JP2018018329A - Power amount prediction program, power amount prediction device and power amount prediction method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To determine a prediction error of a power generation amount.SOLUTION: A power amount prediction device 100 generates a boundary value 143 on the basis of a prediction amount of solar radiation in weather prediction/actual past data 141 and an actual amount of solar radiation. The power amount prediction device 100 estimates if a prediction error of the amount of solar radiation swings to an increase direction or a decrease direction by comparing a clearness index of an object date with the boundary value 143. The power amount prediction device 100 specifies a prediction error of the amount of solar radiation, which satisfies a guarantee probability in the estimated direction, and determines a prediction error of a power generation amount.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a power amount prediction program and the like.

  As a result of the fact that photovoltaic power generation (PV: Photovoltaics) and battery power supply became possible, it is possible to control the power cost related to power supply according to the amount of PV power generation and the amount of battery discharge. Both are required.

  Here, the amount of solar radiation changes depending on the weather, and the amount of PV power generated changes depending on the amount of solar radiation. Therefore, when the power supply is predicted, the prediction is performed in consideration of the weather. For example, as a conventional technique, assuming that the probability of occurrence of solar radiation predicted based on past weather information (or prediction error of solar radiation) follows a normal distribution, specify the amount of solar radiation that satisfies a predetermined guarantee probability There is a technology for estimating the amount of power generation.

FIG. 12 is a diagram for explaining the prior art. The horizontal axis in FIG. 12 indicates the amount of solar radiation, and the vertical axis indicates the occurrence probability. For example, if the guarantee probability to 90%, in the prior art, the amount of solar radiation on the assumption that x _0, estimate the power generation amount of PV.

JP 2006-304402 A

  However, the above-described conventional technology has a problem that it is impossible to obtain a power generation amount prediction error.

  In the above-described prior art, a normal distribution is assumed as the distribution of the probability of occurrence of solar radiation, but in reality, the distribution of the probability of occurrence of solar radiation is not a normal distribution. For this reason, similarly, the distribution of the prediction error of the solar radiation amount is not a normal distribution.

  FIG. 13 is a diagram for explaining a problem of the conventional technique. In FIG. 13, the horizontal axis indicates the clear sky index, and the vertical axis indicates the occurrence probability. The clear sky index is a value obtained by dividing the horizontal solar radiation amount by the atmospheric solar radiation amount. The circles in FIG. 13 indicate the relationship between the clear sky index and the occurrence probability when there is no sunshine, and correspond to the relationship between the clear sky index and the occurrence probability when it is cloudy or rainy. The diamond mark indicates the relationship between the clear sky index and the occurrence probability when there is sunshine, and corresponds to the relationship between the clear sky index and the occurrence probability when the sky is clear. The distribution of circles and the distribution of diamonds are very different from the symmetrical normal distribution. The square marks indicate the relationship between the overall clear sky index and the probability of occurrence when there is no sunshine and when there is sunshine.

  As shown in FIG. 13, the clear sky index in the case of cloudy or rain has a high probability of occurrence near 0, and the clear sky index in the case of clear weather has a high probability of occurrence near the solar radiation amount outside the atmosphere.

  Here, if the forecast of cloudy or rain is off and clear, the expected amount of solar radiation may increase, but it will rarely decrease. In contrast, the fluctuation width in the decreasing direction is almost zero, while the fluctuation width in the increasing direction is a certain amount.

  On the other hand, if the forecast of clear weather is not met and it becomes cloudy or rainy, the expected amount of solar radiation may decrease but not increase. For this reason, the prediction error of the sunny solar radiation amount has a constant amount of fluctuation in the decreasing direction, while the fluctuation amount in the increasing direction is almost zero.

  In the prior art, the distribution of solar radiation prediction errors is assumed to be a normal distribution. For this reason, for example, when predicting sunny solar radiation, it is not necessary to consider when forecasting errors in an increasing direction that do not need to be considered, or when predicting cloudy or rainy solar radiation. In some cases, the prediction error in the decreasing direction was taken into consideration.

  In one aspect, an object of the present invention is to provide a power amount prediction program, a power amount prediction apparatus, and a power amount prediction method capable of obtaining a power generation amount prediction error.

