is above a predetermined value.

[0030] The simulated bidding graph can calculate the bid price and bid quantity for each power source. In the embodiment shown in Figure 3, a simulated bidding graph for selling is shown with the selling bid quantity on the horizontal axis and the selling bid price on the vertical axis. The solid line represents the actual selling bid quantity and selling bid price in the capacity market. The dotted line in Figure 3 represents the simulated bidding graph based on the calculation results for selling bid quantity and selling bid price using the bidding prediction model. The generation unit 50 may repeatedly make adjustments until the deviation rate between the actual and predicted values ​​in the simulated bidding graph falls within a predetermined range. One method of adjustment is to rearrange the power sources that are predicted to be in operation. For example, if the deviation rate between the actual and predicted values ​​in the simulated bidding graph is 0% when it is predicted that power sources A1, B1, ..., and Z1 are being used, and this exceeds the threshold, then power source Z1 is rearranged to power source Z2. Furthermore, if the Z1 power supply is replaced with the Z2 power supply, and the discrepancy between the actual and predicted results in the simulated sell bid graph becomes △%, and is below the threshold (the agreement rate is above a predetermined value), then the subsequent processing may be carried out on the assumption that the prediction that the A1 power supply, B1 power supply, ..., and Z2 power supply are operating is correct.

[0031] The bidding prediction model may include information on the quantity and price of future bids in the capacity market, and may also include a bidding prediction graph. The bidding prediction model may output a bidding prediction graph for the future capacity market using the quantity and price of future bids (see Figure 4). The bidding prediction graph may be generated by applying future scenarios, such as inflation rates, to a simulated bidding graph.

[0032] The bid prediction model may include information on the quantity and price of future buy bids in the capacity market. The prediction unit 10 may output a sell bid prediction graph using the quantity and price of sell bids, and a buy bid prediction graph using the quantity and price of buy bids (see Figure 4).

[0033] In the embodiment shown in Figure 4, a graph predicting sell bids and a graph predicting buy bids are shown, with the bid quantity on the horizontal axis and the bid price on the vertical axis. In this embodiment, the prediction unit 10 predicts that trades will be executed at sell bid quantities and sell bid prices that are lower than buy bid quantities and buy bid prices. In the embodiment shown in Figure 4, the filled-in bars in the bar graph indicate that sell bids will be executed, while the unfilled bars indicate that sell bids will not be executed.

[0034] The generation unit 50 generates a bidding prediction model by simulating past sales bidding curve data showing the relationship between past bid volume and bid price, using past wholesale electricity performance data, supply and demand adjustment performance data, and power source information obtainable from publicly available information (see Figure 6). The storage unit 80 may then store this bidding prediction model. Publicly available information can include the HJKS power generation information disclosure system and press releases from power generation companies. Power source information obtainable from HJKS, etc., includes power source attribute information such as power source type, fuel type, and grid connection area for each power generation facility, as well as authorized output, maximum output, minimum output, output change characteristics, operating hours, and information on shutdowns or operating constraints. Furthermore, this power source information may also include bidding information in the capacity market, area-specific power source configuration information, and operational performance information such as power generation performance output.

[0035] For example, the generation unit 50 may generate a simulated sales bid graph by modeling the bid price and bid volume in the capacity market across Japan, which is an example of the entire scope of a particular capacity market, using past wholesale electricity performance information and supply and demand adjustment performance information, as well as power source information compiled from publicly available information, and also using information such as guidelines and institutional design (see Figure 6). For institutional design, the demand curve creation guidelines provided by the Organization for Cross-regional Coordination of Transmission Operators may be used. In addition, publicly available information may be used for past wholesale electricity performance information and supply and demand adjustment performance information. Regarding power sources, under the institutional design based on the Electricity Business Act, wholesale electricity markets, capacity markets, supply and demand adjustment markets, etc., have been established, and various guidelines and operational rules have been set up in each market to evaluate the output characteristics, supply capacity, adjustment capacity, etc. of power sources. Therefore, this information may be used to generate a simulated bid graph in the capacity market.

