Calculation device and method for calculating required adjustment capacity

Abstract

To accurately calculate an adjustment force required amount.SOLUTION: An arithmetic apparatus includes: a temperature reference extraction unit that determines a past sample target date based on a predicted temperature at a calculation target date which is a target date of calculating an adjustment force required amount; and an adjustment force required amount calculation unit that calculates the adjustment force required amount at the calculation target date based on time-sequence performance data of a power system at the sample target date.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a calculation device and a method for calculating a required amount of regulation power. [Background technology]

[0002] Because electrical energy is difficult to store, transmission and distribution utilities must operate their power grids in accordance with the principle of "balancing," which maintains the difference between power demand and supply within a certain range. In a vertically integrated system (vertically integrated) that integrates power generation, transmission, and retail, transmission and distribution utilities have traditionally flexibly controlled the output of their own generators to balance power supply and demand in order to achieve this balance. With the deregulation of the power industry, which separated electric utilities into power generation and transmission and distribution utilities, transmission and distribution utilities purchase "balancing capacity" from power generation utilities in the supply and demand balancing market, which is the right to control generator output, and use this capacity to balance power supply and demand. In this case, the cost of procuring balancing capacity is ultimately borne by consumers in the form of wheeling charges. Therefore, in order to control electricity rates, it is important to properly plan the procurement of balancing capacity. Patent Document 1 discloses a configuration including a plurality of generators used as load frequency control (LFC) generators or economic load dispatch control (ELD) generators, a ΔF detection unit that detects a frequency change (ΔF) in a power system, a ΔPT detection unit that detects an interconnection line power flow change (ΔPT), and a natural energy detection unit that detects natural energy (N), and the configuration includes an AR calculation unit that calculates an area power requirement (AR) using the frequency change (ΔF), the interconnection line power flow change (ΔPT), and the output of the natural energy detection unit (N), an AR smoothing unit that smoothes the calculated area power requirement (AR), an AR distribution unit that distributes the smoothed area power requirement (AR) to each generator, a target command value calculation unit that calculates a target command value from the distributed area power requirement (AR) and an ELD schedule calculated by economic load dispatch control (ELD), and a command unit that issues the target command value to each generator and issues a command to switch the generator to either an LFC generator or an ELD generator. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2014-204577 Summary of the Invention [Problem to be solved by the invention]

[0004] In the invention described in Patent Document 1, there is room for improvement in the accuracy of calculating the required amount of regulation power. [Means for solving the problem]

[0005] A calculation device according to a first aspect of the present invention includes a temperature reference extraction unit that determines a past sample target date based on a predicted temperature on a calculation target date that is a target day for calculating a required amount of adjustment capacity, and a required amount of adjustment capacity calculation unit that calculates the required amount of adjustment capacity on the calculation target date based on time-series performance data of the power system on the sample target date. The adjustment capacity requirement calculation unit calculates the adjustment capacity requirement on the calculation target day based on the maximum value for each time slot on the sample target day of an evaluation value of residual demand, which is a value obtained by subtracting output from renewable energy from power demand. . A method for calculating a required amount of regulation capacity according to a second aspect of the present invention is a method for calculating a required amount of regulation capacity executed by a computing device, and includes determining a past sample target date based on a predicted temperature on a target calculation date, which is a target day for calculating the required amount of regulation capacity. Decision Process and calculating the required amount of adjustment capacity on the calculation target date based on time-series performance data of the power system on the sample target date. Calculation process and, The calculation process includes calculating the required adjustment capacity on the calculation target day based on the maximum value for each time period on the sample target day of an evaluation value of residual demand, which is a value obtained by subtracting output from renewable energy from power demand. . [Effects of the Invention]

[0006] According to the present invention, the required amount of regulation power can be calculated with high accuracy. [Brief explanation of the drawings]

[0007] [Figure 1] Hardware configuration diagram of an adjustment capability procurement support system according to an embodiment [Figure 2] Functional configuration diagram of an adjustment capability procurement support system according to an embodiment [Figure 3]An example of a database of required control capacity [Figure 4] Flowchart showing the process of the temperature reference extraction unit [Figure 5] Schematic diagram showing the calculation method for primary control capacity [Figure 6] Schematic diagram showing the calculation method for secondary control capacity (2) [Figure 7] Flowchart showing the processing of the required adjustment capacity calculation unit [Figure 8] 10 is a flowchart showing the processing of the temperature reference extraction unit in Modification 1. [Figure 9] Hardware configuration diagram of the adjustment power procurement support system in Variation 6 [Figure 10] Functional configuration diagram of the adjustment power procurement support system in Variation 6 [Figure 11] Flowchart showing the process of the meteorological criterion extraction unit DETAILED DESCRIPTION OF THE INVENTION

[0008] (Definition of terms) In this specification, renewable energy refers to solar, wind, and other non-fossil energy sources that can be used perpetually as an energy source. Examples of renewable energy include solar, wind, hydroelectric, wave, geothermal, solar heat, and biomass. Note that renewable energy may also include nuclear energy. Residual demand is defined as the value obtained by subtracting the output from renewable energy from the electricity demand.

