Display method

Abstract

To evaluate the actual performance of a power plant using exceedance probability calculated from past meteorological data.SOLUTION: A display method in a management system which manages one or more power plants 40 that generate electricity from sunlight is configured to simultaneously display measured power which is measured in the power plant 40 and expected power with predetermined exceedance probability which is calculated based on past sunshine duration information in a predetermined area of the power plant 40.SELECTED DRAWING: Figure 10

Description

[Technical Field]

[0001] The present invention relates to a display method. [Background technology]

[0002] In the solar power generation business, it is well known that the expected power generation amount is calculated from meteorological data, and management and anomaly detection are performed in conjunction with the actual power generation results.

[0003] For example, Patent Document 1 discloses an operational state estimation device that estimates the operational state of a photovoltaic power generation facility. The operational state estimation device includes: a calculation formula storage unit that stores a calculation formula for calculating an estimated value of the amount of power generated by the photovoltaic power generation facility from predetermined types of meteorological data including solar radiation; a weather data acquisition unit that acquires the meteorological data from a weather data providing device that is communicably connected; a first index value calculation unit that calculates, for each first period in which the operational state of the photovoltaic power generation facility is periodically estimated, a first index value that represents the degree of deviation between the estimated value and an actual value, based on an estimated value of the amount of power generated by the photovoltaic power generation facility for the first period calculated using the meteorological data and the calculation formula and an actual value of the amount of power generated by the photovoltaic power generation facility for the first period; a judgment value calculation unit that calculates an average value and a standard deviation of the first index values for a predetermined past period and calculates a judgment value based on the average value and the standard deviation; and an operational state estimation unit that estimates the operational state of the photovoltaic power generation facility based on a result of comparing the first index value with the judgment value.

[0004] Patent Document 2 discloses a business management system that facilitates the long-term continuity of a power generation business. This business management system includes: an analysis means that analyzes the power generation environment and power generation trends of multiple power generation facilities under management for each power generation facility and outputs the analysis result data in association with the identification information of each power generation facility; an evaluation means that regularly or irregularly acquires inspection implementation data representing the results of inspections conducted according to predetermined inspection items at each power generation facility, and evaluates, for each power generation facility, the conformity with predetermined evaluation criteria defined from the perspective of at least one of risk control and the perspective of removing factors inhibiting power generation based on the acquired inspection implementation data and the analysis result data, and outputs the evaluation result data in association with the identification information of the power generation facility; and an electronic medical record management means that generates, for each power generation facility, an electronic medical record in which the analysis result data and the evaluation result data are recorded with a history, and visualizes the recorded items of each electronic medical record within a scope corresponding to predetermined authority information.

[0005] Patent Document 3 discloses an information processing device that prevents the accuracy of calculating the sum of expected power generation from decreasing as the period for calculating the sum of expected power generation becomes longer. This information processing device includes: a solar radiation data acquisition unit that acquires solar radiation data relating to past solar radiation at multiple power plants where solar power generation devices that receive sunlight and generate electricity are installed; an expected power generation calculation unit that calculates the expected power generation of the solar power generation devices for each of the multiple power plants based on the solar radiation data; a deviation calculation unit that calculates the deviation of the expected power generation calculated for each of the multiple power plants; and a sum calculation unit that calculates the sum of the expected power generation of the multiple power plants based on the expected power generation and deviation calculated for each of the multiple power plants. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Japanese Patent Application Publication No. 2023-032497 [Patent Document 2] Japanese Patent Application Publication No. 2023-008924 [Patent Document 3] Japanese Patent Application Laid-Open No. 2023-134273 Summary of the Invention [Problem to be solved by the invention]

[0007] In Patent Documents 1 to 3, when managing a solar power plant, the actual amount of power generation and the amount of solar radiation are not managed based on expected values using exceedance probabilities calculated from past weather data. Therefore, when the amount of power generation decreases, for example, it is difficult to distinguish whether the decrease is due to the influence of the amount of solar radiation or the influence of the power plant by analyzing the exceedance probability.

[0008] An object of the present invention is to provide a display method that can evaluate the performance of a power plant using exceedance probabilities calculated from past weather data. [Means for solving the problem]

[0009] The first aspect of the display method is a display method in a management system that manages one or more power plants that generate electricity by receiving sunlight, and simultaneously displays the measured power generation amount measured at the power plant and the expected power generation amount with a predetermined exceedance probability calculated based on past sunshine hour information in the area where the power plant is located.

[0010] The second display method is the same as the first display method, but in addition to the first display method, simultaneously displays the measured solar radiation measured at the power plant and the expected solar radiation with a predetermined exceedance probability calculated based on the sunshine duration information.

[0011] The display method of the third aspect is the display method of the second aspect, in which, when the evaluation of the measured power generation amount based on the exceedance probability is lower than the evaluation of the measured solar radiation amount based on the exceedance probability, the possibility of at least one of an abnormality in the power plant and the possibility of output control of the power plant is displayed.

[0012] The display method of the fourth aspect is the display method of the first aspect, in which the transition states of the measured amount of power generation measured on a monthly basis and the plurality of expected amounts of power generation are simultaneously displayed.

[0013] The display method of the fifth aspect is the display method of the fourth aspect, and in addition, simultaneously displays the transition states of the measured solar radiation measured on a monthly basis at the power plant and the expected solar radiation with multiple predetermined exceedance probabilities calculated based on the sunshine duration information.

