Information processing device, information processing method, and computer program

Abstract

To provide an information processing apparatus, an information processing method and a computer program which can improve the precision of power market price estimation.SOLUTION: An information processing apparatus includes a processing unit which acquires the planning data of the power generation amount of a power generation facility for generating power tradable in a power market, and, when a first event related to the change of the power generation amount in a target date is detected based on the planning data, estimates the market price fluctuation amount of the power market caused by the first event on the target date.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present disclosure relates to an information processing apparatus, an information processing method, and a computer program.

Background Art

[0002] In the spread and operation of renewable energy, it may be necessary to probabilistically estimate future prices and bid volumes in the electricity market and meet the requirements of various applications. Since the demand and supply of electricity are mainly influenced by weather, good accuracy can be obtained by estimating the price of the electricity market using weather forecasts by a numerical weather simulator. As a specific example, there is a method of obtaining past market prices with similar weather conditions to the weather forecast values of the target day and estimating various quantities (prices and bid volumes) related to the electricity market.

[0003] However, with this method, rapid changes (such as soaring prices) in the electricity market cannot be anticipated in advance. The factors that determine market prices include various things such as seasonal circumstances, troubles in power generation facilities, recent world situations, natural disasters, etc., and in a method that emphasizes the similarity of weather conditions, highly accurate predictions may not be possible in some cases.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] The present embodiment provides an information processing apparatus, an information processing method, and a computer program for improving the accuracy of estimating the market price of the electricity market.

Means for Solving the Problems

[0006] The information processing device disclosed herein includes a processing unit that acquires planned data on the amount of power generated by a power generation facility that generates electricity that can be traded in the electricity market, and when a first event related to a change in the amount of power generated on a target day is detected based on the planned data, the processing unit that estimates the amount of change in the market price of the electricity market caused by the first event on the target day. [Brief explanation of the drawing]

[0007] [Figure 1] A functional block diagram of a price surge prediction device, which is an information processing device according to this embodiment. [Figure 2] A diagram showing specific examples of electricity market performance data areas. [Figure 3] A diagram showing concrete examples of electricity market performance data from across Japan. [Figure 4] A diagram showing specific examples of weather forecast data. [Figure 5] A diagram illustrating a specific example of power generation equipment shutdown plan data. [Figure 6] This figure shows an example of output data from the price surge prediction device (prediction result calculation unit). [Figure 7] A flowchart illustrating an example of the overall operation of the price surge prediction device shown in Figure 1. [Figure 8] A flowchart illustrating an example of the operation of the data extraction range determination unit, the normal price prediction unit, and the prediction result calculation unit. [Figure 9] A diagram showing an example of changing the data extraction range. [Figure 10] A diagram showing an example of how to create searchable data. [Figure 11] A schematic diagram illustrating the operation of the normal price forecasting unit. [Figure 12] This diagram schematically illustrates an example of the calculation process of the prediction result calculation unit when the data extraction range is changed. [Figure 13] A diagram showing another example of output data from the prediction result calculation unit. [Figure 14] This figure shows an example of the hardware configuration of a price surge prediction device as an information processing device according to this embodiment. [Modes for carrying out the invention]

[0008] This embodiment will be described below with reference to the drawings.

[0009] Figure 1 is a functional block diagram of the price surge prediction device 10, which is an information processing device according to this embodiment. The price surge prediction device 10 broadly comprises a processing unit 100, a data acquisition unit 200, a data storage unit 300, and an input unit 400. The processing unit 100 includes a price surge prediction function 100A, a normal state prediction function 100B, and a power market prediction function 100C.

[0010] This embodiment determines whether the market price of electricity will surge on a given day, based on the operating status of a power plant (power generation equipment), specifically, the planned power generation amount of the power generation equipment. For example, data on the planned power generation reduction (shutdown) of a power plant (power generation equipment), which is published on the Power Generation Information Disclosure Website (HJKS), is acquired periodically or intermittently, and events related to changes in power generation (first event or power generation equipment factor event) are detected based on the reduction amount or the change in the reduction amount from the previous day. Whether or not a power generation equipment factor event is detected is used to estimate whether or not a price surge will occur.

[0011] If the first event is detected, a price surge is determined; if the first event is not detected, it is determined that no price surge will occur. If it is determined that a price surge will occur, the amount of change in the market price of the electricity market caused by the first event on the target day is estimated, and the market price on the target day is estimated based on this change. This allows for a highly accurate estimation of the market price even when the market price surges on the target day. For example, even if the power generation status of a power generation facility is stopped or the amount of power generated decreases on the target day due to an unexpected cause, the market price on the target day can be estimated with high accuracy.

[0012] Note that the amount of decrease in the power generation amount at the power plant is also called the stop amount in the sense that power generation is stopped by the amount of decrease. When the power generation equipment stops, the power generation amount corresponding to the rated output decreases. When reducing the output of the power generation equipment, the reduced amount becomes the reduction amount. In the following description, the expression of stopping the power generation equipment may be mainly used, but it is assumed that the case of reducing the output of the power generation equipment may also be included in the stop of the power generation equipment.

[0013] In addition, in the present embodiment, in addition to the operating status of the power plant (power generation equipment), an event related to the weather (second event or weather factor event) is detected based on the weather prediction value of the prediction target date. Whether or not a weather factor event is detected is used to determine whether a soaring of the market price due to weather causes occurs. When the second event is detected, it is determined that a price increase due to weather causes occurs, and when the second event is not detected, it is determined that a price increase due to weather causes does not occur. When it is determined that a price increase occurs, the market price is estimated using past data (weather prediction data and power market performance data of past years) in which the weather conditions are similar to those of the prediction target date. Thereby, even when the power generation amount decreases (including the stop of power generation) due to a sudden change in weather conditions, the market price on the target date can be estimated with high accuracy.

[0014] As described above, according to the present embodiment, even when the market price soars due to a decrease in the power generation amount due to a trouble in the power generation equipment or a sudden change in weather conditions, the market price can be estimated with high accuracy.

[0015] In the following description, a future date (prediction target date) is mainly assumed as the target date for estimating the market price, and the case of estimating the market price on the prediction target date is shown. In the present embodiment, estimating the market price of a future date is particularly called predicting the market price, and hereinafter, mainly estimating the market price and the like will be described as predicting the market price. Hereinafter, the present embodiment will be described in more detail.

[0016] The data acquisition unit 200 includes a weather prediction acquisition unit 210, a power market performance acquisition unit 220, and a power generation equipment stop plan acquisition unit 230.