[0009] --Embodiment-- Hereinafter, an embodiment of an adjustment power procurement support system that is a calculation device will be described with reference to Figures 1 to 7. Note that the following is merely one embodiment, and it is not intended that the invention itself be limited to the specific content below.

[0010] FIG. 1 is a hardware configuration diagram of an adjustment reserve procurement support system 100 according to an embodiment of the present invention, and also shows a power system 20 to which the adjustment reserve procurement support system 100 is applied. The upper part of FIG. 1 shows an example configuration of the power system 20, and the lower part of FIG. 1 shows the configuration of the adjustment reserve procurement support system 100. A communication network 30 that connects the power system 20 and the adjustment reserve procurement support system 100 is also shown between the upper and lower parts of FIG. 1. A supply and demand balancing market 40 is also shown on the right side of FIG. 1. A generator 10, a load 15, and a measurement device 16 are connected to the communication network 30. The power system 20 includes branches (lines) 14, nodes (buses) 11, and the measurement device 16. The generator 10 and the load 15 are each connected to the power system 20 via a node 11 and a transformer 13.

[0011] (Hardware configuration of the adjustment capability procurement support system 100) As shown in the lower part of Figure 1, the adjustment capacity procurement support system 100 is made up of a computer system and includes a display unit 101, an input unit 102, a communication unit 103, a processor 104, a memory 105, and multiple databases. Each device built into the adjustment capacity procurement support system 100 is connected to a communication bus 106 and can exchange information with each other.

[0012] The display unit 101 is, for example, a display device. The display unit 101 may be configured to use a printer device, an audio output device, or the like instead of or together with the display device. The input unit 102 is configured to include, for example, at least one of a keyboard switch, a pointing device such as a mouse, a touch panel, an audio instruction device, or the like. The communication unit 103 is a communication interface for connecting the coordination power procurement support system 100 to the communication network 3 and operates according to a predetermined communication protocol. The processor 104 is a central processing unit. The processor 104 executes a program described below to instruct image data to be displayed, search for data in various databases, and the like. The processor 104 may be configured as one or more semiconductor chips, or as a computer device such as a calculation server.

[0013] The memory 105 is, for example, a RAM (Random Access Memory). The RAM temporarily stores calculation result data, image data, processing programs, and the like required for each process. The screen data stored in the memory 105 may be sent to and displayed on the display unit 101. The control reserve procurement support system 100 includes a residual demand record database 202, a temperature record database 203, a temperature forecast database 204, a verification range database 205, and a control reserve requirement database 206. Note that in this specification and drawings, "database" may also be abbreviated as "DB."

[0014] (Communication Network 30) The communication network 30 connects the various components of the power system 20 illustrated in the upper part of Fig. 1 with the adjustment reserve procurement support system 100 and the supply and demand balancing market 40 illustrated in the lower part of Fig. 1 via communication lines. For example, system state measurements taken by the measuring devices 16, generators 10, and loads 15 installed in the power system 20 are converted into signals and sent to a communication unit 103 of the adjustment reserve procurement support system 100 via the communication network 30.

[0015] Furthermore, the required amount of adjustment power calculated by the adjustment power procurement support system 100 is transmitted as an adjustment power bid amount of the power transmission and distribution business operator from the communication unit 103 of the adjustment power procurement support system 100 to the supply and demand balancing market 40 via the communication network 30. In this way, various state quantities of the power system 20 are collected in chronological order by the adjustment power procurement support system 100 from the measuring devices 16, generators 10, and loads 15 installed in the power system 20, and the required amount of adjustment power calculated by the adjustment power procurement support system 100 is transmitted to the supply and demand balancing market 40.

[0016] (Functional configuration of the adjustment capability procurement support system 100) 2 is a functional configuration diagram of the adjustment reserve procurement support system 100. In FIG. 2, the adjustment reserve procurement support system 100 includes a residual demand record database 202, a temperature record database 203, a temperature forecast database 204, a verification range database 205, and a required adjustment reserve database 206. The adjustment reserve procurement support system 100 also includes a temperature reference extraction unit 110 and a required adjustment reserve calculation unit 130. The temperature reference extraction unit 110 and the required adjustment reserve calculation unit 130 are realized by the processor 104 executing a calculation program read from the program database 201 to the memory 105. The temperature reference extraction unit 110 and the required adjustment reserve calculation unit 130 obtain data required for their respective calculations from the respective databases via the communication bus 106.

[0017] The temperature reference extraction unit 110 determines the date of actual data (hereinafter referred to as the "sample target date") that will be used as a sample for the required adjustment capacity calculation unit 130 to calculate the required adjustment capacity, based on the actual temperature records stored in the temperature record database 203. The required adjustment capacity calculation unit 130 calculates the required adjustment capacity for a future calculation target date based on the time-series actual data of the power system 20 on the sample target date, and writes the calculated amount to the required adjustment capacity database 206. The detailed operations of the temperature reference extraction unit 110 and the required adjustment capacity calculation unit 130 will be described later.