[0014] The display method of the sixth aspect is the display method of the first aspect, in which the transition states of the measured power generation amount measured on an annual basis at the power plant and the multiple expected power generation amounts are simultaneously displayed.

[0015] The seventh aspect of the display method is the same as the sixth aspect, but in addition to the sixth aspect, it simultaneously displays the transition states of the measured solar radiation measured on an annual basis at the power plant and the expected solar radiation with multiple predetermined exceedance probabilities calculated based on the sunshine duration information.

[0016] The display method of the eighth aspect is the display method of the first aspect, in which the total value of the measured power generation measured on an annual basis at multiple power plants and the transition states of each of the multiple expected power generation amounts are simultaneously displayed.

[0017] The display method of the ninth aspect is the display method of the eighth aspect, and further includes simultaneously displaying the transition states of the average value of the measured solar radiation measured on an annual basis at a plurality of the power plants and the expected solar radiation of a plurality of predetermined exceedance probabilities calculated based on the sunshine duration information.

[0018] The tenth aspect of the display method is a display method in a management system that manages one or more power plants that generate electricity by receiving sunlight, and simultaneously displays the transition states of the amount of power generated calculated based on past sunshine hours information in the area where the power plant is located and the predicted amount of power generated based on the amount of power generated. [Effects of the Invention]

[0019] According to the present invention, the performance of a power plant can be evaluated using the exceedance probability calculated from past weather data. [Brief explanation of the drawings]

[0020] [Figure 1] 1 is a schematic configuration diagram of a remote monitoring system including a power generation system according to a first embodiment. [Figure 2] 1 is a diagram schematically illustrating an example of a hardware configuration of a power generation system according to a first embodiment. [Figure 3] 1 is a schematic configuration diagram of a power generation system according to a first embodiment. [Figure 4] 10 is a flowchart of a power generation amount prediction logic as a second acquisition example. [Figure 5] 4 is a control flowchart showing a power generation control routine that is executed at the start of power generation in the power generation system of the first embodiment. [Figure 6] 4 is a control flowchart showing a power generation amount monitoring routine executed during power generation. [Figure 7] This is a front view of the operation / display panel of the user interface, where information generated by the information management unit is displayed in graph form. (A) is a time-series characteristic diagram of the measured power generation amount Pk, which is the power generation amount data that can be obtained (measured) when output control is applied. (B) is a characteristic diagram in which the characteristic diagram of the measured power generation amount Pk is superimposed with the characteristic diagram of the restored power generation amount Pf. (C) is a characteristic diagram in which the characteristic diagram of the restored power generation amount Pf is superimposed with the effective power generation amount Pj, which is the restored power generation amount Pf multiplied by the output control amount, superimposed on the characteristic diagram in which the characteristic diagram of the restored power generation amount Pf is superimposed. [Figure 8] FIG. 10 is an image diagram of the amount of power generated by output control on the power selling side. [Figure 9] FIG. 10 is an image diagram of output control on the power purchasing side. [Figure 10] FIG. 10 is a schematic configuration diagram of a power generation system according to a second embodiment. [Figure 11] 10 is an example of a time series graph showing measured power generation and expected power generation in a power plant according to the second embodiment on a monthly basis. [Figure 12] 10 is an example of a time series graph showing the measured amount of solar radiation and the expected amount of solar radiation in the power plant per month according to the second embodiment. [Figure 13] 10 is an example of a time series graph showing the measured power generation amount and the expected power generation amount of the power plant according to the second embodiment on a yearly basis. [Figure 14] 10 is an example of a time series graph showing the measured amount of solar radiation and the expected amount of solar radiation in the power plant in units of years according to the second embodiment. [Figure 15] 10 is an example of a time series graph showing the sum of measured power generation amounts and the sum of expected power generation amounts of a plurality of power plants on an annual basis according to the second embodiment. [Figure 16] 10 is an example of a time series graph showing the average values of the measured solar radiation and the average values of the expected solar radiation in a plurality of power plants on an annual basis according to the second embodiment. [Figure 17] FIG. 10 is a diagram showing an example of a screen display showing evaluations of measured power generation and measured solar radiation according to the second embodiment. [Figure 18] 10 is an example of a time series graph displaying the future tendency of the amount of power generated in the power plant according to the second embodiment. [Figure 19] 10 is a flowchart showing an example of the flow of a performance display process for displaying performance of a power plant according to the second embodiment. [Figure 20] 20 is a flowchart illustrating an example of the flow of the performance display process following FIG. 19. [Figure 21] 10 is a flowchart showing an example of the flow of an expected value calculation process for each power plant according to the second embodiment. [Figure 22] 10 is a flowchart showing an example of the flow of an expected value calculation process for all power plants according to the second embodiment. [Figure 23] 10 is a flowchart showing an example of the flow of a trend display process for displaying the future trend of expected power generation according to the second embodiment. [Figure 24] FIG. 10 is a schematic configuration diagram of a power generation system 10 according to a modified example of the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0021] (First embodiment) FIG. 1 is a schematic configuration diagram of a remote monitoring system 50 including a power generation system 10 according to a first embodiment. As shown in FIG. 1, the remote monitoring system 50 of this embodiment is configured to include the power generation system 10, a power company 20, an external weather management server 30, and multiple power plants 40. The power generation system 10, the power company 20, the external weather management server 30, and the multiple power plants 40 are each connected to a network N and are capable of communicating with each other. The network N may be, for example, an internet line such as a wide area network (WAN) or a dedicated line. Although FIG. 1 illustrates one power company 20 and one external weather management server 30, there may be multiple of each. Furthermore, although multiple power plants 40 are illustrated, there is only required to be at least one. The power generation system 10 is an example of an "information processing device."