  In the first plan, the computer executes the following processing. The computer performs the following processing based on the predicted solar radiation amount predicted at the prediction target point and date and the actually measured solar radiation amount at the prediction target point and date and time. The computer generates prediction error information that specifies whether the prediction error of the predicted solar radiation amount with respect to the actually measured solar radiation amount is in an increasing direction or a decreasing direction for each weather prediction. The computer calculates a power generation amount generated by the solar power generation device and a power generation amount prediction error based on the prediction error information, the solar radiation amount prediction information, and the solar power generation device information.

  The prediction error of the power generation amount can be obtained.

FIG. 1 is a functional block diagram illustrating a configuration of the power amount prediction apparatus according to the present embodiment. FIG. 2 is a diagram illustrating an example of a data structure of weather prediction / actual past data. FIG. 3 is a diagram illustrating an example of a data structure of weather prediction data. FIG. 4 is a diagram illustrating an example of the first frequency distribution data. FIG. 5 is a diagram illustrating an example of the second frequency distribution data. FIG. 6 is a diagram (1) for explaining the process of the limit solar radiation amount calculation unit. FIG. 7 is a diagram (2) for explaining the processing of the limit solar radiation amount calculation unit. FIG. 8 is a diagram for explaining the processing of the charge / discharge plan optimization unit. FIG. 9 is a flowchart illustrating a processing procedure in which the power amount prediction apparatus generates boundary values and frequency distribution data. FIG. 10 is a flowchart illustrating a processing procedure in which the power amount prediction apparatus calculates a charge / discharge plan. FIG. 11 is a diagram illustrating an example of a hardware configuration that executes the power amount prediction program. FIG. 12 is a diagram for explaining the prior art. FIG. 13 is a diagram for explaining a problem of the conventional technique.

  Hereinafter, embodiments of a power amount prediction program, a power amount prediction apparatus, and a power amount prediction method disclosed in the present application will be described in detail with reference to the drawings. Note that the present invention is not limited to the embodiments.

  FIG. 1 is a functional block diagram illustrating a configuration of the power amount prediction apparatus according to the present embodiment. As illustrated in FIG. 1, the power amount prediction apparatus 100 includes a communication unit 110, an input unit 120, a display unit 130, a storage unit 140, and a control unit 150.

  The communication unit 110 is a processing unit that performs data communication with an external server or the like via a network. For example, the power amount prediction apparatus 100 may communicate with an external server using the communication unit 110 to acquire weather prediction / actual past data 141, weather prediction data 144, and the like, which will be described later.

  The input unit 120 is an input device for inputting various types of information to the power amount prediction device 100. The input unit 120 corresponds to a keyboard, a mouse, a touch panel, or the like.

  The display unit 130 is a display device that displays information output from the control unit 150. The display unit 130 corresponds to a liquid crystal display, a touch panel, or the like.

  The storage unit 140 includes weather prediction / result past data 141, frequency distribution data 142, boundary values 143, weather prediction data 144, and power generation equipment data 145. The storage unit 140 corresponds to, for example, a semiconductor memory device such as a random access memory (RAM), a read only memory (ROM), or a flash memory, or a storage device such as a hard disk or an optical disk.

  The weather prediction / actual past data 141 is a table that holds information on the weather forecast for the past date and time predicted in the past and the past weather results. FIG. 2 is a diagram illustrating an example of a data structure of weather prediction / actual past data. As shown in FIG. 2, the weather prediction / actual past data 141 associates date / time, longitude / latitude, weather, predicted solar radiation amount, and actual solar radiation amount.

  The date and time of the weather prediction / result past data 141 indicates a date and time that is earlier than the current date and time. The longitude and latitude correspond to the position where the solar radiation amount is predicted and the position where the solar radiation amount is observed. The weather indicates, for example, sunny, cloudy or rainy. The predicted amount of solar radiation is the amount of solar radiation predicted at the relevant date and time, longitude and latitude. The actually measured amount of solar radiation is an actually measured value of the amount of solar radiation actually measured at the corresponding date and time, longitude and latitude.

  The frequency distribution data 142 is information indicating the relationship between the clear sky index error and the frequency. A specific description regarding the frequency distribution data 142 will be described later.

  The boundary value 143 indicates a clear sky index that is a boundary between a clear sky index in which the direction of the prediction error is a direction in which the amount of solar radiation increases and a clear sky error in which the direction of the prediction error is a direction in which the amount of solar radiation decreases.

  The weather prediction data 144 is a table that holds information related to the weather that is predicted at a date earlier than the current date. FIG. 3 is a diagram illustrating an example of a data structure of weather prediction data. As shown in FIG. 3, the weather prediction data 144 associates date and time, longitude / latitude, weather, and predicted amount of solar radiation.