[0018] (Database) The program database 201 stores program data for implementing the temperature reference extraction unit 110 and the adjustment capacity requirement calculation unit 130. The residual demand record database 202 stores the past residual demand of the power system 20 (hereinafter referred to as "residual demand record") as time-series data. As mentioned above, the residual demand is the value obtained by subtracting the output from renewable energy from the power demand.

[0019] The temperature record database 203 stores, as time-series data, temperatures (hereinafter referred to as "temperature record") measured in the past in the target area (hereinafter referred to as "target area") for which the control capacity procurement support system 100 calculates control capacity. The temperature forecast database 204 stores, as time-series data, predicted future temperatures in the target area. The time-series data in the residual demand record database 202, temperature record database 203, and temperature forecast database 204 are values ​​every 30 seconds, for example. However, the time intervals of the data stored in each database do not have to be the same.

[0020] The test range database 205 stores control parameters used by the temperature reference extraction unit 110. In this embodiment, the control parameter is information indicating a temperature range from a reference value. For example, this control parameter is "5," which indicates a range of plus or minus 5 degrees from the reference temperature. Therefore, it can be said that the test range database 205 stores information indicating a predetermined temperature range.

[0021] The required control reserve database 206 stores the required control reserve for each time slot on the calculation target date calculated by the control reserve procurement support system 100. The required control reserve in this embodiment is primary control reserve D1, secondary control reserve (1) D21, secondary control reserve (2) D22, tertiary control reserve (1) D31, and composite contract C. Note that for "secondary control reserve (1)," it is common to use a circled "1" instead of the "1" in parentheses. The same applies to secondary control reserve (2) and tertiary control reserve (1).

[0022] FIG. 3 is a diagram showing an example of the required adjustment capacity database 206. The example shown in FIG. 3 shows the required adjustment capacity for July 1, 2022 and July 2, 2022 calculated by the required adjustment capacity calculation unit 130. Specifically, values ​​are stored every three hours for each of the five required adjustment capacity mentioned above. The adjustment capacity procurement support system 100 may display the required adjustment capacity database 206 on the display unit 101 in the form of a table shown in FIG. 3, or may process the data into a graph or the like and display it on the display unit 101.

[0023] (Operation of the temperature reference extraction unit 110) Figure 4 is a flowchart showing the processing of the temperature reference extraction unit 110. The processing shown in Figure 4 is processing to support adjustment reserve procurement for a single calculation target day. If multiple days are the target, the processing shown in Figure 4 is performed for each day. For example, if the calculation target days are seven days, the temperature reference extraction unit 110 changes the calculation target day and repeats the processing shown in Figure 4 seven times. In step S301, the temperature reference extraction unit 110 identifies the calculation target day. In the following step S302, the temperature reference extraction unit 110 reads the predicted temperatures for the calculation target day from the temperature prediction database 204 and identifies the largest value among them, i.e., the predicted maximum temperature.

[0024] In the next step S303, the temperature reference extraction unit 110 reads the control parameters from the test range database 205 and identifies the temperature range to be extracted. Specifically, the temperature reference extraction unit 110 sets the range specified by the control parameters as the temperature range to be extracted, using the predicted maximum temperature identified in step S302 as the reference value. For example, if the predicted maximum temperature identified in step S302 is "25 degrees" and the control parameter is "5 degrees," the temperature range to be extracted is "20 degrees to 30 degrees."

[0025] In the next step S304, the temperature reference extraction unit 110 identifies the month to be read. The temperature reference extraction unit 110 may set all months as the month to be read, or may set the month from the month before to the month to which the target calculation date belongs as the month to be read. In the next step S305, the temperature reference extraction unit 110 reads all the temperature records for the month to be read identified in step S304 and identifies the maximum temperature for each day.

[0026] In the next step S306, the temperature reference extraction unit 110 identifies all days whose daily maximum temperatures fall within the temperature range to be extracted, i.e., sample target days, and ends the process shown in Fig. 4. Specifically, if the maximum temperature of a certain day identified in step S305 falls within the temperature range to be extracted identified in step S303, that day is designated as a sample target day.

[0027] (Operation of the adjustment capacity requirement calculation unit 130) The required control capacity calculation unit 130 calculates the required control capacity using the actual residual demand for the sample day extracted by the temperature reference extraction unit 110. The required control capacity in this embodiment is the primary control capacity D1, secondary control capacity (1) D21, secondary control capacity (2) D22, tertiary control capacity (1) D31, and composite contract C. Note that for "secondary control capacity (1)," a circled "1" is typically used instead of the "1" in parentheses. The same applies to secondary control capacity (2) and tertiary control capacity (1). The required control capacity calculation unit 130 calculates each index for each time slot on the sample day using the method described below. In this embodiment, the time slots are three-hour slots starting at 0:00.

[0028] The method for calculating the primary control capacity D1 is as follows: First, the required control capacity calculation unit 130 calculates an evaluation value tD1 using the following Equation 1.

[0029] tD1=MAX(J(1s)-J(10m)) (Formula 1)

[0030] where J(1s) is the measured residual demand every second, and J(10m) is the moving average of J(1s) over 10 minutes. The function MAX is a function that calculates the maximum value in parentheses for the same time period. The required control capacity calculation unit 130 then calculates the primary control capacity D1 by adding a 3-sigma value to the average of the evaluation values ​​for all sample days for the evaluation value tD1 for each time period.