[0022] The power generation system 10 is an information processing device that manages information related to power generation. For example, the power generation system 10 acquires weather-related data from an external weather management server 30, receives power generation instructions from an electric power company 20, and manages power plants 40 registered in the power generation system 10. Note that the power generation system 10 is not limited to being configured by a single information processing device, and may be configured by multiple devices (for example, microcomputers, which will be described later) installed in different locations.

[0023] The electric power company 20 is a management system or server for selling the electric power generated by the power plant 40. The electric power company 20 can also transmit power generation instructions to the power generation system 10 and control the output of the power plant 40.

[0024] The external weather management server 30 is a server that manages weather data, sunshine data, etc. acquired from observation stations installed throughout Japan. The external weather management server 30 is, for example, a server that stores data from the Japan Meteorological Agency's AMeDAS (Automated Meteorological Data Acquisition System). The weather data and sunshine data are examples of "sunshine duration information."

[0025] The power plant 40 includes a plurality of power generation devices 14 and a sunlight sensor 14A. The power generation devices 14 according to this embodiment are solar panels. The sunlight sensor 14A is installed near the power generation devices 14 and is a sensor that acquires sunlight information. The power plant 40 transmits, for example, data on the amount of power generated by the power generation devices 14 and data on the amount of sunlight measured by the sunlight sensor 14A to the power generation system 10. The power plant 40 according to this embodiment includes an information processing device (not shown) for transmitting data to the power generation system 10.

[0026] (Hardware configuration) 2 is a diagram schematically illustrating an example of a hardware configuration of a power generation system 10 according to the first embodiment. The power generation system 10 includes a central processing unit (CPU) 10A, a read-only memory (ROM) 10B, a random access memory (RAM) 10C, a storage 10D, an input / output I / F 10E, and a communication I / F 10F. Each component is connected to each other via a bus 10G so as to be able to communicate with each other.

[0027] The CPU 10A is a central processing unit that executes various programs and controls each component. The ROM 10B stores various programs and data. The RAM 10C temporarily stores programs or data as a work area. That is, the CPU 10A reads a program from the ROM 10B and executes the program using the RAM 10C as a work area.

[0028] The storage 10D is configured by a hard disk drive (HDD), a solid state drive (SSD), etc., and stores various programs and various data. The storage 10D includes a processing program and a history database 32 (see FIG. 3) described later.

[0029] The input / output I / F 10E is an interface for connecting to an input / output device and is used for inputting and outputting various types of information. The input / output I / F 10E is, for example, a user interface 16 (see FIG. 3) described later.

[0030] The communication I / F 10F is an interface for communicating with other devices. Specifically, the communication I / F 10F communicates with the electric power company 20, the external weather management server 30, and a plurality of power plants 40 via a network N. For this communication, for example, a wired communication standard such as Ethernet (registered trademark) or FDDI, or a wireless communication standard such as 4G, 5G, or Wi-Fi (registered trademark) is used.

[0031] FIG. 3 is a schematic configuration diagram of a power generation system 10 according to this embodiment. In FIG. 3, each block is classified by function and does not limit the hardware configuration. Some or all of the blocks may be executed by a processing program executed by a microcomputer. Although not shown, the microcomputer is composed of a CPU (Central Processing Unit), RAM (Random Access Memory), ROM (Read Only Memory), input / output ports, and buses such as a data bus and a control bus that connect these.

[0032] In addition, some or all of the blocks that make up the power generation system 10 may be constructed using semiconductor integrated circuits such as ASICs (Application Specific Integrated Circuits), FPGAs (Field Programmable Gate Arrays), and CPLDs (Complex Programmable Logic Devices).

[0033] 3, the power generation system 10 includes a power generation control unit 12. The power generation control unit 12 controls the power generation of the power generation device 14 (such as a solar panel) by sending a power generation instruction to the power generation device 14. For example, the power generation instruction is the amount of power generation, and the power generation instruction is sent in the range of 0% to 100%.

[0034] The power generation control unit 12 is connected to a user interface 16. The user interface 16 includes an operation / display panel (touch panel) 16A.

[0035] The power generation instruction is given by an operator operating the operation / display panel 16A. A predetermined power generation program may automatically instruct the user to start and stop power generation at predetermined times. The user interface 16 will be described in detail later.

[0036] The power generation control unit 12 also receives the power generated by the power generation device 14 and sends it to the power management unit 18. The power management unit 18 sells the power to a predetermined power company 20. Note that all the power may be sold, or, for example, the power remaining after consuming the power necessary to operate the power generation system 10 may be sold.

[0037] Here, the power company 20 may issue an instruction to control the output in order to limit the sale of power, as necessary.

[0038] The output control command from the power company is acquired by an output control command acquisition unit 22 of the power generation system 10.

[0039] The output control instruction acquisition unit 22 is connected to the power generation control unit 12 and the restoration unit 24 .