[0017] The weather forecast acquisition unit 210 acquires weather forecast data from the weather forecasting system 1, including weather forecast results from AMeDAS stations nationwide (e.g., calculation results from the numerical weather simulator WRF), and sends the weather forecast data to the data storage unit 300. The weather forecast data may be acquired at arbitrary time intervals, such as every hour, every day, every week, or it may be acquired by sending an acquisition request to the weather forecasting system 1 at the necessary timing.

[0018] The electricity market performance acquisition unit 220 acquires actual market prices and transaction volumes (contracted amounts) of the electricity market, bid volumes in the transaction market, virtual system price data, etc., from the electricity market performance value management system 2 as electricity market performance data, and sends the electricity market performance data to the data storage unit 300. Examples of information that can be acquired from the electricity market performance value management system 2 include, for example, information disclosed on the website of the Japan Electric Power Exchange (JEPX), a general incorporated association, http: / / www.jepx.org / market / index.html. Electricity market performance data may be acquired daily, at arbitrary intervals such as one-hour blocks which are the unit of trading time in the electricity market, or by sending an acquisition request to the electricity market performance value management system 2 at the necessary timing.

[0019] The power generation equipment shutdown plan acquisition unit 230 acquires data (power generation equipment shutdown plan data) regarding the operating status and shutdown status of power plants (power generation equipment) of each power source type nationwide from the power plant operation status management system 3, and sends the power generation equipment shutdown plan data to the data storage unit 300. Examples of information that can be acquired from the power plant operation status management system 3 include, for example, the power generation information disclosure system and information disclosed on the HJKS website https: / / hjks.jepx.or.jp / hjks / top. The timing of acquisition of the power generation equipment shutdown plan data is not particularly limited as long as it can be acquired intermittently. It may be acquired at any time interval such as every hour, every day, every week, or it may be acquired by sending an acquisition request to the power plant operation status management system 3 at the necessary timing.

[0020] The data storage unit 300 includes a weather forecast storage unit 310, a power market performance storage unit 320, and a power generation equipment shutdown plan storage unit 330.

[0021] The weather forecast storage unit 310 receives weather forecast data from the weather forecast acquisition unit 210 and stores the weather forecast data. The weather forecast storage unit 310 also stores weather forecast data acquired in the past. The stored weather forecast data is sent to the price surge forecast function 100A and also to the normal price forecast data storage unit 180 of the normal price forecast function 100B. The normal price forecast data storage unit 180 stores the weather forecast data received from the weather forecast storage unit 310.

[0022] The electricity market performance data storage unit 320 receives electricity market performance data from the electricity market performance data acquisition unit 220 and stores the electricity market performance data. The electricity market performance data storage unit 320 also stores electricity market performance data acquired in the past. The stored electricity market performance data is sent to the price surge prediction function 100A and also to the normal price prediction data storage unit 180 of the normal price prediction function 100B. The normal price prediction data storage unit 180 stores the electricity market performance data received from the electricity market performance data storage unit 320.

[0023] The power generation equipment shutdown plan storage unit 330 receives power generation equipment shutdown plan data from the power generation equipment shutdown plan acquisition unit 230 and stores the power generation equipment shutdown plan data. The electricity market performance storage unit 320 also stores electricity market performance data acquired in the past. The power generation equipment shutdown plan storage unit 330 also stores electricity market performance data acquired in the past. The stored power generation equipment shutdown plan data is sent to the price surge prediction function 100A.

[0024] The input unit 400 receives input from the user and sends the input information to the price surge prediction function 100A. The input unit 400 is a device that can input information using any method, such as a keyboard, mouse, touch panel, voice input unit, or gesture input unit. The types of information accepted by the input unit 400 are shown below as [1] to [3].

[0025] [1] Information (aggregation item information) regarding the items (e.g., cause of shutdown, type of shutdown (planned shutdown, unplanned shutdown)) that are subject to aggregation of the decrease in power generation output from power generation facilities in order to determine whether or not a price surge will occur due to a problem with the power generation facilities. As described later, the planned shutdown values ​​of the power generation facilities at the power plant (planned values ​​of the decrease or shutdown amount, which is the amount of power generated that decreases from the planned power generation amount (e.g., rated output)) are totaled for each area corresponding to the electricity market, and the presence or absence of a price surge in the electricity market is determined based on the totaled values. More specifically, it is determined whether or not an event related to a change in power generation (first event or power generation facility-related event) is detected based on the totaled values. If a power generation facility-related event is detected, it is determined that a price surge due to power generation facilities will occur, and if a power generation facility-related event is not detected, it is determined that a price surge due to power generation facilities will not occur. In this way, the presence or absence of a price surge is determined. Note that the items subject to aggregation may be the type of power generation facility in addition to the cause of shutdown and type of shutdown.

[0026] [2] Information indicating the criteria for determining whether or not there has been a price surge (conditions for determining the cause of power generation equipment). Examples of criteria include a threshold for the amount of decrease in power generation (power generation decrease) and a threshold for the change in the power generation decrease from the previous day's value.

[0027] [3] Information indicating the items to be used for determining whether a price surge is caused by weather, and the conditions for determination (weather-related determination conditions). Specifically, this includes information on which weather (weather forecast) to focus on, and threshold information for comparison with the weather forecast value for that weather. As described later, it is determined whether a weather-related event (second event or weather-related event) is detected based on the weather forecast value indicated by the weather forecast item. If a weather-related event is detected, it is determined that a price surge caused by weather will occur; if it is not detected, it is determined that a price surge caused by weather will not occur.

[0028] This section explains the overview of the price surge prediction function 100A. The price surge prediction function 100A receives electricity market performance data and power generation equipment shutdown plan data from the data storage unit 300, and receives aggregation item information and judgment conditions (power generation equipment cause judgment conditions) from the input unit 400. The price surge prediction function 100A determines whether or not a price surge in the electricity market price (hereinafter referred to as a price surge) will occur due to power generation equipment, and calculates the amount of the surge if one occurs. The price surge prediction function 100A sends data indicating the calculated surge amount to the output unit 500.

[0029] In this embodiment, a price surge is defined as a price exceeding a benchmark price determined for each area. The method for determining the benchmark price is arbitrary. For example, based on the most recent market price, one could identify the normal price when there is no price surge and the price when there is a price surge (normal price + price surge), and then use the price that divides these two prices in half as the benchmark price. Other methods are also possible. An example of how to determine the benchmark price is shown below. Example 1: In a scenario where the day traded in the electricity market is divided into 48 time slots of 30 minutes each, and the commodity (electricity) is traded for each time slot, a standard price of 40 yen / kWh is uniformly set for each time slot. Example 2: Based on electricity market performance data from the past year, the 75th percentile value is used as the benchmark price for each time frame.