[0031] Figure 5 is a schematic diagram showing how to calculate primary control reserve D1. The upper part of Figure 5 is a time series graph showing one time period on a sample date, specifically from 00:00 to 3:00 on July 1, 2022. The solid line in the upper part of Figure 5 shows the actual residual demand every second, i.e., J(1s) in Equation 1. The dashed line in the upper part of Figure 5 shows the 10-minute moving average of the actual residual demand, i.e., J(10m) in Equation 1. The dashed line in the upper part of Figure 5 shows J(1s)-J(10m). The maximum value of the dashed line in the time period in the upper part of Figure 5 is the evaluation value tD1.

[0032] The lower part of Figure 5 shows a histogram of the evaluation values ​​tD1 for all sample dates. Here, for convenience of drawing, the histogram is simply represented by a curve 901, but in reality, each point constituting the histogram corresponds to the evaluation value for each sample date. For example, the evaluation value calculated using data from 0:00 to 3:00 on July 1, 2022, shown in the upper part of Figure 5, is the single point indicated by the symbol 902. For example, if the temperature reference extraction unit 110 extracts 70 sample dates, the histogram shown in the lower part of Figure 5 will consist of a total of 70 points.

[0033] The required control capacity calculation unit 130 then calculates the average value 903 and standard deviation σ of the evaluation values ​​tD1, and determines the primary control capacity D1 by adding three times the standard deviation σ to the average value 903. Just to be clear, if the evaluation values ​​tD1 are normally distributed, 99.7% of the evaluation values ​​tD1 on all sample days will fall within the range from "D1" to "D1-6σ." As a result of the calculation shown in Figure 5, for example, the primary control capacity D1 for a certain time slot on a certain day in the required control capacity database 206 shown in Figure 3, i.e., the value of one cell in the table shown in Figure 3, is calculated.

[0034] The method for calculating the secondary control capacity (1) D21 is as follows: First, the required control capacity calculation unit 130 calculates the evaluation value tD21 using the following Equation 2.

[0035] tD21=MAX(J(10m)-J(30m)) (Formula 2)

[0036] where J(30m) is the 30-minute moving average of the actual residual demand. The required control capacity calculation unit 130 then calculates the secondary control capacity (1) D21 by adding a 3-sigma value to the average of the evaluation values ​​tD21 for each time period on all sample days. The method shown in the lower part of Figure 5 can be used to calculate the secondary control capacity (1) D21 using each evaluation value tD21.

[0037] The calculation method for secondary control reserve (2) will be explained with reference to Figure 6. Note that Figure 6 shares the same horizontal and vertical axes as the upper part of Figure 5, and the vertical dashed lines represent 30-minute time intervals. In Figure 6, the thin solid line denoted by reference numeral 911 is the measured value of actual excess demand every 30 seconds. In Figure 6, the thick solid line denoted by reference numeral 912 is the 30-minute average value of actual excess demand. This average value is the average value every 30 minutes from midnight and remains constant for 30 minutes. In Figure 6, the dashed line denoted by reference numeral 913 is the value obtained by subtracting the predicted value of renewable energy at the time of GC from the BG demand plan. In Figure 6, the dashed line denoted by reference numeral 914 represents the value obtained by subtracting the value denoted by reference numeral 913 from the value denoted by reference numeral 912 for the same time period. The difference between the values ​​denoted by reference numeral 913 for each 30-minute interval is defined as tD221 to tD225. In this case, the required adjustment capacity calculation unit 130 calculates the evaluation value tD22 using the following Equation 3.

[0038] tD22=MAX(tD221~tD225) (Formula 3)

[0039] The required control capacity calculation unit 130 then calculates the secondary control capacity (2) D22 by adding a 3-sigma value to the average of the evaluation values ​​tD22 for each time slot on all sample days. The method shown in the lower part of Figure 5 can be used to calculate the secondary control capacity (2) D22 using each evaluation value tD22.

[0040] The method for calculating the tertiary control capability (1) D31 is as follows: First, the control capability requirement calculation unit 130 calculates the evaluation value tD31 using the following Equation 4.

[0041] tD31=MAX(J(30m)-J(30s)) (Formula 4)

[0042] where J(30s) is the measured value of the actual residual demand every 30 seconds, and J(30m) is the moving average value of the actual residual demand over 30 minutes. The required control capacity calculation unit 130 then calculates the tertiary control capacity (1)D31 by adding a 3 sigma value to the average of the evaluation values ​​tD31 for each time period on all sample days. The method shown in the lower part of Figure 5 can be used to calculate the tertiary control capacity (1)D31 using each evaluation value tD31.

[0043] The method for calculating the composite contract C is as follows: First, the adjustment capacity requirement calculation unit 130 calculates the evaluation value tC using the following Equation 5.