[0040] When the power generation control unit 12 receives the output control value (for example, 40%, 100%) acquired by the output control instruction acquisition unit 22, it limits the amount of power generated by the power generation device 14 based on the output control value.

[0041] Here, in the power generation system 10, it is necessary to monitor whether power generation is being carried out as controlled by the power generation control unit 12, whether power generation restriction processing is being carried out in accordance with output control from the power company 20, etc.

[0042] Therefore, the power generation system 10 of this embodiment is configured to include an information management unit 26 that aggregates information related to power generation. The information management unit 26 is connected to the restoration unit 24 and the power generation amount measurement unit 28.

[0043] The restoration unit 24 calculates the amount of power (restored power generation amount Pf) that can be generated by the power generation device 14 when it is assumed that there is no output control (output control 0%), and sends it to the information management unit 26.

[0044] To calculate the restored power generation amount Pf, the restoration unit 24 is connected to the output control instruction acquisition unit 22, the external weather management server 30, and the history database 32.

[0045] The restoration unit 24 extracts time periods when the output control value is other than 0% (40% and 100% in the above example), and uses sunshine information, etc. acquired from the external weather management server 30 or the sunshine sensor 14A installed near the power generation device 14 to predict the amount of power that can be generated based on the sunshine information, etc. (first acquisition example).

[0046] In addition, past power generation data (such as the most recent or same day of the previous year) can be read from the history database 32, and the amount of power generation can be predicted based on the weather data obtained from the external weather management server 30 (or sunshine information obtained from a sunshine sensor 14A installed near the power generation device 14) (second acquisition example).

[0047] As an example, the power generation amount prediction logic based on the second acquisition example will be described with reference to FIG. (Step 1) Select the target date (here, today). (Step 2) Obtain past data (most recent or previous year, etc.). (Step 3) Generate a correction value depending on the type of data obtained (the algorithm for generating the correction value differs depending on whether it is the most recent data or the previous year). (Step 4) Obtain weather data (or sunshine information). (Step 5) Calculate the predicted power generation amount from weather data (or sunshine information) and past data. For example, use a machine learning model. In this case, the training data is weather data (amount of sunshine). (Step 6) Calculate the amount of power generated taking into account the correction value.

[0048] In addition to obtaining the restored power generation amount, the second acquisition example can also predict the future power generation amount (for example, the power generation amount for the next weekend) with high accuracy.

[0049] The method of calculating the restored power generation amount in the restoration unit 24 may be either the first or second acquisition example, or a combination of both acquisition examples. Alternatively, another method of predicting the restored power generation amount may be used.

[0050] The information management unit receives the output control value and the restored power generation amount Pf from the restoration unit 24. The information management unit also receives the measured power generation amount Pk from the power generation amount measurement unit .

[0051] The information management unit 26 prepares the following information as power generation information. (Information 1) Measured power generation amount Pk (measured and available power generation amount) (Information 2) Restored power generation amount Pf (power generation amount restored by output control information) (Information 3) Differential power generation ΔP (restored power generation amount - measured power generation amount) (Information 4) Effective power generation amount Pj (restored power generation amount x output control value (rate)) (Information 5) Abnormality judgment (effective power generation amount - measured power generation amount ≠ 0)

[0052] In addition, in information 5, since the effective power generation amount - the measured power generation amount will never be negative in practice, it may be determined that the effective power generation amount - the measured power generation amount > 0, and that the value is normal when it is 0, and that anything else is abnormal. Also, the information management unit 26 can use the value of the power generation amount of a test panel not connected to a PCS as an alternative index of the amount of solar radiation, and for example, prepare the restored solar radiation amount even without the sunshine sensor 14A or the like. In other words, if the measured power generation amount and the output control value are known, the amount of solar radiation can be calculated, and the restored power generation amount can be obtained from the restored solar radiation amount.

[0053] The information management unit 26 is connected to the notification content acquisition unit 34. Type information of the notification content selected by operating the operation / display panel 16A of the user interface 16 is input to the notification content acquisition unit 34, and the notification content (information 1 to information 5) is acquired from the information management unit 26 based on the type information.

[0054] The notification contents (information 1 to information 5) acquired by the notification content acquisition unit 34 are sent to the user interface 16 via the output unit 36. The output unit 36 can also send the restored amount of solar radiation to the user interface 16.

[0055] In the case of visual notification, the user interface 16 uses the monitor function of the operation / display panel 16A to display information in, for example, a graph format as shown in FIG.

[0056] The user interface 16 also includes a notification device 16B.

[0057] Examples of the notification device 16B include a speaker or buzzer that notifies through hearing, and a warning light or printer that notifies through vision, similar to the operation / display panel 16A. In addition, a notification that is not a direct notification but is sent to a tablet terminal or the like carried by the operator via communication can also be considered a notification.

[0058] The operation of this embodiment will be described below with reference to the flowcharts of FIGS.

[0059] FIG. 5 is a control flowchart showing a power generation control routine that is started when power generation starts.

[0060] In step 100, a command is issued to generate power at a specified power generation amount (for example, 100%). This causes the power generation device 14 to start generating power, and the power is sold to the power company 20 via the power management unit 18.