[0030] Furthermore, the price surge prediction function 100A receives weather forecast data from the weather forecast storage unit 310 and weather forecast items and judgment conditions (weather cause judgment conditions) from the input unit 400. The price surge prediction function 100A determines whether or not a price surge will occur due to weather. If it is determined that a price surge will not occur, it determines the data extraction range necessary to calculate the market price when a price surge does not occur due to weather (for example, 7 days from the day before the forecast target date) and sends information indicating the specified data extraction range to the normal forecast function 100B. If it is determined that a price surge will occur, it identifies the range of data periods (data extraction range) necessary to calculate the market price when a price surge occurs due to weather, from the weather forecast data and the actual electricity market data, respectively (for example, a period in a previous year with similar weather conditions) and sends information indicating the specified data extraction range to the normal forecast function 100B. In this way, if it is determined that a price surge will occur due to weather, the data extraction range is changed from the normal range. Market prices when weather-related price increases occur, and market prices when weather-related price increases do not occur, are calculated using the normal forecast function of 100B.

[0031] The following provides a more detailed explanation of the price surge prediction function 100A. The price surge prediction function 100A is a function that predicts price surges caused by power generation equipment, and includes a power generation equipment shutdown plan data preprocessing unit 110 (hereinafter referred to as the preprocessing unit 110), a trend analysis unit 120, a price surge determination unit (power generation equipment cause) 130, a price sensitivity calculation unit 140, and a surge amount prediction unit 150.

[0032] The preprocessing unit 110 performs preprocessing on the power generation equipment shutdown plan data. More specifically, the preprocessing unit 110 receives the power generation equipment shutdown plan data from the data storage unit 300 and aggregate item information from the input unit 400. The preprocessing unit 110 aggregates (sums) the planned values ​​of the reduction amount for each area for the items indicated in the aggregate item information in the power generation equipment shutdown plan data, and sends the aggregated reduction amount data to the trend analysis unit 120.

[0033] The trend analysis unit 120 receives area-specific decline data from the preprocessing unit 110 and electricity market performance data from the electricity market performance storage unit 320, and performs trend analysis of electricity market prices based on the fluctuations (time-series changes) of the decline amount for each area and the fluctuations (time-series changes) of electricity market prices. More specifically, the trend analysis unit 120 receives area-specific decline data from the preprocessing unit 110 and electricity market performance data from the electricity market performance storage unit 320, analyzes the fluctuation trends of the decline amount for each area and the fluctuation trends of electricity market prices, and calculates the change in the decline amount for each area (for example, the change from the previous day) and the rate of change in electricity market prices in response to the change in the decline amount. The trend analysis unit 120 sends the power generation stoppage change amount data, including the calculated information, to the price surge determination unit (power generation equipment cause) 130. The change in the amount of decrease may be calculated, for example, by the difference between the amount of decrease calculated based on the first plan data acquired at the first time point (for example, the day before the forecast date) for the amount of power generated by the power generation facility on the forecast date, and the amount of decrease calculated based on the second plan data acquired at a second time point prior to the first time point (for example, the day before the first time point) for the amount of power generated by the power generation facility on the forecast date. In other words, the amount of change in the amount of decrease can be calculated by comparing the first plan data and the second plan data.

[0034] The price surge determination unit (power generation equipment cause) 130 determines whether a price surge (power generation equipment cause price surge) will occur due to the shutdown of a power plant (power generation equipment). More specifically, the price surge determination unit (power generation equipment cause) 130 uses the area-specific power generation shutdown change amount data received from the trend analysis unit 120 and the thresholds received from the input unit 400 (at least one of the decrease amount threshold (shutdown amount threshold) and the decrease amount change amount (change amount of decrease amount)) to determine whether an event related to the change in power generation amount (first event or power generation equipment factor event) is detected. If a power generation equipment factor event is detected, it is determined that a power generation equipment cause price surge will occur, and if a power generation equipment factor event is not detected, it is determined that a power generation equipment cause price surge will not occur. Whether a power generation equipment factor event is detected is determined, for example, by whether the decrease in power generation amount for each area exceeds the threshold on the forecast target day, and whether the change in the decrease amount (change in the decrease amount from the previous day (the day before the forecast target day)) exceeds the threshold. If any threshold is exceeded, a power generation equipment-related event is detected, and it is determined that a price surge due to power generation equipment will occur. The price surge determination unit (power generation equipment-related) 130 sends information on whether or not a price surge due to power generation equipment will occur to the price surge amount prediction unit 150. Furthermore, if it is determined that a price surge will occur, it sends information indicating the amount of decrease in power generation and the amount of change in the decrease (decrease amount / change amount information) to the price surge amount prediction unit 150.

[0035] The price sensitivity calculation unit 140 calculates price sensitivity, which is an index that converts the change in the decrease in power generation (change in power generation equipment shutdown) into a change in the price of electricity in the electricity market. More specifically, the price sensitivity calculation unit 140 uses electricity market performance data received from the electricity market performance storage unit 320 to calculate price sensitivity, which is an index that converts the change in the decrease into a change in the price of electricity in the electricity market. The price sensitivity calculation unit 140 sends the calculated price sensitivity data (price sensitivity data) to the price surge prediction unit 150.

[0036] The price surge prediction unit 150 predicts the amount of the price surge (the price difference from the normal price assuming there is no price surge due to power generation equipment) when the price surge determination unit (power generation equipment cause) 130 determines that a price surge will occur. More specifically, when the price surge determination unit (power generation equipment cause) 130 determines that a price surge due to power generation equipment will occur, the price surge prediction unit 150 receives the change in power generation decrease data and the price sensitivity data and predicts the price surge on the target date. The price surge prediction unit 150 sends data indicating the predicted price surge (price surge data) to the prediction result calculation unit 182. If the price surge determination unit (power generation equipment cause) 130 determines that a price surge due to power generation equipment will not occur, the price surge prediction unit 150 may send price surge data indicating 0 yen as the price surge to the prediction result calculation unit 182.

[0037] The price surge prediction function 100A includes a price surge determination unit (weather cause) 160 and a data extraction range determination unit 170, as a function to predict price surges caused by weather.

[0038] The price surge determination unit (weather-related) 160 receives weather forecast data and electricity market performance data from the data storage unit 300, and information indicating weather forecast items and thresholds from the input unit 400. The price surge determination unit (weather-related) 160 identifies the weather forecast value indicated by the weather forecast item in the weather forecast data and detects weather-related events (secondary events or weather-related events) based on the weather forecast value. If a weather-related event is detected, it is determined that a weather-related price surge will occur; if not detected, it is determined that a weather-related price surge will not occur. Whether or not a weather-related event occurs is determined, for example, by whether or not the weather forecast value exceeds a threshold. In this case, if the weather forecast value meets the threshold, it is determined that a weather-related price surge will occur. Meeting the threshold can mean either exceeding or falling below the threshold, depending on the type of weather. The price surge determination unit (weather-related) 160 sends information on whether or not a weather-related price surge will occur to the data extraction range determination unit 170.