[0044] tC=MAX(J(1m)-(BG-GC)) (Formula 5)

[0045] Here, J(1m) is the measured value of the actual surplus demand per minute, BG is the GB plan, and GC is the forecast value of renewable energy at the time of GC. Here, the BG plan refers to the amount of power generated over 30 minutes submitted by a balancing group consisting of multiple power generation companies. The forecast value of renewable energy at the time of GC is the amount of renewable energy power generation forecast and planned by a general power transmission and distribution company or a power generation company at the time of GC. The adjustment reserve requirement calculation unit 130 then calculates the composite contract C by adding a 3-sigma value to the average of the evaluation values ​​tC for each time slot on all sample days. The method shown in the lower part of Figure 5 can be used to calculate the composite contract C using each evaluation value tC.

[0046] Fig. 7 is a flowchart showing the processing of the adjustment capacity requirement calculation unit 130. Before the processing shown in Fig. 7 starts, a calculation target day is identified, and a sample target day for calculating the adjustment capacity requirement for that calculation target day is identified by the temperature reference extraction unit 110. The processing shown in Fig. 7 is processing for supporting adjustment capacity procurement for a certain calculation target day. When multiple days are the target days, the processing shown in Fig. 7 is performed for each day. For example, when the calculation target days are seven days, the adjustment capacity requirement calculation unit 130 changes the calculation target day and repeats the processing shown in Fig. 7 seven times.

[0047] First, in step S321, the adjustment capacity requirement calculation unit 130 acquires information about the sample target date calculated by the temperature reference extraction unit 110, and then proceeds to step S322. The sample target date information is information that identifies the sample target date, such as "June 1-8, 12, 15, 20-22, July 5-10, August 1-20." In step S322, the adjustment capacity requirement calculation unit 130 determines the time slots to be calculated, and then proceeds to step S323. The time slots are, for example, time slots every three hours starting from midnight. The order of calculation is arbitrary; for example, when step S322 is executed for the first time, the earliest time slot, i.e., "midnight to 3:00," may be selected and then sequentially changed to later time slots, or vice versa.

[0048] In step S323, the required control capacity calculation unit 130 determines the index to be calculated. Specifically, one of primary control capacity D1, secondary control capacity (1) D21, secondary control capacity (2) D22, tertiary control capacity (1) D31, and composite contract C is selected. When step S323 is executed for the first time, any of these six indexes may be selected; from the second time onwards, an unselected index is selected. In the following step S324, the required control capacity calculation unit 130 calculates an evaluation value for the target time slot for each sample target date. For example, if the index is primary control capacity D1, the processing of step S324 is processing to calculate an evaluation value tD1 as described with reference to the upper part of FIG. 5.

[0049] In the following step S325, the adjustment capacity requirement calculation unit 130 performs statistical processing of the evaluation values ​​for each sample day calculated in step S324, calculates an average value and a 3-sigma value, and calculates an evaluation value, for example, the value of D1. In the following step S326, the adjustment capacity requirement calculation unit 130 determines whether all indicators have been calculated, and if it determines that there are indicators that have not been calculated, it returns to step S323 and calculates the uncalculated indicators. If it determines in step S326 that all indicators have been calculated, the adjustment capacity requirement calculation unit 130 proceeds to step S327.

[0050] In step S327, the required adjustment capacity calculation unit 130 determines whether calculations have been completed for all time periods. If the required adjustment capacity calculation unit 130 determines that there are time periods for which calculations have not been completed, the process returns to step S322 and repeats the processing from step S322 onwards for the time periods for which calculations have not been completed. If the required adjustment capacity calculation unit 130 determines in step S327 that calculations have been completed for all time periods, the process in FIG. 7 ends.

[0051] According to the above-described embodiment, the following effects can be obtained. (1) The adjustment capacity procurement support system 100, which is also a calculation device, includes a temperature reference extraction unit 110 that determines a past sample target date based on the predicted temperature on a calculation target date, which is the target day for calculating the adjustment capacity requirement, and an adjustment capacity requirement calculation unit 130 that calculates the adjustment capacity requirement on the calculation target date based on time-series performance data of the power system 20 on the sample target date. Therefore, the adjustment capacity requirement can be calculated with high accuracy. The effect of this will be described in detail.

[0052] In this embodiment, the sample target date is extracted using the predicted temperature for the calculation target date, thereby extracting the actual residual demand used to calculate the required control capacity for the calculation target date. Because the residual demand is the power demand minus the output from renewable energy, the actual residual demand also changes depending on the magnitude of demand. Furthermore, due to the characteristics of the power grid 20, there is a correlation between temperature and the magnitude of demand. Therefore, by extracting the actual residual demand used to calculate the required control capacity based on the actual and predicted temperatures, the calculation accuracy of the required control capacity can be improved. Specifically, for example, if the predicted maximum temperature for the calculation target date is 20°C, the required control capacity is calculated using the actual residual demand for days with maximum temperatures between 15°C and 25°C, rather than the entire month of the target date. This makes it possible to exclude the actual residual demand for days with significantly different maximum temperatures, even within the target month of the target date, thereby improving the calculation accuracy of the required control capacity.

[0053] (2) As shown in FIG. 4, the temperature reference extraction unit 110 determines the sample target date as a day on which the maximum temperature falls within a predetermined range based on the predicted maximum temperature on the calculation target date.