  The date / time of the weather prediction data 144 indicates a date / time ahead of the current date / time. The longitude / latitude indicates the position for which the amount of solar radiation is to be predicted. The weather indicates the predicted weather. The predicted amount of solar radiation is the amount of solar radiation predicted at the relevant date and time, longitude and latitude.

  The power generation device data 145 is information that defines the amount of solar radiation and the amount of power generated by the solar power generation device based on the amount of solar radiation.

  The control unit 150 includes a collection unit 151, a generation unit 152, and a calculation unit 153. The control unit 150 corresponds to an integrated device such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA). Moreover, the control part 150 respond | corresponds to electronic circuits, such as CPU and MPU (Micro Processing Unit), for example.

  The collection unit 151 is a processing unit that accesses an external server or the like via a network and collects the weather prediction / actual past data 141 and the weather prediction data 144. The user may input the weather prediction / actual past data 141 and the weather prediction data 144 to the power amount prediction apparatus 100 by operating the input unit 120. In this case, the collection unit 151 collects the weather prediction / actual past data 141 and the weather prediction data 144 from the input unit 120. The collection unit 151 stores the weather prediction / result past data 141 and the weather prediction data 144 in the storage unit 140.

  The generation unit 152 is a processing unit that generates the boundary value 143 and the frequency distribution data 142 based on the predicted solar radiation amount and the actual solar radiation amount stored in the weather prediction / actual past data 144. Hereinafter, a process in which the generation unit 152 generates the boundary value 143 and a process of generating the frequency distribution data 142 will be described.

  An example of processing in which the generation unit 152 generates the boundary value 143 will be described. The generation unit 152 selects an unselected record of the weather prediction / actual past data 144, acquires the predicted solar radiation amount from the selected record, and calculates the first clear sky index. The first clear sky index is calculated by equation (1). In equation (1), the solar radiation amount outside the atmosphere is the amount of solar radiation reaching outside the atmosphere. For example, the generation unit 152 acquires in advance information on the amount of solar radiation outside the atmosphere from an external server or the like.

  1st clear sky index = predicted amount of solar radiation / amount of solar radiation outside the atmosphere (1)

  The generation unit 152 compares the measured solar radiation amount included in the selected record with the predicted solar radiation amount, and determines whether the prediction error of the predicted solar radiation amount with respect to the actual solar radiation amount is increasing or decreasing. To do. The generation unit 152 associates the identified direction of the prediction error with the first clear sky index calculated by Expression (1). The generation unit 152 selects an unselected record, repeatedly executes the process of associating the direction of the prediction error with the first clear sky index, and specifies the first clear sky index at which the direction of the prediction error is switched as the boundary value 143. The generation unit 152 stores the boundary value 143 in the storage unit 140.

  In the above processing, the example in which the boundary value 143 is obtained without fixing the longitude / latitude is shown. However, the boundary value 143 may be obtained for each longitude / latitude by fixing the longitude / latitude. In this case, the generation unit 152 compares the measured solar radiation amount and the predicted solar radiation amount corresponding to a certain same longitude and latitude, and specifies whether the direction is an increasing direction or a decreasing direction.

  Next, an example of processing in which the generation unit 152 generates the frequency distribution data 142 will be described. The generation unit 152 selects an unselected record of the weather prediction / actual past data 144, selects a predicted solar radiation amount and an actual solar radiation amount from the selected record, and calculates a clear sky index error based on the selected information. To do. The clear sky index error is calculated by equation (2). The second clear sky index included in Equation (2) is calculated by Equation (3).

  Clear weather index error = 2nd clear sky index-1st clear sky index (2)

  2nd clear sky index = actual solar radiation amount / outside air solar radiation amount (3)

  The generation unit 152 selects an unselected record, repeatedly executes a process of calculating a clear sky index error, and generates frequency distribution data 142 in which the clear sky index error is associated with the appearance frequency of the clear sky index error. The generation unit 152 generates the first frequency distribution data 142a when the clear sky index error is negative, and the second frequency distribution data 142b when the clear sky index error is positive. The frequency distribution data 142 is data including first frequency distribution data 142a and second frequency distribution data 142b.

  FIG. 4 is a diagram illustrating an example of the first frequency distribution data. As shown in FIG. 4, the vertical axis of the first frequency distribution data 142a indicates the appearance frequency, and the horizontal axis corresponds to the clear sky index error. On the horizontal axis of the first frequency distribution data 142a, the clear sky index prediction error changes in a decreasing direction from the right side to the left side.