[0061] In the next step 102, it is determined whether or not there has been an output control command from the electric power company 20. If the determination in step 102 is negative, it is determined that there has been no output control command from the electric power company 20, and the routine proceeds to step 104. In step 104, it is determined whether or not it is time to end power generation, and if the determination is negative, the routine returns to step 102. If the determination in step 104 is positive, the routine proceeds to step 106, where an instruction to end power generation is sent, and the routine ends.

[0062] On the other hand, if the determination in step 102 is affirmative, it is determined that an instruction to control output has been received from the power company 20, and the process proceeds to step 108.

[0063] In step 108, the output control value is acquired. For example, depending on the time period, it may be 0% or 40%. Note that the output control value is not limited to 0% and 40%, but can be set between 0% and 100% (0% is essentially no output control).

[0064] In the next step 110, a power generation instruction is sent based on the acquired output control value, so that the power generation control unit 12 instructs the power generation device 14 to generate power based on the output control value.

[0065] In the next step 112, it is determined whether or not the output control value has been changed, and if the determination is negative, the process proceeds to step 114, where it is determined whether or not the output control has ended. If the determination is negative in step 114, the process returns to step 112, and steps 112 and 114 are repeated until a positive determination is made in step 112 or step 114.

[0066] If the determination in step 112 is affirmative, it is determined that the output control value has been changed, and the process returns to step 108, where the output control value is acquired again, and the above process is repeated.

[0067] If the determination in step 114 is affirmative, it is determined that the output control has ended, and the process returns to step 100, where power generation at the designated power generation amount (i.e., 100%) is instructed, and the above steps are repeated.

[0068] FIG. 6 is a control flowchart showing a power generation amount monitoring routine that is executed during power generation based on the control flowchart shown in FIG.

[0069] In step 150, the amount of power generated during power generation is measured (measured power generation amount Pk). Next, in step 152, it is determined whether output control is in progress. If the determination in step 152 is negative, it is determined that output control is not in progress, and the process proceeds to step 154.

[0070] In step 154, the measured power generation amount Pk is displayed on the monitor function of the operation / display panel 16A of the user interface, and the process proceeds to step 168.

[0071] If the determination in step 152 is affirmative, it is determined that output control is in progress, and the process proceeds to step 156.

[0072] In step 156, the amount of power generated during non-output control is restored (restored power generation amount Pf). The restored power generation amount pf can be obtained by the first or second acquisition example described above.

[0073] In the next step 158, the difference ΔP between the restored power generation amount Pf and the measured power generation amount Pk is calculated (power generation difference ΔP).

[0074] In the next step 160, the amount of power generated is calculated from the restored power generation amount Pf and the output control value (effective power generation amount Pj).

[0075] In the next step 161, the information obtained in steps 156, 158, and 160 is selected, graphed, and displayed on the operation / display panel 16A of the user interface 16 (see FIG. 7). The display forms of FIGS. 7(A) to 7(C) will be described later.

[0076] In the next step 162, it is determined whether the measured power generation amount Pk displayed on the operation / display panel 16A of the user interface 16 is a normal value or an abnormal value based on the difference between the effective power generation amount Pj and the measured power generation amount Pk.

[0077] That is, if the effective power generation amount Pj = the measured power generation amount Pk, it is determined to be normal. Also, if the effective power generation amount Pj ≠ the measured power generation amount Pk (effective power generation amount Pj - measured power generation amount Pk > 0), it is determined to be abnormal.

[0078] In the next step 164, it is determined whether the judgment result is normal or abnormal. If it is determined to be abnormal in this step 164, the process proceeds to step 166, where the operation / display panel 16A and the notification device 16B of the user interface 16 are used to notify that the display is abnormal, and the process proceeds to step 168.

[0079] If the result of the determination in step 164 is normal, there is no need to notify, so the process proceeds to step 168.

[0080] In step 168, it is determined whether or not power generation has ended, and if the determination is negative, the process returns to step 150 and the above steps are repeated. If the determination is positive in step 168, this routine ends.

[0081] FIG. 7 is a front view of operation / display panel 16A of user interface 16, on which the information (information 1 to information 5) generated by information management unit 26 is displayed in the form of graphs.

[0082] Figure 7(A) is a time series characteristic diagram A of the measured power generation amount Pk, which is the available (measurable) power generation amount data when the output is controlled. This characteristic diagram shows that the power generation amount is controlled according to the output control value, which changes every minute.

[0083] Figure 7(B) is a characteristic diagram in which characteristic diagram B of the restored power generation amount Pf is superimposed on characteristic diagram A of the measured power generation amount Pk in Figure 7(A). By simultaneously displaying the measured power generation amount Pk and the restored power generation amount Pf in this way, the area where no power generation was achieved due to output control (the area indicated by the cross-hatched line in Figure 7(B)) can be visually recognized.

[0084] Figure 7(C) is a characteristic diagram obtained by superimposing characteristic diagram A of the measured power generation amount Pk in Figure 7(B) and characteristic diagram B of the restored power generation amount Pf on characteristic diagram C, which is obtained by superimposing effective power generation amount Pj obtained by multiplying the restored power generation amount Pf by the output control amount.

[0085] In the case of Figure 7(C), there is a time period (around 15:00 to 18:00) where there is a difference between the effective power generation amount Pj and the measured power generation amount Pk (see the diagonally shaded area rising to the right in Figure 7(C)). This makes it possible to determine that there is a display abnormality in the operation / display panel 16A of the user interface 16, and distinguish it from a decrease in power generation due to output control.