[0054] (3) The adjustment capacity requirement calculation unit 130 calculates the adjustment capacity requirement on the calculation target date based on the time-series actual data on the sample target date of the residual demand, which is the value obtained by subtracting the output from renewable energy from the power demand.

[0055] (4) The adjustment capacity requirement calculation unit 130 calculates the adjustment capacity requirement for each time period and each sample target day, and calculates the adjustment capacity requirement on the calculation target day by statistically processing the adjustment capacity requirement for all sample target days for each time period.

[0056] (5) The statistical processing performed by the adjustment capacity requirement calculation unit 130 is the calculation of the average value and the 3-sigma value. Therefore, it is possible to calculate the adjustment capacity requirement that covers a sufficiently wide range obtained from past statistics, specifically, a range of 99.7%.

[0057] (Variation 1) In the above-described embodiment, the target month for reading is determined based on a predetermined standard, for example, the month preceding the month to which the target calculation date belongs to, or the month following the month. However, if there are few target sample dates, the number of target months for reading may be increased.

[0058] FIG. 8 is a flowchart showing the processing of the temperature reference extraction unit 110 in Modification 1. However, since the processing up to step S304 is the same as in FIG. 4, some of the description is omitted. Furthermore, the same steps as in FIG. 4 are assigned the same step numbers, and their descriptions are omitted. As shown in FIG. 8, the temperature reference extraction unit 110 in this modification executes step S331 after step S306. In step S331, the temperature reference extraction unit 110 determines whether the number of sample target days identified in step S306 is greater than a predetermined threshold, for example, 50 days. If the temperature reference extraction unit 110 determines that the number of sample target days is greater than the predetermined threshold, it ends the processing shown in FIG. 8. If the temperature reference extraction unit 110 determines that the number of sample target days is less than or equal to the predetermined threshold, it proceeds to step S332.

[0059] In step S332, the temperature reference extraction unit 110 increases the number of target months to be read from the previous month, and returns to step S305. For example, if the target month to be read immediately before executing step S332 was from the month before to the month after the month to which the target calculation date belongs, step S332 changes the target month to be read from the month two months before to the month to which the target calculation date belongs to the month two months after. The loop of steps S305 to S332 is repeated until the number of target sample days becomes greater than the threshold value.

[0060] According to this modification 1, the following effects can be obtained. When there is a small amount of sample data used to calculate the required adjustment capacity, the calculation accuracy decreases, and the required adjustment capacity becomes smaller than the actual amount, which may reduce the stability of supply and demand operations. In this modification, when there is a small amount of sample data, the months to be read are expanded. By increasing the number of sample data used for the required adjustment capacity, the calculation accuracy of the required adjustment capacity can be improved and the stability of supply and demand operations can be maintained.

[0061] For example, if the predicted maximum temperature on the calculation target day is 25 degrees, the days in the reading target month on which the maximum temperature was between 25 degrees and 35 degrees will be the sample target days. If the number of sample target days is below the threshold, the number of sample target days can be increased to above the threshold by reading more months than the initial reading target months. Therefore, by increasing the number of sample data used for the adjustment reserve requirement, the accuracy of calculating the adjustment reserve requirement can be improved and the stability of supply and demand operations can be maintained.

[0062] (Variation 2) In the embodiment described above, the temperature reference extraction unit 110 determines the sample date based on the maximum temperature. However, the temperature reference extraction unit 110 may determine the sample date based on a standard other than the maximum temperature, such as the average temperature or the minimum temperature. In this modification, the processing of steps S302 and S305 in FIG. 4 is mainly changed.

[0063] 4 will be used as an example to explain the differences in the process. In step S302, the average temperature for the calculation target date is identified, and in step S303, the temperature range to be extracted is identified based on this average temperature. In step S305, the average temperature for each day of the reading target month is identified, and in step S306, the days of the reading target month whose average temperature falls within the temperature range to be extracted are identified and used as sample days.

[0064] (Variation 3) In the above-described embodiment, the adjustment capacity requirement calculation unit 130 calculates the 3 sigma value of the evaluation value to calculate the target index. However, the adjustment capacity requirement calculation unit 130 may use a value other than the 3 sigma value to calculate the target index. For example, the adjustment capacity requirement calculation unit 130 may use a 1 sigma value, or may use the 99.87 percentile value as the 3 sigma equivalent value.

[0065] (Variation 4) In the above-described embodiment, the maximum value of the calculated values ​​for each time period and for each time period on the sample target day was used as the evaluation value. However, the average value or the standard deviation σ may be used instead of the maximum value. For example, in the calculation of the primary control reserve D1, the average value of the dashed dotted lines shown at the top of Figure 5 may be changed to the evaluation value tD1. The processing after calculating the evaluation value tD1 is the same as in the embodiment. This change can be applied to all of the secondary control reserve (1) D21, secondary control reserve (2) D22, tertiary control reserve (1) D31, and composite contract C.

[0066] This modification provides the following advantages. (6) The adjustment capacity requirement calculation unit 130 calculates the adjustment capacity requirement on the calculation target day based on the maximum value of the evaluation value of the residual demand for each time slot on the sample target day.