  FIG. 5 is a diagram illustrating an example of the second frequency distribution data. The vertical axis of the second frequency distribution data 142b indicates the appearance frequency, and the horizontal axis corresponds to the clear sky index error. On the horizontal axis of the second frequency distribution data 142b, the clear sky index prediction error changes in the increasing direction from the left to the right.

  In the above process, the first frequency distribution data 142a and the second frequency distribution data 142b are obtained without fixing the longitude / latitude. However, the longitude / latitude is fixed and the first frequency distribution data 142a and the second frequency distribution data 142b are fixed. The first frequency distribution data 142a and the second frequency distribution data 142b may be obtained.

  Returning to the description of FIG. The calculation unit 153 is a processing unit that calculates a power generation amount generated by the photovoltaic power generation apparatus and a prediction error of the power generation amount based on the pieces of information 141 to 145 stored in the storage unit 140. The calculation unit 153 includes an error direction determination unit 154, a limit solar radiation amount calculation unit 155, a power cost risk direction estimation unit 156, and a charge / discharge plan optimization unit 157.

  The error direction determination unit 154 is a processing unit that determines whether the direction of the prediction error of the solar radiation amount is an increasing direction or a decreasing direction. The error direction determination unit 154 outputs the determination result to the limit solar radiation amount calculation unit 155 and the power cost risk direction estimation unit 156.

  The error direction determination unit 154 specifies the date / time and the longitude / latitude to be predicted, and acquires the predicted date / time and the predicted solar radiation amount of the longitude / latitude from the weather prediction data 144. In the following description, the date / time and longitude / latitude to be predicted are appropriately described as the target date / time. The error direction determination unit 154 calculates the first clear sky index of the target date and time based on the predicted solar radiation amount acquired from the weather prediction table 144 and the formula (1).

  The error direction determination unit 154 compares the first clear sky index and the boundary value 143. If the first clear sky index is larger than the boundary value 143, the direction of the prediction error of the solar radiation amount at the target date and time is in the decreasing direction. It is determined that On the other hand, the error direction determination unit 154 compares the first clear sky index and the boundary value 143. If the first clear sky index is not larger than the boundary value 143, the direction of the prediction error of the solar radiation amount at the target date and time is It is determined that the direction is increasing.

The limit solar radiation amount calculation unit 155 is a processing unit that calculates the limit solar radiation amount. The marginal solar radiation amount calculation unit 155 calculates a clear sky index based on the direction of the prediction error of the solar radiation amount determined by the error direction determination unit 154 before the critical solar radiation amount is calculated, so that the cumulative probability is equal to the guaranteed probability in the prediction error direction. to calculate the error _{y 0.} It is assumed that the guarantee probability is instructed in advance by the user.

6 and 7 are diagrams for explaining the processing of the limit solar radiation amount calculation unit. The process of the limit solar radiation amount calculation unit 155 when it is determined that the direction of the prediction error of the solar radiation amount is the decreasing direction will be described. As shown in FIG. 6, the limit solar radiation amount calculation unit 155, on the first frequency distribution data 142a, it sets the sunny index error _{y 0.} The limit solar radiation amount calculation unit 155 adjusts the clear sky index error y ₀ so that the cumulative probability calculated based on the equation (4) is equal to the guarantee probability. In Expression (4), the first region is a region surrounded by the vertical axis 10a, the horizontal axis 10b, and the line 10c. The second region is a region surrounded by the vertical axis 10a, the horizontal axis 10b, the line 10c, and the line 10d.

  Cumulative probability = area of second region / area of first region × 100 (%) (4)

The process of the limit solar radiation amount calculation unit 155 when it is determined that the direction of the prediction error of the solar radiation amount is the increasing direction will be described. As shown in FIG. 7, the limit solar radiation amount calculation unit 155, on the second frequency distribution data 142b, it sets the sunny index error _{y 0.} The limit solar radiation amount calculation unit 155 adjusts the clear sky index error y ₀ so that the cumulative probability calculated based on the equation (5) becomes equal to the guarantee probability. In Expression (5), the third region is a region surrounded by the vertical axis 20a, the horizontal axis 20b, and the line 20c. The fourth region is a region surrounded by the vertical axis 20a, the horizontal axis 20b, the line 20c, and the line 20d.