[0036] As shown in Figure 2, the information processing device 100 of this embodiment may have a search unit 60 that automatically searches for information necessary for prediction, such as publicly available power supply information.

[0037] The acquisition unit 40 may acquire information about operating power sources, including operating power sources, non-operating power sources, or the equipment utilization rate of operating power sources, by applying wholesale power performance information and supply and demand adjustment performance information to the power source operation model.

[0038] The power source operation model may be a pre-prepared model. The power source operation model may be constructed based on generator information registered in the power generation information disclosure system, publicly available materials from power generation companies, and power generation performance data for each power source. When obtaining information on operating power sources, the content disclosed in Patent No. 7697093, which was filed and registered by the applicant in this case, may be used.

[0039] The wholesale power performance information may include estimated wholesale power revenue in the wholesale power market. The supply and demand adjustment performance information may include estimated supply and demand adjustment revenue in the supply and demand adjustment market. The generation unit 50 may generate a simulated bidding graph using the maintenance costs for each of the multiple power sources, and the wholesale power revenue and supply and demand adjustment revenue for each of the multiple power sources. The bid price for each power source in the capacity market may be calculated, for example, as revenue expected from power source maintenance costs minus revenue from other markets. In this case, the power source maintenance cost minus (wholesale power revenue + supply and demand adjustment revenue) for a power source expected to be operational may be set as the bid price for that power source, and a simulated bidding graph may be generated. Other markets include the wholesale power market and the supply and demand adjustment market. For multiple power sources, the generation unit 50 may generate a simulated bidding graph so that the bid price for each power source (power source maintenance cost minus revenue from other markets) matches past performance. The same applies to the predicted bidding graph, where the power source maintenance cost minus (wholesale power revenue + supply and demand adjustment revenue) for a power source expected to be operational may be set as the bid price for that power source, and a predicted bidding graph may be generated.

[0040] When the generation unit 50 generates a simulated bidding graph in the capacity market, it may use the same power source data (fuel type, fuel cost characteristics, years of age, etc.) as the power source operation model used in the wholesale electricity market and the supply and demand adjustment market. By adopting this configuration, it is possible to simulate past markets at the bidding unit level for each power source.

[0041] If a simulated bidding graph is generated, you may compare it with past performance data to check whether a high degree of reproducibility has been achieved (see Figure 3 for past performance and calculation results). If a high degree of reproducibility has not been achieved, you may want to make some adjustments.

[0042] The generation unit 50 may generate the slope of the demand curve and coefficients to be multiplied by the expected capacity other than thermal power and pumped water, based on past performance such as demand curves and information on the amount of bids of 0 yen, when generating the bid simulation graph.

[0043] The assumptions for bid prices in the capacity market bid simulation graph generated by the generation unit 50 may be based on past performance in the wholesale electricity market and the supply and demand adjustment market, including projected investment recovery periods for each power source, business feasibility, and various information for each power source. In this case, the generation unit 50 may adjust the bid prices aggregated by area or power source type to match past performance.

[0044] The bid volume assumptions in the simulated bid graph generated by the generation unit 50 may be calculated based on the market's system design to determine the expected capacity. In this case, the generation unit 50 may adjust the total bid volume by area, power source type, etc., to match past performance.

[0045] The generation unit 50 may generate future wholesale power forecast models and supply and demand adjustment forecast models based on wholesale power performance information and supply and demand adjustment performance information, using future scenarios such as thermal and pumped-storage plant information (including new construction, replacement, and decommissioning plans), equipment capacity of each power source (renewable energy, nuclear power, storage batteries, etc.), demand and generation profiles, fuel prices, interconnection line capacity and reinforcement plans, supply and demand profiles, and inflation rates. Specifically, a future wholesale power forecast model may be generated by using current wholesale power performance information as a basis and replacing the current information with information that will change according to future scenarios. Similarly, a future supply and demand adjustment forecast model may be generated by using current supply and demand adjustment performance information as a basis and replacing the current information with information that will change according to future scenarios. The forecasting unit 10 may use the said wholesale power forecast model and supply and demand adjustment forecast model to forecast future wholesale power forecast information and supply and demand adjustment forecast information.