[0039] The data extraction range determination unit 170 determines the data extraction range (data period) to be used by the normal price forecast unit 181 based on information from the price surge determination unit (weather cause) 160 regarding whether or not a weather-related price surge will occur. For example, if it is determined that a weather-related price surge will not occur, the data extraction range is determined to show a period of a certain duration (e.g., one week) starting from the day before the forecast target date (the trading day one day prior). If it is determined that a weather-related price surge will occur, the data extraction range is determined to show a similar period in the past from past weather forecast data that includes days similar to the weather conditions indicated by the weather forecast value (or days within a certain period before and after), and the data extraction range showing the specified period is determined. The similar period in the past can be any length, such as 30 days. The data extraction range determination unit 170 sends the information indicating the determined data extraction range to the normal price forecast unit 181 of the normal forecast function 100B.

[0040] The normal price prediction function 100B comprises a data storage unit 180 for normal price prediction, a normal price prediction unit 181, and a prediction result calculation unit 182.

[0041] The regular price forecast data storage unit 180 receives and stores electricity market price data and weather forecast data from the data storage unit 300. The regular price forecast data storage unit 180 may also store data that it has received from the data storage unit 300 in the past.

[0042] The normal price forecasting unit 181 extracts weather forecast data and actual electricity market price data from the storage unit 180 based on the data extraction range information received from the data extraction range determination unit 170. Based on the extracted data, the normal price forecasting unit 181 forecasts the market price. The forecast performed by the normal price forecasting unit 181 is called a normal price forecast. By using data within the range indicated in the data extraction range information received from the data extraction range determination unit 170, if it is determined that a price surge due to weather will occur, the normal price forecasting unit 181 can perform a price forecast that takes into account the price surge due to weather, using data from similar periods in the past. If it is determined that a price surge due to weather will not occur, the unit can perform a price forecast as usual, for example, using the most recent data (for example, data for one week prior to the forecast date). The price forecasted by the normal price forecasting unit 181 is the price assuming there is no price surge due to power generation equipment (normal price or first market price), and the normal price will reflect the price surge due to weather if there is one. The normal price forecasting unit 181 calculates a predicted value for the electricity market price (predicted value for the normal price) and sends data including the predicted value (normal price data) to the forecast result calculation unit 182.

[0043] The prediction result calculation unit 182 receives normal price data from the normal price prediction unit 181 and surge amount data from the surge amount prediction unit 150, and calculates the final prediction result for the electricity market price. For example, the prediction result for the final electricity market price is calculated by adding the surge amount indicated by the surge amount data (if there is no price surge due to power generation equipment, the surge amount can be 0 yen) to the normal price indicated by the normal price data. Calculating the final electricity market price by adding the normal price and the surge amount is just one example; other methods are also acceptable as long as they can be calculated using a function that includes both the normal price and the surge amount. For example, the final electricity market price may be calculated by a weighted sum of the normal price and the surge amount. The prediction result calculation unit 182 sends output data, including the calculated prediction results, to the output unit 500. The output data may also include information other than the prediction results, such as the date, normal price, and surge amount.

[0044] The output unit 500 outputs the output data received from the prediction result calculation unit 182. The output unit 500 may be, for example, a display, and display the output data on the screen. The output unit 500 may also be a communication device. In this case, the output unit 500 may transmit the output data to the equipment of a company that uses the output data to conduct business.

[0045] For example, the output unit 500 may transmit output data to a bidding device that generates bidding data for the electricity market and provides it to the electricity market trading system. If the bidding device determines, based on the output data, that the market price will be higher than a threshold on the predicted date, it may place a buy bid for the required amount of electricity with the electricity market trading system before the predicted date in order to buy electricity before the predicted date. Alternatively, in order to sell electricity at a high price on the predicted date, it may refrain from placing a sell bid for the required amount of electricity until before the predicted date, and then place a sell bid on the predicted date to sell the electricity at a high price.

[0046] The output unit 500 may also transmit the output data to a device (DR device) that controls the demand response (DR) of a demand response (DR) operator. If the DR device determines that the market price will be higher than a threshold on the forecast date, it may plan to implement downward DR on the forecast date to encourage consumers to reduce their electricity usage. There are many other ways in which the output data can be utilized.

[0047] Before describing the operation of this embodiment, the definitions and specific examples of various parameters, data, and mathematical formulas are shown below.

[0048] TIFF0007855541000001.tif29170

[0049] TIFF0007855541000002.tif17170

[0050] TIFF0007855541000003.tif19170

[0051] TIFF0007855541000004.tif51170

[0052] Figure 2 shows a specific example of electricity market performance data area. The spot market performance data for the electricity market records the system price (yen / kWh) and the area price (market price) (yen / kWh) for each 30-minute time slot. The time code is an integer value from 1 to 48 that labels each 30-minute time slot. Spot average price from the previous hour (yen / kWh) may also be recorded.

[0053] Figure 3 shows specific examples of electricity market performance data from across the country. Virtual system prices are recorded. Virtual system prices have been published on the JEPX website since January 2022. Here, the virtual system price refers to the price at the intersection of the supply and demand curves when the sell bid volume and buy bid volume are increased by 0.5 GW, 1 GW, and 5 GW, respectively, using the supply and demand curve data of the system price for each time frame. For example, "Virtual system price sell 500 MW" is the price at the intersection of the supply and demand curves when the sell bid volume is increased by 0.5 GW. "Virtual system price buy 1000 MW" is the price at the intersection of the supply and demand curves when the buy bid volume is increased by 1 GW. The price at the intersection corresponds to, for example, the execution price.

[0054] TIFF0007855541000005.tif21170

[0055] Figure 4 shows a specific example of weather forecast data. As numerical weather forecast data, we use weather research and forecasting (WRF) data at 10-minute intervals from AMeDAS stations used by the Japan Meteorological Agency. In the example figure, the average value every 30 minutes is shown. For each area to be forecasted, we use the temperature (T2: °C) and solar radiation intensity (AVG4: W / m2) of all AMeDAS stations included in the area. The column names use the code number, such as "T2_code" and "AVG4_code". For example, "T2_00001" is the temperature at AMeDAS station 00001, and "AVG4_00001" is the solar radiation intensity at AMeDAS station 00001.