[0086] Here, International Publication No. 2022 / 024960 discloses a solar radiation correction method that acquires solar radiation data, acquires meteorological data, and corrects the acquired solar radiation data based on the acquired meteorological data.

[0087] In addition to forecasting services, it can be put to practical use as part of a service that responds to output control, a system in which power companies20 temporarily limit the amount of electricity they purchase to prevent a sudden increase in the supply of electricity.

[0088] For example, as shown in Figure 8, the actual measured value of the power generation amount is the value after the output control is applied. This makes it impossible to grasp the planned power generation amount, and it becomes difficult to manage the appropriateness (detecting abnormalities, etc.) of the power plant that is the control target of the power generation system.

[0089] Solar power generation peaks during the daytime when demand for electricity is low (see Figure 9). During these times, output suppression (output control) has a significant impact. Power generation forecasts require a model to learn the correct amount of power generation, and data that restores the amount of power generation that was controlled by output control to the amount that would have been generated is essential information.

[0090] Furthermore, if the visualized information is based on the correct amount of power generation, it can become reliable information for power generation management.

[0091] Taking the above facts into consideration, according to this embodiment, it is possible to restore the value after the output control and manage the amount of power generated by the power plant without being affected by the output control.

[0092] According to this embodiment, it is possible to grasp the planned power generation amount by using the power restoration technology cultivated through forecasting. It is possible to distinguish between a decrease in power generation amount due to an abnormality in the panel (operation / display panel 16A) and a decrease due to output control. According to the power generation system 10, it is possible to develop a service that combines with the existing solar power generation diagnostic business as a management service.

[0093] (Technology of the Invention) The present invention includes the following disclosed techniques. (Disclosed Technology 1)

[0094] A power generation system comprising at least a power generation device whose power generation output is controlled in a predetermined case, and a power generation amount measuring device capable of accurately measuring the amount of power generation without output control.

[0095] The power generation measurement device is expected to be part of the power generation panel or a separate pyranometer.

[0096] According to Disclosed Technology 1, it is possible to accurately measure the amount of power generated even when output restrictions are imposed. For example, from the perspective of power generation forecasting, it is possible to improve the accuracy of future power generation forecasts compared to when no power generation amount measuring device is used.

[0097] (Disclosed Technology 2) In a power generation system in which the output of power generation is controlled in predetermined cases, the method includes at least an output power generation obtaining step of obtaining output power generation data, a restoration step of restoring the power generation data when the output power generation decreases to obtain restored power generation data (characteristic diagram B shown in Figures 7(B) and (C)), and a judgment step of comparing a predicted value of power generation data predicted from the restored power generation data (characteristic diagram C in Figure 7(C)) with the power generation data (characteristic diagram A in Figures 7(A) to (C)) to judge whether the decrease in power generation is due to output control, and if it is judged not to be due to output control in the judgment step, an abnormality is notified.

[0098] An example of an abnormality in a power generation system is a panel failure. Methods for obtaining restored power generation data include using the power generation measurement device (pyranometer) of Disclosed Technology 1 and calculating it by calculation.

[0099] According to the disclosed technology 2, it becomes possible to detect whether the decrease in output is due to control or an abnormality.

[0100] (Disclosed Technology 3) (3-1) A display method for a power generation system in which the output of power generation is controlled in a predetermined case, the display method comprising at least a restored power generation obtaining step of obtaining restored power generation data (characteristic diagram B shown in Figures 7(B) and (C)) by restoring power generation data when the output power generation drops, and displaying the restored power generation data (characteristic diagram B shown in Figures 7(B) and (C)) on a display means.

[0101] According to disclosed technology 3-1, restored power generation data can be visualized.

[0102] (3-2) A display method for a power generation system in which the output of power generation is controlled in a predetermined case, the display method comprising at least an output power generation amount obtaining step of obtaining output power generation amount data, and a restored power generation amount obtaining step of restoring the power generation amount data when the output power generation amount decreases to obtain restored power generation amount data (characteristic diagram B shown in Figures 7(B) and (C)), and simultaneously displaying the power generation amount data (characteristic diagram C shown in Figures 7(A) to (C)) and the restored power generation amount data (characteristic diagram B shown in Figures 7(B) and (C)) on a display means.

[0103] As the display means, paper, a display, etc. can be used.

[0104] According to the disclosed technique 3-2, it becomes easy to compare the observed power generation amount data with the restored power generation data.

[0105] (3-3) The display method of Disclosed Technology 3-1 further includes a predicted value acquisition step of acquiring a predicted value of power generation data (characteristic diagram C shown in Figure 7(C)) predicted from the restored power generation data, and simultaneously displays the power generation data (characteristic diagram C shown in Figures 7(A) to (C)), the restored power generation data (characteristic diagram B shown in Figures 7(B) and (C)), and the predicted value (characteristic diagram C shown in Figure 7(C)) on a display means.

[0106] According to Disclosed Technology 3-3, in addition to Disclosed Technology 2, comparison with predicted values becomes easier.

[0107] (3-4) The display method of Disclosed Technology 3-3, in which the difference between the power generation amount data and the predicted value is displayed on a display means by changing the color.

[0108] According to disclosed technology 3-4, it becomes easy to grasp the difference.

[0109] (3-5) The display method of disclosed technology 3-4 displays an abnormality on the display means when the difference exceeds a predetermined value.