[0067] (Variation 5) In the above-described embodiment, the required control capacity is defined as the primary control capacity D1, the secondary control capacity (1) D21, the secondary control capacity (2) D22, the tertiary control capacity (1) D31, and the composite contract C. However, the required control capacity may include at least one of the above five values, and may further include other values, for example, the tertiary control capacity (2).

[0068] (Variation 6) In the above-described embodiment, the temperature reference extraction unit 110 determines the sample date based on the maximum temperature. However, in addition to the temperature reference extraction unit 110, a weather reference extraction unit 120 may be provided, and the sample date may be determined based on the average amount of solar radiation in addition to the maximum temperature.

[0069] 9 is a hardware configuration diagram of an adjustment capability procurement support system 100A in Modification 6. As shown in FIG. 9, the adjustment capability procurement support system 100A in this modification newly includes a verification range database 205A, a weather record database 207, and a weather forecast database 208.

[0070] (Functional configuration of the adjustment capability procurement support system 100A) 10 is a functional configuration diagram of the adjustment capability procurement support system 100A in Modification 6. In FIG. 2, the adjustment capability procurement support system 100A newly includes a weather record database 207 and a weather forecast database 208. The adjustment capability procurement support system 100A also newly includes a meteorological criterion extraction unit 120. The meteorological criterion extraction unit 120 is realized by the processor 104 executing a calculation program read from the program database 201 into the memory 105. The meteorological criterion extraction unit 120 obtains data required for each calculation from the respective databases via the communication bus 106.

[0071] (Database) In addition to the control parameters used by the temperature criterion extraction unit 110, the control parameters used by the meteorological criterion extraction unit 120 are stored in the inspection range database 205A.

[0072] The weather record database 207 stores, as time-series data, weather measured in the past (hereinafter referred to as "weather record") in the target area for which the control capacity procurement support system 100 calculates control capacity, i.e., the target area described above. The weather forecast database 208 stores, as time-series data, predicted future weather in the target area. Here, weather data refers to, for example, data such as the amount of solar radiation and wind conditions in the target area. The time-series data in the weather record database 207 and the weather forecast database 208 are values ​​measured every 30 seconds, for example. However, the time intervals of the data stored in each database do not have to match.

[0073] (Operation of the meteorological criterion extraction unit 120) Fig. 11 is a flowchart showing the processing of the meteorological criterion extraction unit 120. The processing shown in Fig. 11 is processing for supporting adjustment reserve procurement for a single calculation target day. When multiple days are the target days, the processing shown in Fig. 11 is performed for each day. For example, when the calculation target days are seven days, the meteorological criterion extraction unit 120 changes the calculation target day and repeats the processing shown in Fig. 11 seven times. In step S341, the meteorological criterion extraction unit 120 identifies the calculation target day. In the following step S342, the meteorological criterion extraction unit 120 reads the solar radiation for the calculation target day from the weather record database 207 and identifies the average value for that day, i.e., the expected average solar radiation.

[0074] In the next step S343, the meteorological criterion extraction unit 120 reads the control parameters from the test range database 205 and identifies the extraction target meteorological range. Specifically, the meteorological criterion extraction unit 120 sets the range specified by the control parameters as the extraction target meteorological range, using the expected average solar radiation identified in step S342 as the reference value. For example, if the expected average solar radiation identified in step S342 is "1000 W / m2" and the control parameter is "100 W / m2," the extraction target meteorological range will be "900 W / m2 to 1100 W / m2."

[0075] In the following step S344, the meteorological criterion extraction unit 120 identifies as the calculation target date the sample target date identified by the temperature criterion extraction unit 110. In the following step S305, the meteorological criterion extraction unit 120 reads all of the weather records for the read calculation target date identified in step S345 and identifies the average solar radiation amount for each day.

[0076] In the next step S346, the meteorological criterion extraction unit 120 identifies all days for which the daily average solar radiation falls within the extraction target weather range, i.e., sample target days, and ends the process shown in Fig. 11. Specifically, if the average solar radiation for a certain day identified in step S346 falls within the extraction target weather range identified in step S343, that day is designated as the sample target day.

[0077] This modification provides the following advantages. (7) As shown in Fig. 11, the meteorological criterion extraction unit 120 determines the sample target date as a day on which the average solar radiation falls within a predetermined range, based on the predicted average solar radiation on the calculation target date. Therefore, the sample target date is determined to be a day on which not only the temperature but also the weather conditions are similar, thereby improving the calculation accuracy of the required amount of regulation power.

[0078] In this modification, the temperature reference extraction unit 110 first tentatively determines the sample date, and then the meteorological reference extraction unit 120 determines a day that matches the conditions from the tentatively determined sample date as the sample date to be processed by the required regulation capacity calculation unit 130. However, the order may be reversed. That is, the meteorological reference extraction unit 120 may tentatively determine a sample date for each day of the reading month, and then the temperature reference extraction unit 110 may determine a day that matches the conditions from the tentatively determined sample date as the sample date. Alternatively, the temperature reference extraction unit 110 and the meteorological reference extraction unit 120 may independently determine the sample date, and then the logical product of the sample dates determined by both units may be determined as the sample date to be processed by the required regulation capacity calculation unit 130.