  Cumulative probability = Area of the fourth region / Area of the third region × 100 (%) (5)

The limit solar radiation amount calculation unit 155 calculates the third clear sky index based on the equation (6) after obtaining the clear sky index error y _{0 in} which the cumulative probability is equal to the guaranteed probability. The third clear sky index corresponds to a clear sky index whose cumulative probability is equal to the guaranteed probability.

3rd clear sky index = 1st clear sky index + clear sky index error y ₀ (6)

  The limit solar radiation amount calculation unit 155 calculates the limit solar radiation amount based on the equation (7). The marginal solar radiation amount is an expected solar radiation amount that satisfies the guarantee probability.

  Marginal solar radiation amount = 3rd clear sky index x solar radiation amount outside the atmosphere ... (7)

  The limit solar radiation amount calculation unit 155 calculates the limit solar radiation amount for each date and time related to a certain longitude and latitude by repeatedly executing the above processing while fixing the longitude and latitude and changing the date and time. The limit solar radiation amount calculation unit 155 outputs information on the limit solar radiation amount for each date and time related to a certain longitude / latitude to the charge / discharge plan optimization unit 157. For example, a certain longitude / latitude corresponds to a position where a photovoltaic power generation device is installed.

  The power cost risk direction estimation unit 156 is a processing unit that estimates whether the power cost increases or decreases based on the determination result of the error direction determination unit 154. The power cost risk direction estimation unit 156 outputs the estimation result to the charge / discharge plan optimization unit 157.

  The power cost risk direction estimation unit 156 estimates that the power cost is in a decreasing direction when the direction of the solar radiation amount prediction error is an increasing direction. When the amount of solar radiation forecast error increases, it means that the amount of power generated by solar power generation equipment increases.If the amount of power generation increases, the amount of power purchased from the power company decreases, so the power cost decrease.

  On the other hand, the power cost risk direction estimation unit 156 estimates that the power cost increases when the direction of the prediction error of the solar radiation amount decreases. When the amount of solar radiation forecast error is decreasing, this means that the amount of power generated by solar power generation equipment will decrease.If the amount of power generation decreases, the amount of power purchased from the power company will increase. Increase.

  The charge / discharge plan optimization unit 157 calculates the power generation amount generated by the solar power generation device at the target date and time based on the limit solar radiation amount and the power generation device data 145. Note that, as described above, the limit solar radiation amount is the solar radiation amount that takes into account the prediction error of the solar radiation amount. Therefore, the power generation amount calculated by the charge / discharge plan optimization unit 157 includes the prediction error of the power generation amount. Become. The charge / discharge plan optimization unit 157 calculates the amount of power generated by the solar power generation device at each target date and time.

  The charge / discharge plan optimization unit 157 calculates, using linear programming, the storage battery discharge amount that maximizes the peak power reduction using the power demand amount and the power generation amount at each target date and time. For example, the charge / discharge amount of the storage battery at each time when the peak power reduction is the maximum is the charge / discharge plan.

  FIG. 8 is a diagram for explaining the processing of the charge / discharge plan optimization unit. The horizontal axis in FIG. 8 corresponds to time, and the vertical axis corresponds to power. In the example shown in FIG. 8, the value obtained by subtracting d2 from d1 corresponds to the peak power to be reduced.

  In FIG. 8, D corresponds to the power demand at each time (target date and time). M corresponds to the power generation amount in the solar power generation device at each time. X corresponds to the battery charge / discharge amount at each time. The storage battery capacity is A, and the storage battery initial charge is B. At this time, the charge / discharge plan that maximizes the peak power reduction is obtained by solving the linear programming problem of Equation (8). Information on D, A, and B is specified in advance.

  Z included in the equation (8) is an upper limit of the power value obtained by reducing the demand power by the power generation amount and the battery discharge, and the solution minZ of the linear programming problem is the minimum peak power. The constraint conditions related to A and B in the latter half of the problem mean that the charge amount of the storage battery does not fall below the capacity.

  The charge / discharge plan optimization unit 157 calculates a charge / discharge plan that maximizes the peak power reduction. Then, the charge / discharge plan optimization unit 157 associates and outputs the calculation result of the charge / discharge plan and the estimation result of the power cost risk direction estimation unit 156. The charge / discharge plan optimization unit 157 may output to the display unit 130 or may output to another terminal device via a network.

  For example, when the power cost risk direction estimation unit 156 estimates that the power cost is decreasing, the power cost corresponding to the calculated charge / discharge plan is the upper limit of the power cost.