[0046] When calculating future wholesale electricity forecasts, power generation and pumped-storage / energy storage plans, as well as area-specific marginal costs, may be calculated using a wide-area merit order.

[0047] When forecasting future supply and demand adjustments, it is also possible to calculate the ΔkW bidding amount due to additional startup / output reduction of thermal power plants and surplus capacity of pumped-storage hydroelectric power plants and battery storage. Alternatively, lost profits and opportunity costs due to securing ΔkW can be calculated from the difference between the wholesale electricity market price and marginal costs, and bidding prices can be assumed for each plant, and a contract simulation can be conducted.

[0048] The generation unit 50 may generate a sales bid forecast graph including sales bid price and sales bid volume, and a purchase bid forecast graph including purchase bid price and purchase bid volume for the capacity market, using future wholesale power forecast information and supply and demand adjustment forecast information derived from future scenarios, future power source data compiled from publicly available information, as well as information such as guidelines and institutional design (see Figure 7). Future scenarios include thermal and pumped-storage plant information (including new construction, replacement, and decommissioning plans), installed capacity of each power source (renewable energy, nuclear power, storage batteries, etc.), demand and generation profiles, fuel prices, interconnection line capacity and expansion plans, supply and demand profiles, inflation rates, etc. Future wholesale power forecast information and supply and demand adjustment forecast information include revenue in the future wholesale power market and revenue in the supply and demand adjustment market derived from future wholesale power forecast information and supply and demand adjustment forecast information.

[0049] The sell bid prediction graph shown in Figure 4 may be generated based on the sell bid simulation graph shown in Figure 3. For example, future revenue in the wholesale electricity market and revenue in the supply and demand adjustment market are predicted based on future scenarios. In addition, future operational power sources are predicted based on publicly available information compiled from future scenarios. When constructing future scenarios, information such as guidelines and institutional designs (for example, predicted installation volume of solar power generation) may be considered. The generation unit 50 generates the sell bid prediction graph from future revenue in the wholesale electricity market and revenue in the supply and demand adjustment market, and the maintenance costs for operational power sources. For example, the bid amount in the sell bid simulation graph may be shifted in the increasing direction (to the right in Figure 3) while the bid price may be shifted in the increasing direction (up in Figure 3). In this embodiment, revenue in the wholesale electricity market and revenue in the supply and demand adjustment market are used as examples of other market revenues, but the system is not limited to these.

[0050] The generation unit 50 may generate a buy bid forecast graph by assuming buy bid quantities and buy bid prices using future scenarios. The buy bid forecast graph may be based on past buy bid performance graphs in the capacity market and generated using future forecasts of supply and demand profiles, fuel prices, thermal and pumped-storage plant data, installed capacity of each power source, inflation rates, etc. For example, the buy bid forecast graph may be generated by sliding the buy bid performance graph upwards, for example, taking into account forecast values ​​such as the inflation rate, relative to the past buy bid performance graph. Area price calculation may be performed by simulating the execution of the main auction.

[0051] Typically, if future wholesale power forecasts and supply-demand adjustment forecasts are N years in the future, then future capacity market forecasts will be N+α years in the future, where α is, for example, 4 years.

[0052] Power source information may include area information. Area size may be defined by prefecture, by specific regions such as Hokkaido, Tohoku, Kanto, Chubu, Kinki, Chugoku, Shikoku, and Kyushu (including Okinawa), or by the service area of ​​a general power transmission and distribution company, such as Hokkaido, Tohoku, Tokyo, Chubu, Hokuriku, Kansai, Chugoku, Shikoku, and Kyushu. For example, the Tokyo area corresponds to the service area of ​​Tokyo Electric Power Grid Co., Ltd.

[0053] The prediction unit 10 may also take area information into consideration to predict future contract information in the capacity market. More specifically, as shown in Figure 5, the prediction unit 10 may perform a reduction contract process to decrease contracts for power sources in a predetermined area, and an addition contract process to add contracts for power sources outside the predetermined area in order to compensate for the power sources that have decreased due to the reduction contract process.