[0056] TIFF0007855541000006.tif22170

[0057] Figure 5 shows a specific example of power generation equipment shutdown plan data. Information on power generation facility shutdowns is published on HJKS. HJKS centrally manages the operation and shutdown information of power generation facilities (generators) in each area. The shutdown information of power generation facilities allows for understanding the operation plans of power generation facilities in each area. The information includes area, power generation company, power plant code, power plant name, power generation type, unit name (generator identifier), authorized output, shutdown category (planned shutdown, unplanned shutdown, output reduction), type, reduction amount (power generation reduction), shutdown date and time, recovery outlook, planned recovery date, cause of shutdown, and last updated date and time.

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[0067] A similar year is selected by choosing a year in which the average price of actual prices from the day before the target date t to one week prior is close. For example, if the target date t = 2022 / 03 / 17, the average price for this year is calculated from the data for the period 2022 / 03 / 10 to 2022 / 03 / 16. Similarly, for years prior to 2022, the average price is calculated from the data for the period 20XX / 03 / 10 to 20XX / 03 / 16. "XX" can be, for example, "21", "20", "19", "18", or "17". Here, the number of years to go back is 5, but it can be less than 5 or 6 or more. The year among these XX that is closest to this year's average is selected as the similar year. Here, the same period for each year is targeted, but it is also possible to detect the closest past period (1 week) of actual price data from the day before the target date t to one week prior and use that as the similar period. In this case, the past period can be the same year as the target date, or it can be a year earlier than the year to which the target date belongs. The number of years to go back can be arbitrary.

[0068] TIFF0007855541000026.tif24170

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[0079] The flowchart in Figure 7 is just one example of operation, and other operations are also possible. For example, if it is determined that a price surge due to weather will not occur, the data extraction range determination unit 170 may send information specifying a certain period (for example, one week) from the day before the forecast target date to the normal price forecast data storage unit 180, and the normal price forecast data storage unit 180 may perform data extraction based on that information. Alternatively, the information or the data extraction range change information described above may be sent to the normal price forecast unit 181 instead of the normal price forecast data storage unit 180, and the normal price forecast unit 182 may specify the data range to the normal price forecast data storage unit 180 and perform reading.

[0080] TIFF0007855541000039.tif73170

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[0090] (Step S15) The prediction result calculation unit 182 calculates a predicted market price (area price) based on the predicted value of the normal price and the predicted value of the price increase. The cases in which the data extraction range is not changed and the cases in which it is changed will be explained separately.

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[0094] TIFF0007855541000064.tif39170

[0095] As described above, according to this embodiment, based on the operating status of the power plant, specifically the planned power generation data of the power generation equipment, it is determined whether a surge in market prices will occur on the target date. If it is determined that a surge will occur, the amount of the market price change is estimated based on the planned data. By estimating the market price based on this change, it is possible to estimate the market price with high accuracy even when a surge in market prices occurs.

[0096] In this embodiment, in addition to the operating status of the power generation equipment at the power plant, it is determined whether a surge in market prices due to weather causes will occur based on the weather forecast values ​​for the target date. If it is determined that a surge due to weather causes will occur, the market price is estimated using past data (weather forecast data and actual electricity market data) with similar weather conditions to the target date. This makes it possible to estimate the market price with high accuracy even if the amount of power generated decreases or stops due to sudden changes in weather conditions.

[0097] Thus, according to this embodiment, even when power generation decreases due to troubles with power generation equipment or when market prices surge due to sudden changes in weather conditions, market prices can be estimated with high accuracy. This embodiment can improve the profitability of businesses involved in the supply and demand of electricity and can be used in fuel cell utilization planning, etc.

[0098] (modified version) In the embodiment described above, a surge in market prices was determined based on a decrease in power generation. However, by performing the same process in the case of an increase in power generation, it is possible to determine a market price crash and predict the market price. In this case, one should replace "surge" with "crash" and "decrease" with "increase" in the description above.

[0099] TIFF0007855541000065.tif35170

[0100] TIFF0007855541000066.tif29170

[0101] [1] Hyperparameters for similarity search used below [Table 1]

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[0103] TIFF0007855541000073.tif18170

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[0104] TIFF0007855541000078.tif13170

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[0107] TIFF0007855541000095.tif12170

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[0108] TIFF0007855541000098.tif18170

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[0109] (Hardware configuration) Figure 14 shows the hardware configuration of the price surge prediction device 10 as an information processing device according to this embodiment. The price surge prediction device 10 is composed of a computer device 600. The computer device 600 includes a processor CPU 601, an input interface 602, a display device 603, a communication device 604, a main memory 605, and an external memory device 606, which are interconnected by a bus 607.

[0110] The CPU (Central Processing Unit) 601 executes an information processing program, which is a computer program, on the main memory 605. The information processing program is a program that implements each of the above-described functional configurations of this device. The information processing program may not be a single program, but rather a combination of multiple programs or scripts. Each functional configuration is realized when the CPU 601 executes the information processing program.

[0111] The input interface 602 is a circuit for inputting operation signals from input devices such as keyboards, mice, and touch panels to this device.

[0112] The display device 603 displays data output from this device. The display device 603 is, for example, an LCD (liquid crystal display), an organic electroluminescent display, a CRT (cathode ray tube), or a PDP (plasma display), but is not limited to these. Data output from the computer device 600 can be displayed on this display device 603.

[0113] The communication device 604 is a circuit for this device to communicate with an external device wirelessly or via a wired connection. Data can be input from an external device via the communication device 604. The data input from the external device can be stored in the main memory 605 or the external memory 606.

[0114] The main memory 605 stores information processing programs, data necessary for the execution of the information processing programs, and data generated by the execution of the information processing programs. The information processing programs are deployed and executed on the main memory 605. The main memory 605 is, for example, RAM, DRAM, or SRAM, but is not limited to these. Each storage unit or database in Figure 1 may be built on the main memory 605.

[0115] The external storage device 606 stores information processing programs, data necessary for the execution of the information processing programs, and data generated by the execution of the information processing programs. These information processing programs and data are read into the main memory 605 when the information processing programs are executed. The external storage device 606 is, for example, a hard disk, optical disk, flash memory, and magnetic tape, but is not limited to these. Each storage unit or database of the information processing device may be built on the external storage device 606.

[0116] The information processing program may be pre-installed on the computer device 600, or it may be stored on a storage medium such as a CD-ROM. Furthermore, the information processing program may be uploaded to the internet.

[0117] Furthermore, this device may consist of a single computer device 600, or it may be configured as a system consisting of multiple interconnected computer devices 600.