  On the other hand, when the power cost risk direction estimation unit 156 estimates that the power cost is increasing, the power cost corresponding to the calculated charge / discharge plan is the lower limit of the power cost.

  Next, an example of a processing procedure of the power amount prediction apparatus according to the present embodiment will be described. FIG. 9 is a flowchart illustrating a processing procedure in which the power amount prediction apparatus generates boundary values and frequency distribution data. As illustrated in FIG. 9, the generation unit 152 of the power amount prediction apparatus 100 refers to the weather prediction / result past data 141, and based on the past predicted solar radiation amount and the outdoor solar radiation amount, An index is calculated (step S101).

  The generation unit 152 calculates a plurality of second clear sky indexes based on the past actually measured solar radiation amount and the atmospheric solar radiation amount (step S102). The generation unit 152 calculates the boundary value 143 from the relationship between the first clear sky index and the second clear sky index at the same date and time in the past (step S103).

  The generation unit 152 calculates a clear sky index error based on the difference between the first clear sky index and the second clear sky index at the same date and time in the past (step S104). The generating unit 152 generates the frequency distribution data 142 of the clear sky index error (step S105).

  FIG. 10 is a flowchart illustrating a processing procedure in which the power amount prediction apparatus calculates a charge / discharge plan. As illustrated in FIG. 10, the calculation unit 153 of the power amount prediction apparatus 100 calculates the first clear sky index at the target date and time based on the predicted solar radiation amount and the atmospheric solar radiation amount at the target date and time (step S201). The calculation unit 153 determines whether or not the first clear sky index is larger than the boundary value 143 (step S202).

  When the first clear sky index is not larger than the boundary value 143 (No at Step S202), the calculation unit 153 estimates the error direction as “a direction in which the amount of solar radiation increases” (Step S203), and proceeds to Step S205. . On the other hand, when the first clear sky index is larger than the boundary value 143 (step S202, Yes), the error direction is estimated as “a direction in which the amount of solar radiation decreases” (step S204), and the process proceeds to step S205.

The calculation unit 153 selects the frequency distribution data 142 in accordance with the estimated error direction, and specifies the clear sky index error y _{0 in} which the cumulative probability is equal to the guaranteed probability (step S205). For example, in step S205, when the error direction is the decreasing direction, the calculating unit 153 selects the first frequency distribution data 142a, identifies the sunny index error _{y 0.} If the error direction is the increasing direction, the calculating unit 153 selects the second frequency distribution data 142b, identifies a sunny index error y _0.

Calculating unit 153, by adding the clear sky index error y ₀ in the first sunny index of the target date, and calculates a third sunny index (step S206). The calculating unit 153 calculates the limit solar radiation amount by multiplying the third clear sky index and the atmospheric solar radiation amount (step S207). The calculation unit 153 estimates whether the power cost increases or decreases based on the estimated error direction (step S208). The calculation unit 153 generates a charge / discharge plan (step S209).

  Next, the effect of the power amount prediction apparatus 100 according to the present embodiment will be described. The power amount prediction apparatus 100 generates the boundary value 143 based on the predicted solar radiation amount and the actual solar radiation amount of the weather prediction / actual past data 141. And the electric energy prediction apparatus 100 estimates whether the prediction error of the amount of solar radiation fluctuates in an increasing direction or a decreasing direction by comparing the clear sky index of the target date and time with the boundary value 143. The power amount prediction apparatus 100 determines a prediction error of the amount of solar radiation that satisfies the guarantee probability based on the estimated direction, and calculates a power generation amount, thereby obtaining a power generation amount prediction error without using an error distribution assumption based on a normal distribution. be able to.

  The power amount prediction apparatus 100 repeatedly executes a process of associating the direction of the prediction error with the first clear sky index based on the weather prediction / actual past data 141, and the first clear sky index in which the direction of the prediction error is switched to the boundary. It is specified as a value 143. For this reason, it is possible to accurately estimate the direction of the prediction error using the optimum boundary value.

  In the prior art, when generating a charge / discharge plan that satisfies the guarantee probability, if a normal prediction error distribution is used, the charge / discharge plan is generated for both the direction in which the prediction error increases and the direction in which the prediction error decreases. The calculation cost was high. On the other hand, in the electric energy prediction apparatus 100, the direction of the prediction error is determined to one side, and a charge / discharge plan may be generated for the determined direction. can do.