[0079] Furthermore, when the meteorological criteria extraction unit 120 tentatively determines or determines sample target dates for each day of the target month for reading, if the number of tentatively determined or determined days falls below a predetermined threshold, the number of target months for reading may be increased.

[0080] In the above-described modified example, the meteorological criterion extraction unit 120 determines the sample date based on the average solar radiation. However, the meteorological criterion extraction unit 120 may determine the sample date based on meteorological data other than the average solar radiation, such as the maximum solar radiation or the average wind speed. In this case, the process of steps S342 and S345 in FIG. 11 will be mainly changed.

[0081] In each of the above-described embodiments and modifications, the functional block configurations are merely examples. Some functional configurations shown as separate functional blocks may be configured as an integrated unit, or a configuration shown in a single functional block diagram may be divided into two or more functions. Furthermore, some of the functions of each functional block may be provided by other functional blocks.

[0082] The coordination capability procurement support system 100 may read a program from another device via the communication unit 103 or a medium reading device (not shown). Here, the medium refers to, for example, a storage medium that can be attached to or detached from an input / output interface, or a communication medium, i.e., a wired, wireless, or optical network, or a carrier wave or digital signal that propagates through the network. In addition, some or all of the functions realized by the program may be realized by a hardware circuit or FPGA.

[0083] The above-described embodiments and modifications may be combined with each other. Although various embodiments and modifications have been described above, the present invention is not limited to these. Other embodiments conceivable within the scope of the technical concept of the present invention are also included within the scope of the present invention. [Explanation of symbols]

[0084] 100, 100A: Adjustment power procurement support system 110: Temperature reference extraction part 120: Weather standard extraction unit 130: Required adjustment force calculation section 201: Program Database 202: Residual demand performance database 203: Temperature record database 204: Temperature forecast database 205, 205A: Test range database 206: Database of required adjustment capacity

Claims

1. a temperature reference extraction unit that determines a past sample target date based on the predicted temperature on a calculation target date that is a target date for calculating the required amount of regulation power; a required adjustment capacity calculation unit that calculates the required adjustment capacity on the calculation target date based on time-series performance data of the power system on the sample target date, The adjustment capacity requirement calculation unit calculates the adjustment capacity requirement on the calculation target day based on the maximum value for each time period on the sample target day of an evaluation value of residual demand, which is the value obtained by subtracting the output from renewable energy from the power demand.

2. 2. The computing device according to claim 1, a weather criterion extraction unit that determines a past sample target date based on the forecast weather on the calculation target date; The required adjustment capacity calculation unit sets the sample target day to the day determined by the temperature reference extraction unit and the weather reference extraction unit.

3. 2. The computing device according to claim 1, The temperature reference extraction unit is a computing device that determines, as the sample target date, a day on which the maximum temperature is within a predetermined range based on the predicted maximum temperature on the calculation target date.

4. 3. The computing device according to claim 2, The meteorological criterion extraction unit determines, as the sample target date, a day on which the average solar radiation amount falls within a predetermined range based on the predicted average solar radiation amount on the calculation target date.

5. 2. The computing device according to claim 1, The adjustment capacity requirement calculation unit calculates the adjustment capacity requirement for each time period and for each sample target day, and calculates the adjustment capacity requirement on the calculation target day by statistically processing the adjustment capacity requirement for all the sample target days for each time period.

6. 6. The computing device according to claim 5, The statistical processing is calculation of an average value, a 3 sigma value, or a 98.87 percentile value.

7. 2. The computing device according to claim 1, the temperature reference extraction unit determines, as the sample target date, a day included in a month of a first range, which is a predetermined range based on the month to which the calculation target date belongs, and on which the maximum temperature is within a predetermined range from the predicted maximum temperature of the calculation target date; When the number of sample target days is less than a predetermined threshold, the temperature standard extraction unit selects as the sample target days days that are included in a second range that is wider than the first range and whose maximum temperature is within a predetermined range from the predicted maximum temperature of the calculation target day.

8. 3. The computing device according to claim 2, the meteorological criterion extraction unit determines the sample target day as a day included in a first range of months, which is a predetermined range based on the month to which the calculation target day belongs, and on which the average solar radiation amount is within a predetermined range from the predicted average solar radiation amount for the calculation target day; When the number of sample target days is less than a predetermined threshold, the meteorological standard extraction unit determines as the sample target day a day that is included in a second range that is wider than the first range and whose average solar radiation is within a predetermined range from the predicted average solar radiation for the calculation target day.

9. A method for calculating a required amount of adjustment power executed by a calculation device, a determination process for determining a past sample target date based on the predicted temperature on the calculation target date, which is the target day for calculating the required adjustment capacity; a calculation process for calculating the required adjustment capacity on the calculation target date based on time-series performance data of the power system on the sample target date, The calculation process includes calculating the required adjustment capacity on the calculation target day based on the maximum value for each time period on the sample target day of an evaluation value of residual demand, which is the value obtained by subtracting output from renewable energy from electricity demand.

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