[0118] It should be noted that the present invention is not limited to the embodiments described above, and the components can be modified and implemented in practice without departing from the spirit of the invention. Furthermore, various inventions can be formed by appropriately combining the multiple components disclosed in the embodiments described above. For example, a configuration in which some components are removed from all the components shown in each embodiment is also conceivable. Moreover, components described in different embodiments may be appropriately combined.

[0119] This embodiment can also be configured as follows. [Note] [Item 1] A processing unit acquires planned data on the amount of power generated by a power generation facility that generates electricity that can be traded in the electricity market, and when it detects a first event related to a change in the amount of power generated on a target day based on the planned data, it estimates the amount of change in the market price of the electricity market on the target day caused by the first event. Equipped with an information processing device. [Item 2] The first event is that the change in the amount of power generated on the target day exceeds a threshold. The information processing device described in item 1. [Item 3] The first event is when the difference between the change in the amount of power generated on the target day and the change in the amount of power generated on a trading day prior to the target day exceeds a threshold. An information processing device as described in item 1 or 2. [Item 4] The processing unit estimates a first market price, which is the market price if the first event does not occur on the target day, based on the actual market price data in the electricity market. The processing unit estimates a second market price, which is the market price when the first event occurs on the target date, based on the first market price and the amount of change. An information processing device as described in any one of items 1 to 3. [Item 5] The processing unit calculates the second market price using a function that includes the first market price and the fluctuation amount. The information processing device described in item 4. [Item 6] The aforementioned planning data includes at least one of the cause of the fluctuation in the amount of power generated by the power generation equipment, the type of the fluctuation, and the type of the power generation equipment. The system includes an input unit in which the user specifies at least one piece of information, such as the cause of the fluctuation, the type of the fluctuation, and the type of the power generation equipment. The processing unit determines whether the first event occurs based on the change in the total amount of power generated by the power generation equipment that matches the information specified by the user. An information processing device as described in any one of items 1 to 5. [Item 7] The first event is an event relating to a change in the total amount of electricity generated by multiple power generation facilities located within the area covered by the aforementioned electricity market. An information processing device as described in any one of items 1 to 6. [Item 8] The first event is that the change in the total amount of power generated exceeds a threshold. The information processing device described in item 7. [Item 9] The first event is when the difference between the total change in the amount of power generated on the target day and the total change in the amount of power generated on trading days prior to the target day exceeds a threshold. The information processing device described in item 7 or 8. [Item 10] The processing unit calculates a coefficient representing an estimated value of the change in the market price when the amount of electricity traded increases by a unit amount, based on the actual market price data. The processing unit calculates the amount of change by multiplying the difference between the amount of change in the amount of power generated on the target day and the amount of change in the amount of power generated on the trading days prior to the target day by the coefficient. An information processing device described in any one of items 1 to 9. [Item 11] The processing unit acquires the actual market price data and the weather forecast data for the period prior to the target date. The processing unit obtains weather forecast values ​​for the target day and calculates the first market price for the target day based on the obtained weather forecast values, the actual data, and the weather forecast data. Information processing device as described in item 4 or 5. [Item 12] The processing unit acquires the actual market price data and the weather forecast data, and each of the actual data and the weather forecast data includes a first period prior to the target date and a second period prior to the first period. The processing unit obtains weather forecast values ​​for the target day, and if a second weather-related event is detected based on the weather forecast values, it calculates the first market price based on the actual data and weather forecast data for the second period. If no second event is detected, it calculates the first market price based on the actual data and weather forecast data for the first period. Information processing device as described in item 4 or 5. [Item 13] The processing unit obtains the first plan data acquired at a first time point for the amount of power generated by the power generation facility on the target day, and the plan data acquired at a second time point prior to the first time point for the amount of power generated by the power generation facility on the target day, and calculates the difference based on the first plan data and the second plan data. The information processing device described in item 3. [Item 14] The change in the amount of power generated is the decrease in the amount of power generated. An information processing device as described in item 2 or 3. [Item 15] The change in the amount of power generated is the decrease in the amount of power generated. The information processing device described in item 3. [Item 16] The change in the total amount of power generated is the decrease in the total amount of power generated. The information processing device described in item 8. [Item 17] The change in the total amount of power generated is the decrease in the total amount of power generated. The information processing device described in item 9. [Item 18] We obtain planned generation data for power generation facilities that generate electricity that can be traded in the electricity market. If a first event related to a change in power generation on a target day is detected based on the aforementioned planning data, the amount of change in the market price of the electricity market caused by the first event on the target day is estimated. Information processing methods. [Item 19] The steps include obtaining planned data on the amount of electricity generated by power generation facilities that generate electricity that can be traded in the electricity market, and If a first event related to a change in power generation on a target day is detected based on the aforementioned planning data, the steps include: estimating the amount of change in the market price of the electricity market on the target day due to the first event; A computer program that causes a computer to execute something. [Explanation of Symbols]

[0120] 1. Weather forecasting system 2. Electricity Market Performance Data Management System 3. Power Plant Operation Status Management System 10 Price surge prediction device 100 Processing Unit 100A Price Increase Prediction Function 100B Normal Prediction Function 100C Power Market Forecasting Function 110 Power generation equipment shutdown plan data preprocessing unit (preprocessing unit) 120 Trend Analysis Department 130 Price surge detection unit (power generation equipment cause) 140 Price Sensitivity Calculation Unit 150 Price Increase Forecast Section 160 Price surge detection unit (weather-related) 170 Data extraction range determination unit 180 Data storage unit for normal price prediction 181 Regular Price Forecast Section 182 Prediction Result Calculation Unit 200 Data Acquisition Unit 210 Weather Forecast Acquisition Department 220 Electricity Market Performance Acquisition Department 230 Power Generation Facility Shutdown Plan Acquisition Department 300 Data Storage Unit 310 Weather forecast memory unit 320 Electricity Market Performance Memory Unit 330 Power generation equipment shutdown plan storage unit 400 Input section 500 Output section 600 Computer devices 601 CPU (Processor) 602 Input Interface 603 Display device 604 Communication equipment 605 Main storage 606 External storage device 607 Bus

Claims

1. We obtain planned generation data for power generation facilities that generate electricity that can be traded in the electricity market. Based on the aforementioned planning data, if the change in the amount of power generated on the target day exceeds a threshold, a first event related to the change in the amount of power generated is detected. A processing unit that estimates the amount of change in the market price of the electricity market caused by the first event on the target date, The planning data includes at least one of the cause of the fluctuation in the amount of power generated by the power generation equipment, the type of the fluctuation, and the type of the power generation equipment, and the input unit allows the user to specify at least one piece of information regarding the cause of the fluctuation, the type of the fluctuation, and the type of the power generation equipment. Equipped with, The processing unit determines whether the first event occurs based on the change in the total amount of power generated by the power generation equipment that matches the information specified by the user, and whether the change in the total amount exceeds the threshold. Information processing device.