[0054] Depending on the relationship between areas, it may be impossible to supply electricity to another area beyond a certain amount, resulting in market fragmentation. By adopting this approach, it is possible to predict future contract information in the capacity market, taking into account cases where electricity cannot be supplied due to the relationship between areas. For example, if the area where contracts are predicted to occur is Hokkaido, it will be difficult to transmit electricity to the Kyushu area beyond a certain amount.

[0055] The generation unit 50 may generate a market segmentation model. If, based on past performance, area A and area B are segmented when a certain amount of electricity is exceeded, then the generation unit 50 may generate a market segmentation model in which power supply cannot be provided between area A and area B when a certain amount of electricity is exceeded. The generation unit 50 may adjust various indicators related to market segmentation so that they match past performance. The prediction unit 10 may predict the execution of sell bids and sell bids by considering information on buy bid areas and sell bid areas.

[0056] For example, if you want to predict transactions in a specific area, you can calculate the selling bid volume and selling bid price using only the area excluding those to which power cannot be supplied (the target area), and then use the values ​​in the region where the selling bid volume and selling bid price in the target area are lower than the buying bid volume and buying bid price to predict the transactions for the selling bid volume and selling bid price. In this case, as shown in Figure 4, you can first predict transactions throughout Japan, and then perform reduction and additional transaction processing to predict future transactions in the capacity market using power sources in the target area.

[0057] For example, in the case of supply reliability, the number of calculations can be reduced by assuming that the calculation results match past performance regarding the degree of risk of demand fluctuations and unplanned shutdowns.

[0058] The information processing device 100, in its bidding prediction model, assumes the amount of bids for power sources in a wide-area capacity market, such as a nationwide market. The amount of bids in each of the multiple narrower areas included in the wide area will also be predicted. However, by using a market segmentation model, the amount of bids from a predetermined area may be excluded, and the risk assessment unit 70 may perform a risk assessment of the supply reliability for the amount of bids for power sources in the wide-area capacity market. When the risk assessment unit 70 determines that the risk in supply reliability exceeds a threshold, the amount of bids from power sources located in the target area may be added.

[0059] You may repeatedly exclude bids from designated areas and add bids from power sources located in those areas until the risk falls below a threshold.

[0060] The "Tried Volume at the Time of Nationwide Transaction Processing" in Figure 5 is the result of the prediction unit 10's forecast, as shown in Figure 4, that transactions will occur in the region where the sold bid volume and sold bid price are below the bought bid volume and bought bid price. In contrast, the lower graph of Figure 5 shows the result of the prediction unit 10 performing reduction and addition processing using the market segmentation model. Additional transaction processing should be performed to compensate for the amount of traded volume (electricity) reduced by the reduction processing. In this case, it is also possible to perform additional transaction processing with a traded volume (electricity) that exceeds the amount of traded volume (electricity) reduced by the reduction processing, allowing for some leeway.

[0061] The prediction unit 10, reading unit 20, acquisition unit 40, generation unit 50, search unit 60, risk assessment unit 70, output unit 85, etc. may be implemented by a single unit (control unit) or by different units. Functions from multiple "units" may be integrated; for example, the functions of the prediction unit 10, reading unit 20, and acquisition unit 40 may be implemented by a single unit. Furthermore, the prediction unit 10, reading unit 20, acquisition unit 40, generation unit 50, search unit 60, risk assessment unit 70, output unit 85, etc. may be implemented by a circuit configuration or by a processor executing a program.