  By the way, in the said Example, it was estimated by the comparison with the clear sky index | exponent of the object date and time, and the boundary value 143, whether the prediction error of the solar radiation amount fluctuated in the increase direction or the decrease direction, but based on the weather of the object date The estimation may be performed. For example, the error direction determination unit 154 of the power amount prediction apparatus 100 determines that the direction of the prediction error of the amount of solar radiation at the target date / time is “decreasing direction” when the weather at the target date / time is “sunny”. On the other hand, when the weather at the target date / time is “cloudy / rainy”, the error direction determination unit 154 determines that the direction of the prediction error of the amount of solar radiation at the target date / time is “increase direction”. In this way, by calculating the direction of the prediction error based on the weather instead of comparing with the boundary value, the processing can be simplified and the processing load can be reduced.

  Next, an example of a hardware configuration that executes a power amount prediction program that realizes the same function as that of the power amount prediction apparatus 100 described in the above embodiment will be described. FIG. 11 is a diagram illustrating an example of a hardware configuration that executes the power amount prediction program.

  As illustrated in FIG. 11, the computer 200 includes a CPU 201 that executes various arithmetic processes, an input device 202 that receives input of data from a user, and a display 203. The computer 200 also includes a reading device 204 that reads programs and the like from a storage medium, and an interface device 205 that exchanges data with other computers via a network. The computer 200 also includes a RAM 206 that temporarily stores various information and a hard disk device 207. The devices 201 to 207 are connected to the bus 208.

  The hard disk device 207 has a generation program 207a and a calculation program 207b. The CPU 201 reads the generation program 207 a and the calculation program 207 b and expands them in the RAM 206.

  The generation program 207a functions as a generation process 206a. The calculation program 207b functions as a calculation process 206b.

  For example, the process of the generation process 206 a corresponds to the process of the generation unit 152. The process of the calculation process 206b corresponds to the process of the calculation unit 153.

  Note that the generation program 207a and the calculation program 207b are not necessarily stored in the hard disk device 207 from the beginning. For example, each program is stored in a “portable physical medium” such as a flexible disk (FD), a CD-ROM, a DVD disk, a magneto-optical disk, and an IC card inserted into the computer 200. Then, the computer 200 may read and execute the programs 207a and 207b.

  The following supplementary notes are further disclosed with respect to the embodiments including the above examples.

(Supplementary note 1)
Based on the predicted solar radiation amount predicted at the prediction target point and date and the actual solar radiation amount actually measured at the prediction target point and date and time, the prediction error of the predicted solar radiation amount with respect to the actual solar radiation amount increases. Generate prediction error information that identifies whether the direction is the direction or the direction of decrease for each weather forecast,
Based on the prediction error information, the solar radiation amount prediction information, and the solar power generation device information, a process of calculating the power generation amount generated by the solar power generation device and the power generation amount prediction error is executed. A power amount prediction program characterized by that.

(Supplementary note 2) The electric energy prediction program according to supplementary note 1, wherein the weather prediction is a weather prediction including clear, cloudy, and rainy categories.

(Supplementary note 3) The electric energy prediction program according to supplementary note 1, wherein the weather prediction is an index related to the amount of solar radiation.

(Supplementary note 4) The electric energy prediction program according to supplementary note 1, wherein the weather prediction is a clear sky index obtained by dividing the predicted solar radiation amount by an outdoor solar radiation amount.

(Supplementary Note 5) The calculation process uses an increase direction prediction error included in the prediction error information or a decrease direction prediction error included in the prediction error information based on the solar radiation amount prediction information. The power amount prediction program according to appendix 1, wherein a prediction error of the power generation amount is calculated.

(Supplementary note 6) Prediction of the predicted solar radiation amount with respect to the actual solar radiation amount based on the predicted solar radiation amount predicted at the prediction target point and date and the actual solar radiation amount actually measured at the prediction target point and date and time A generation unit that generates prediction error information that specifies whether the error is in an increasing direction or a decreasing direction for each weather prediction;
Based on the prediction error information, solar radiation amount prediction information, and solar power generation device information, a power generation amount generated by the solar power generation device and a calculation unit that calculates a prediction error of the power generation amount An apparatus for predicting electric energy, comprising:

(Supplementary note 7) The electric energy prediction apparatus according to supplementary note 6, wherein the weather prediction is a weather prediction including clear, cloudy, and rainy categories.

(Supplementary note 8) The electric energy prediction device according to supplementary note 6, wherein the weather prediction is an index related to the amount of solar radiation.