2. We obtain planned generation data for power generation facilities that generate electricity that can be traded in the electricity market. Based on the aforementioned planning data, if the difference between the change in the amount of power generated on the target day and the change in the amount of power generated on trading days prior to the target day exceeds a threshold, a first event related to the change in the amount of power generated is detected. A processing unit that estimates the amount of change in the market price of the electricity market caused by the first event on the target date, The planning data includes at least one of the cause of the fluctuation in the amount of power generated by the power generation equipment, the type of the fluctuation, and the type of the power generation equipment, and the input unit allows the user to specify at least one piece of information regarding the cause of the fluctuation, the type of the fluctuation, and the type of the power generation equipment. Equipped with, The processing unit determines whether the first event occurs based on the change in the total amount of power generated by the power generation equipment that matches the information specified by the user, and whether the difference between the change in the total amount on the target day and the change in the total amount on transaction days prior to the target day exceeds the threshold. Information processing device.

3. We obtain planned generation data for multiple power generation facilities that generate electricity that can be traded in the electricity market. Based on the aforementioned planning data, if the total change in the amount of power generated by the multiple power generation facilities located within the area covered by the aforementioned electricity market on the target day exceeds a threshold, a first event related to the change in power generation is detected. A processing unit that estimates the amount of change in the market price of the electricity market caused by the first event on the target date, The planning data includes at least one of the cause of the fluctuation in the amount of power generated by the power generation equipment, the type of the fluctuation, and the type of the power generation equipment, and the input unit allows the user to specify at least one piece of information regarding the cause of the fluctuation, the type of the fluctuation, and the type of the power generation equipment. Equipped with, The processing unit determines whether the first event occurs based on the change in the total amount of power generated by the power generation equipment that matches the information specified by the user, and whether the change in the total amount exceeds the threshold. Information processing device.

4. We obtain planned generation data for multiple power generation facilities that generate electricity that can be traded in the electricity market. Based on the aforementioned planning data, if the difference between the total change in the amount of power generated on the target day and the total change in the amount of power generated on trading days prior to the target day exceeds a threshold, a first event related to the change in the amount of power generated is detected. A processing unit that estimates the amount of change in the market price of the electricity market caused by the first event on the target date, The planning data includes at least one of the cause of the fluctuation in the amount of power generated by the power generation equipment, the type of the fluctuation, and the type of the power generation equipment, and the input unit allows the user to specify at least one piece of information regarding the cause of the fluctuation, the type of the fluctuation, and the type of the power generation equipment. Equipped with, The processing unit determines whether the first event occurs based on the change in the total amount of power generated by the power generation equipment that matches the information specified by the user, and whether the difference between the total on the target day and the total on transaction days prior to the target day exceeds the threshold. Information processing device.

5. We obtain planned generation data for power generation facilities that generate electricity that can be traded in the electricity market. As the aforementioned planning data, first planning data obtained at a first time point for the amount of power generated by the power generation facility on the target day, and second planning data obtained at a second time point prior to the first time point are obtained. Based on the difference between the first plan data and the second plan data, if a first event related to the change in the amount of power generated on the target day is detected, A processing unit that estimates the amount of change in the market price of the electricity market caused by the first event on the target date, The planning data includes at least one of the cause of the fluctuation in the amount of power generated by the power generation equipment, the type of the fluctuation, and the type of the power generation equipment, and the input unit allows the user to specify at least one piece of information regarding the cause of the fluctuation, the type of the fluctuation, and the type of the power generation equipment. Equipped with, The processing unit determines whether or not the first event occurs based on the difference between the first plan data and the second plan data relating to the total amount of power generated by the power generation equipment that matches the information specified by the user, based on the change in the total amount of power generated by the power generation equipment that matches the information specified by the user. Information processing device.

6. The change in the amount of power generated is the decrease in the amount of power generated. The information processing apparatus according to claim 1.

7. The change in the amount of power generated is the decrease in the amount of power generated. The information processing apparatus according to claim 2.

8. The change in the total amount of power generated is the decrease in the total amount of power generated. The information processing apparatus according to claim 3.

9. The sum of the changes in the amount of power generated is the sum of the decreases in the amount of power generated. The information processing apparatus according to claim 4.

10. A computer, We obtain planned generation data for power generation facilities that generate electricity that can be traded in the electricity market. Based on the aforementioned planning data, if the change in the amount of power generated on the target day exceeds a threshold, a first event related to the change in the amount of power generated is detected. On the aforementioned target date, estimate the amount of change in the market price of the electricity market caused by the first event, The planning data includes at least one of the cause of the fluctuation in the amount of power generated by the power generation equipment, the type of the fluctuation, and the type of the power generation equipment, and the information of at least one of the cause of the fluctuation, the type of the fluctuation, and the type of the power generation equipment is received from the user. Based on the change in the total amount of power generated by the power generation equipment that matches the information specified by the user, it is determined whether or not the first event occurs based on whether or not the change in the total amount exceeds the threshold. Information processing methods.

11. A computer, We obtain planned generation data for power generation facilities that generate electricity that can be traded in the electricity market. Based on the aforementioned planning data, if the difference between the change in the amount of power generated on the target day and the change in the amount of power generated on trading days prior to the target day exceeds a threshold, a first event related to the change in the amount of power generated is detected. On the aforementioned target date, estimate the amount of change in the market price of the electricity market caused by the first event, The planning data includes at least one of the cause of the fluctuation in the amount of power generated by the power generation equipment, the type of the fluctuation, and the type of the power generation equipment, and the information of at least one of the cause of the fluctuation, the type of the fluctuation, and the type of the power generation equipment is received from the user. Based on the change in the total amount of power generated by the power generation equipment that matches the information specified by the user, the system determines whether or not the first event occurs based on whether the difference between the change in the total on the target day and the change in the total on the trading days prior to the target day exceeds the threshold. Information processing methods.

12. A computer, We obtain planned generation data for multiple power generation facilities that generate electricity that can be traded in the electricity market. Based on the aforementioned planning data, if the total change in the amount of power generated by the multiple power generation facilities located within the area covered by the aforementioned electricity market on the target day exceeds a threshold, a first event related to the change in power generation is detected. On the aforementioned target date, estimate the amount of change in the market price of the electricity market caused by the first event, The planning data includes at least one of the cause of the fluctuation in the amount of power generated by the power generation equipment, the type of the fluctuation, and the type of the power generation equipment, and the information of at least one of the cause of the fluctuation, the type of the fluctuation, and the type of the power generation equipment is received from the user. Based on the change in the total amount of power generated by the power generation equipment that matches the information specified by the user, it is determined whether or not the first event occurs based on whether or not the change in the total amount exceeds the threshold. Information processing methods.