[0110] According to Disclosed Technology 3-5, abnormalities in the power generation system can be easily detected.

[0111] (Disclosed Technology 4)

[0112] (4-1) In a power generation system in which the output of power generation is controlled in a predetermined case, a method for providing lost (differential) power generation or an output device for lost power generation includes at least the following steps: an output power generation amount obtaining step for obtaining output power generation amount data (characteristic diagram C shown in Figures 7(A) to (C)); a restored power generation amount obtaining step for restoring the power generation amount data when the output power generation amount decreases and obtaining restored power generation amount data (characteristic diagram B shown in Figures 7(B) and (C)); and a step in which an output means calculates the difference between the power generation amount data and the restored power generation amount data and outputs the calculated difference to an input means as lost (differential) power generation.

[0113] In Disclosed Technology 4-1, the output means is assumed to be a server on the business side, and the input means is assumed to be a PC on the customer side.

[0114] (4-2) The method for providing the amount of lost (differential) power generation according to Disclosed Technique 4-1, wherein the output means outputs the amount of lost power generation for each predetermined period (day, month, etc.) to the input means at a predetermined timing.

[0115] Disclosed Technology 4-2 envisions a function that automatically issues reports listing the amount of power generation lost on a daily and monthly basis.

[0116] In addition, when realizing the power generation system, abnormality notification method, and display method of the present invention, it is possible to construct each necessary process as a program that causes a computer to operate, and the program can be recorded on a recording medium, etc.

[0117] (Second embodiment) Next, a second embodiment will be described while omitting or simplifying parts that overlap with the above-mentioned embodiment. The second embodiment is characterized in that the power generation system 10 displays data on the amount of power generation and the amount of solar radiation.

[0118] (Functional configuration) FIG. 10 is a schematic configuration diagram of a power generation system 10 according to the second embodiment.

[0119] The power generation system 10 of this embodiment communicates with an external weather management server 30 and a power plant 40. Furthermore, the power generation system 10 of this embodiment functions as a calculation unit 21, a power generation amount measurement unit 28, a performance evaluation unit 29 as an evaluation unit, an information management unit 26, a notification content acquisition unit 34, an output unit 36, and the like, by the CPU 10A executing a processing program.

[0120] The external weather management server 30 according to this embodiment includes a history database 31. The history database 31 is a database that stores past sunshine duration data acquired from observation stations (e.g., AMeDAS observation stations) installed throughout Japan. The sunshine duration data is, for example, data on sunshine duration included in the sunshine data.

[0121] The calculation unit 21 has a function of converting sunshine hours to calculate the expected amount of solar radiation. Here, expected solar radiation refers to the amount of solar radiation expected over a predetermined period (e.g., one month, one year, etc.). Specifically, the calculation unit 21 acquires sunshine hour data from the history database 31 of the external weather management server 30 and calculates the expected amount of solar radiation from the acquired sunshine hour data. In addition, the calculation unit 21 performs bias correction when calculating the expected amount of solar radiation from the sunshine hour data. Here, bias correction refers to a method of multiplying the error between the amount of solar radiation calculated at an observation point where weather data on sunshine hours is acquired and the amount of solar radiation at the power plant by a constant. Therefore, the power generation system 10 of this embodiment can improve the accuracy of estimating the expected amount of solar radiation even at points where solar radiation is not measured.

[0122] The calculation unit 21 has a function of converting the expected solar radiation to calculate the expected power generation amount. Here, the expected power generation amount refers to the power generation amount expected for a predetermined period (e.g., one month, one year, etc.). Specifically, the calculation unit 21 calculates the expected power generation amount to be generated by the power generation device 14 based on the expected solar radiation calculated from the sunshine duration data using a known method. The calculation unit 21 calculates the expected power generation amount from the expected solar radiation using, for example, the method described in Japanese Patent Application Laid-Open No. 2023-134273. The calculation unit 21 may also correct the expected power generation amount by multiplying it by an output reduction coefficient indicating the rate of output reduction of the power plant 40. Here, the output reduction coefficient is a constant diagnosed based on the equipment details, installation environment, etc. of the power plant 40, or is calculated from the coefficient of a regression line that fits the trend of the power generation amount. The equipment details, installation environment, etc. of the power plant 40 are examples of "information about the power plant equipment." The coefficient of the regression line that fits the trend of the power generation amount is an example of "information about the past power generation amount."

[0123] The calculation unit 21 has a function of calculating the expected solar radiation and expected power generation for a predetermined exceedance probability. Here, the exceedance probability refers to the probability that the expected solar radiation (or expected power generation) will be equal to or greater than a certain solar radiation (or power generation). Specifically, the calculation unit 21 calculates the expected solar radiation (or expected power generation) for the predetermined exceedance probability using the average value and standard deviation of the calculated expected solar radiation (or expected power generation). The predetermined exceedance probability may be, for example, 90% (hereinafter sometimes referred to as "P90"; the same applies to other probabilities), 75% (P75), 50% (P50), 25% (P25), or 10% (P10), but is not limited to these. For example, the calculation unit 21 calculates the expected solar radiation corresponding to P90 and P50 for April using the average value and standard deviation of the expected solar radiation for April calculated from sunshine duration data for the past 10 years or more. The expected solar radiation corresponding to P90 means that there is a 90% probability that the expected solar radiation will be exceeded, and the expected solar radiation corresponding to P50 means that there is a 50% probability that the expected solar radiation will be exceeded. Therefore, the expected solar radiation for P90 is a lower value than the expected solar radiation for P50.