[0062] The above-described embodiments and the disclosure of drawings are merely examples for illustrating the invention described in the claims, and the above-described embodiments or the disclosure of drawings do not limit the invention described in the claims. [Explanation of Symbols]

[0063] 10 Prediction Section 20 Reading part 80 Storage section 100 Information Processing Devices

Claims

1. A capacity market bidding prediction model generated using wholesale power performance information including power output contracted in the wholesale power market, supply and demand adjustment performance information including power output contracted in the supply and demand adjustment market, and power information including power output from multiple power sources, wherein the bidding prediction model is generated by simulating past sales bidding curve performance showing the relationship between past bid volume and bid price using past wholesale power performance information and supply and demand adjustment performance information, and power information obtainable from publicly available information, and is read from a storage unit. A prediction unit that predicts future trading information in the capacity market using future buying predictions in the capacity market and the bidding prediction model read out by the reading unit, Equipped with, The aforementioned wholesale electricity performance information includes estimated wholesale electricity revenue in the wholesale electricity market. The aforementioned supply and demand adjustment performance information includes estimated supply and demand adjustment revenue in the supply and demand adjustment market. The auction prediction model is an information processing device that is generated using the maintenance costs of the multiple power sources, the estimated wholesale electricity revenue, and the estimated supply and demand adjustment revenue.

2. The information processing apparatus according to claim 1, wherein the bid prediction model includes information regarding the quantity of bids to sell and the bid price to sell in the capacity market.

3. Future buying forecasts in the capacity market include the volume of bids and the price of bids. The information processing apparatus according to claim 2, wherein the prediction unit predicts that the selling bid quantity and selling bid price will be executed in a region below the buying bid quantity and buying bid price.

4. The aforementioned power supply information includes area information relating to the area, The information processing apparatus according to claim 1 or 2, wherein the prediction unit predicts future contract information in the capacity market, taking into account the area information.

5. The information processing apparatus according to claim 1 or 2, wherein the prediction unit predicts future contract information in a capacity market by reducing the contract amount from a power source in a predetermined area and adding the contract amount from a power source outside the predetermined area within the entire range of a capacity market.

6. The information processing apparatus according to claim 5, wherein the prediction unit predicts market fragmentation and reduces the contracted amount from power sources in a predetermined area within the entire range of a certain capacity market, and increases the contracted amount from power sources outside the predetermined area.

7. The reading unit reads from the storage unit a bidding prediction model for the capacity market, which is generated using wholesale power performance information including power output contracted in the wholesale power market, supply and demand adjustment performance information including power output contracted in the supply and demand adjustment market, and power information including power output from multiple power sources, and which is generated by simulating past sales bidding curve performance showing the relationship between past bid volume and bid price using past wholesale power performance information and supply and demand adjustment performance information, and power information obtainable from publicly available information. The process involves a prediction unit predicting future purchases in the capacity market and using the auction prediction model read out by the reading unit to predict future transaction information in the capacity market. Equipped with, The aforementioned wholesale electricity performance information includes estimated wholesale electricity revenue in the wholesale electricity market. The aforementioned supply and demand adjustment performance information includes estimated supply and demand adjustment revenue in the supply and demand adjustment market. The auction prediction model is an information processing method, which is a model generated using the maintenance costs of the multiple power sources, the estimated wholesale electricity revenue, and the estimated supply and demand adjustment revenue.

8. A program for installation on an information processing device, On an information processing device where a program is installed, A bidding prediction model for the capacity market, generated using wholesale power performance information including power output contracted in the wholesale power market, supply and demand adjustment performance information including power output contracted in the supply and demand adjustment market, and power source information including power output from multiple power sources, and a function to read the bidding prediction model from the memory unit, which was generated by simulating past sales bidding curve performance showing the relationship between past bid volume and bid price using past wholesale power performance information and supply and demand adjustment performance information, and power source information obtainable from publicly available information. A function that predicts future purchases in the capacity market and future transaction information in the capacity market using the auction prediction model read out by the aforementioned reading function, To make it happen, The aforementioned wholesale electricity performance information includes estimated wholesale electricity revenue in the wholesale electricity market. The aforementioned supply and demand adjustment performance information includes estimated supply and demand adjustment revenue in the supply and demand adjustment market. The auction prediction model is a program that is generated using the maintenance costs of the multiple power sources, the estimated wholesale electricity revenue, and the estimated supply and demand adjustment revenue.

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