13. A computer, We obtain planned generation data for multiple power generation facilities that generate electricity that can be traded in the electricity market. Based on the aforementioned planning data, if the difference between the total change in the amount of power generated on the target day and the total change in the amount of power generated on trading days prior to the target day exceeds a threshold, a first event related to the change in the amount of power generated is detected. On the aforementioned target date, estimate the amount of change in the market price of the electricity market caused by the first event, The planning data includes at least one of the cause of the fluctuation in the amount of power generated by the power generation equipment, the type of the fluctuation, and the type of the power generation equipment, and the information of at least one of the cause of the fluctuation, the type of the fluctuation, and the type of the power generation equipment is received from the user. Based on the change in the total amount of power generated by the power generation equipment that matches the information specified by the user, the system determines whether or not the first event occurs based on whether the difference between the total on the target day and the total on transaction days prior to the target day exceeds the threshold. Information processing methods.

14. A computer, We obtain planned generation data for power generation facilities that generate electricity that can be traded in the electricity market. As the aforementioned planning data, first planning data obtained at a first time point for the amount of power generated by the power generation facility on the target day, and second planning data obtained at a second time point prior to the first time point are obtained. Based on the difference between the first plan data and the second plan data, if a first event related to the change in the amount of power generated on the target day is detected, On the aforementioned target date, estimate the amount of change in the market price of the electricity market caused by the first event, The planning data includes at least one of the cause of the fluctuation in the amount of power generated by the power generation equipment, the type of the fluctuation, and the type of the power generation equipment, and the information of at least one of the cause of the fluctuation, the type of the fluctuation, and the type of the power generation equipment is received from the user. Based on the change in the total amount of power generated by the power generation equipment that matches the information specified by the user, the system determines whether or not the first event occurs based on the difference between the first plan data and the second plan data relating to the total. Information processing methods.

15. The steps include obtaining planned data on the amount of electricity generated by power generation facilities that generate electricity that can be traded in the electricity market, and A step of detecting a first event related to the change in power generation when the amount of change in power generation on the target day exceeds a threshold based on the aforementioned planning data, The steps include: estimating the amount of change in the market price of the electricity market due to the first event on the target date; The planning data includes at least one of the cause of the fluctuation in the amount of power generated by the power generation equipment, the type of the fluctuation, and the type of the power generation equipment, and the step of receiving information on at least one of the cause of the fluctuation, the type of the fluctuation, and the type of the power generation equipment from the user. The steps include determining whether the first event occurs based on the change in the total amount of power generated by the power generation equipment that matches the information specified by the user, and whether the change in the total amount exceeds the threshold, A computer program that causes a computer to execute something.

16. The steps include obtaining planned data on the amount of electricity generated by power generation facilities that generate electricity that can be traded in the electricity market, and Based on the aforementioned planning data, a first event related to the change in power generation is detected when the difference between the change in power generation on the target day and the change in power generation on trading days prior to the target day exceeds a threshold. The steps include: estimating the amount of change in the market price of the electricity market due to the first event on the target date; The planning data includes at least one of the cause of the fluctuation in the amount of power generated by the power generation equipment, the type of the fluctuation, and the type of the power generation equipment, and the step of receiving information on at least one of the cause of the fluctuation, the type of the fluctuation, and the type of the power generation equipment from the user. The steps include determining whether the first event occurs based on the change in the total amount of power generated by the power generation equipment that matches the information specified by the user, and whether the difference between the change in the total amount on the target day and the change in the total amount on a transaction day prior to the target day exceeds the threshold, A computer program that causes a computer to execute something.

17. The steps include obtaining planned data on the amount of electricity generated by multiple power generation facilities that generate electricity that can be traded in the electricity market, Based on the aforementioned planning data, the first event related to the change in power generation is detected when the total change in the amount of power generated by the multiple power generation facilities located within the area covered by the aforementioned electricity market on the target day exceeds a threshold. The steps include: estimating the amount of change in the market price of the electricity market due to the first event on the target date; The planning data includes at least one of the cause of the fluctuation in the amount of power generated by the power generation equipment, the type of the fluctuation, and the type of the power generation equipment, and the step of receiving information on at least one of the cause of the fluctuation, the type of the fluctuation, and the type of the power generation equipment from the user. The steps include determining whether the first event occurs based on the change in the total amount of power generated by the power generation equipment that matches the information specified by the user, and whether the change in the total amount exceeds the threshold, A computer program that causes a computer to execute something.

18. The steps include obtaining planned data on the amount of electricity generated by multiple power generation facilities that generate electricity that can be traded in the electricity market, Based on the aforementioned planning data, a first event related to the change in power generation is detected when the difference between the total change in power generation on the target day and the total change in power generation on trading days prior to the target day exceeds a threshold. The steps include: estimating the amount of change in the market price of the electricity market due to the first event on the target date; The planning data includes at least one of the cause of the fluctuation in the amount of power generated by the power generation equipment, the type of the fluctuation, and the type of the power generation equipment, and the step of receiving information on at least one of the cause of the fluctuation, the type of the fluctuation, and the type of the power generation equipment from the user. The steps include determining whether the first event occurs based on the change in the total amount of power generated by the power generation equipment that matches the information specified by the user, and whether the difference between the total on the target day and the total on transaction days prior to the target day exceeds the threshold, A computer program that causes a computer to execute something.

19. The steps include obtaining planned data on the amount of electricity generated by power generation facilities that generate electricity that can be traded in the electricity market, and The steps include obtaining, as the aforementioned planning data, first planning data obtained at a first time point for the amount of power generated by the power generation facility on the target day, and second planning data obtained at a second time point prior to the first time point, Based on the difference between the first plan data and the second plan data, if a first event related to the change in the amount of power generated on the target day is detected, The steps include: estimating the amount of change in the market price of the electricity market due to the first event on the target date; The planning data includes at least one of the cause of the fluctuation in the amount of power generated by the power generation equipment, the type of the fluctuation, and the type of the power generation equipment, and the step of receiving information on at least one of the cause of the fluctuation, the type of the fluctuation, and the type of the power generation equipment from the user. The steps include determining whether or not the first event occurs based on the difference between the first plan data and the second plan data relating to the total amount of power generated by the power generation equipment that matches the information specified by the user, A computer program that causes a computer to execute something.

Images