(Supplementary note 9) The electric energy prediction apparatus according to supplementary note 6, wherein the weather prediction is a clear sky index obtained by dividing the predicted solar radiation amount by the atmospheric solar radiation amount.

(Supplementary Note 10) The calculation unit uses an increase direction prediction error included in the prediction error information or a decrease direction prediction error included in the prediction error information based on the solar radiation amount prediction information. The power amount prediction apparatus according to appendix 6, wherein a prediction error of the power generation amount is calculated.

(Additional remark 11) It is the electric energy prediction method which a computer performs, Comprising:
Based on the predicted solar radiation amount predicted at the prediction target point and date and the actual solar radiation amount actually measured at the prediction target point and date and time, the prediction error of the predicted solar radiation amount with respect to the actual solar radiation amount increases. Generate prediction error information that identifies whether the direction is the direction or the direction of decrease for each weather forecast,
Based on the prediction error information, the solar radiation amount prediction information, and the solar power generation device information, a process of calculating the power generation amount generated by the solar power generation device and the power generation amount prediction error is executed. An electric energy prediction method characterized by the above.

(Supplementary note 12) The electric energy prediction method according to supplementary note 11, wherein the weather prediction is a weather prediction including clear, cloudy, and rainy categories.

(Supplementary note 13) The electric energy prediction method according to supplementary note 11, wherein the weather prediction is an index related to the amount of solar radiation.

(Supplementary note 14) The electric energy prediction method according to supplementary note 11, wherein the weather prediction is a clear sky index obtained by dividing the predicted solar radiation amount by an outdoor solar radiation amount.

(Supplementary Note 15) The calculation process uses an increase direction prediction error included in the prediction error information or a decrease direction prediction error included in the prediction error information based on the solar radiation amount prediction information. The power amount prediction method according to appendix 11, wherein a prediction error of the power generation amount is calculated.

DESCRIPTION OF SYMBOLS 100 Electric power amount prediction apparatus 110 Communication part 120 Input part 130 Display part 140 Storage part 150 Control part 151 Collection part 152 Generation part 153 Calculation part

Claims (7)

On the computer,
Based on the predicted solar radiation amount predicted at the prediction target point and date and the actual solar radiation amount actually measured at the prediction target point and date and time, the prediction error of the predicted solar radiation amount with respect to the actual solar radiation amount increases. Generate prediction error information that identifies whether the direction is the direction or the direction of decrease for each weather forecast,
Based on the prediction error information, the solar radiation amount prediction information, and the solar power generation device information, a process of calculating the power generation amount generated by the solar power generation device and the power generation amount prediction error is executed. A power amount prediction program characterized by that.   The electric energy prediction program according to claim 1, wherein the weather prediction is a weather prediction including sunny, cloudy, and rainy categories.   The electric energy prediction program according to claim 1, wherein the weather prediction is an index related to solar radiation.   The electric energy prediction program according to claim 1, wherein the weather prediction is a clear sky index obtained by dividing the predicted solar radiation amount by an outdoor solar radiation amount.   The process of calculating, based on the prediction information of the solar radiation amount, using the prediction error in the increasing direction included in the prediction error information, or the prediction error in the decreasing direction included in the prediction error information, The power amount prediction program according to claim 1, wherein a power generation amount prediction error is calculated. Based on the predicted solar radiation amount predicted at the prediction target point and date and the actual solar radiation amount actually measured at the prediction target point and date and time, the prediction error of the predicted solar radiation amount with respect to the actual solar radiation amount increases. A generation unit that generates prediction error information specifying for each weather prediction whether it is a direction or a decreasing direction;
Based on the prediction error information, solar radiation amount prediction information, and solar power generation device information, a power generation amount generated by the solar power generation device and a calculation unit that calculates a prediction error of the power generation amount An apparatus for predicting electric energy, comprising: A method for predicting the amount of power executed by a computer,
Based on the predicted solar radiation amount predicted at the prediction target point and date and the actual solar radiation amount actually measured at the prediction target point and date and time, the prediction error of the predicted solar radiation amount with respect to the actual solar radiation amount increases. Generate prediction error information that identifies whether the direction is the direction or the direction of decrease for each weather forecast,
Based on the prediction error information, the solar radiation amount prediction information, and the solar power generation device information, a process of calculating the power generation amount generated by the solar power generation device and the power generation amount prediction error is executed. An electric energy prediction method characterized by the above.

Images