[0124] The calculation unit 21 has a function of correcting the standard deviation for each month to a standard deviation on an annual basis. Specifically, when managing data for individual or multiple power plants on an annual basis, the calculation unit 21 calculates the exceedance probability by correcting the standard deviation and performing a weighted average based on the total or power generation capacity using the method described in JP 2023-134273 A.

[0125] The calculation unit 21 has a function of calculating the future trend of the amount of power generation. The calculation unit 21 calculates the future trend of the amount of power generation from the trend of the amount of power generation (not including the output derating coefficient) calculated from the amount of measured solar radiation. One method of calculating the trend, for example, is to find the slope of an approximating regression line from the moving average value of the amount of power generation over a long period, such as 10 years, and predict the future power generation trend from the slope. Note that the amount of measured solar radiation may use data that takes into account recent trends in climate change (for example, data from 2010 onwards). The future trend of the amount of power generation is an example of a "prediction of the amount of power generation."

[0126] The performance evaluation unit 29 has a function of evaluating the measured amount of solar radiation and the measured amount of power generation using an exceedance probability. Specifically, the performance evaluation unit 29 acquires the measured amount of solar radiation measured by the sunshine sensor 14A and the measured amount of power generation measured by the power generation amount measurement unit 28. The performance evaluation unit 29 then evaluates the acquired measured amount of solar radiation and the measured amount of power generation by comparing them with the expected amount of solar radiation and the expected amount of power generation with a predetermined exceedance probability calculated by the calculation unit 21. Note that the performance evaluation unit 29 may also calculate and evaluate the exceedance probability corresponding to the measured amount of solar radiation and the measured amount of power generation.

[0127] The performance evaluation unit 29 has a function of evaluating the equipment of the power plant 40. Specifically, the performance evaluation unit 29 evaluates the equipment of the power plant 40 based on an evaluation using the measured solar radiation and the exceedance probability of the measured power generation. For example, if the measured solar radiation is about P50 and the measured power generation is about P70, that is, if the measured power generation is less than the power generation possible for the measured solar radiation, the performance evaluation unit 29 evaluates that there is a possibility of an abnormality in the equipment of the power plant 40. Furthermore, if the measured solar radiation is about P70 and the measured power generation is about P70, that is, if the power generation possible for the measured solar radiation is equal to the measured power generation, the performance evaluation unit 29 evaluates that there is no problem with the equipment of the power plant 40. Note that the performance evaluation unit 29 may also evaluate the climate of the location of the power plant 40. For example, when the measured amount of solar radiation is about P70 and the measured amount of power generation is about P70, the performance evaluation unit 29 can make the following evaluation: That is, if the amount of power generation that can be generated for the measured amount of solar radiation is equal to the measured amount of power generation, but the measured amount of power generation is less than the standard value for the expected amount of power generation (i.e., the value of P50), it may be evaluated that there is no problem with the equipment of the power plant 40 and that the decrease in power generation is due to the decrease in solar radiation.

[0128] The information management unit 26 has a function of managing data on the measured amount of solar radiation and the measured amount of power generation. Specifically, the information management unit 26 acquires data on the measured amount of solar radiation from the sunshine sensor 14A and acquires data on the measured amount of power generation from the power generation amount measurement unit 28, and stores these in the history database 32 (see FIG. 3). Furthermore, the information management unit 26 notifies the user by issuing an alert if the acquired data is missing or missing. Then, when the information management unit 26 has accumulated data for one month or one year, the information management unit 26 adds up the data to actual values for each month or year and makes them available to each functional unit of the power generation system 10.

[0129] The information management unit 26 prepares the following information as notification contents. (Information 6) Measured power generation (measured and available power generation) (Information 7) Measured solar radiation (measured and available solar radiation) (Information 8) Expected power generation and probability of exceedance (calculated from statistical data) (Information 9) Expected solar radiation and exceedance probability (calculated from statistical data) (Information 10) Abnormality judgment (probability of exceeding measured power generation < probability of exceeding measured solar radiation) The exceedance probability used in (Information 8) and (Information 9) may be the exceedance probability calculated by correcting the standard deviation in the calculation unit 21 using the method described in JP 2023-134273 A. Also, (Information 10) indicates the content evaluated by the performance evaluation unit 29.

[0130] The output unit 36 has a function of outputting notification content. Specifically, the output unit 36 displays, on the operation / display panel 16A, time-series information indicating transition states of (information 6) to (information 9) and an evaluation based on the determination of (information 10). The output unit 36 displays, for example, time-series graphs (see FIGS. 11 to 16) and an evaluation (see FIG. 17), which will be described later. The output unit 36 also displays, on the operation / display panel 16A, a time-series graph (see FIG. 19), which will be described later, indicating a future trend in the amount of power generation. The output unit 36 can output multiple time-series graphs and evaluations simultaneously. For example, the output unit 36 displays, on the operation / display panel 16A, the time-series graph of FIG. 11, the time-series graph of FIG. 12, and the evaluation of FIG. 17, which will be described later.

[0131] (Time series graph) Next, time series graphs, which are examples of (Information 6) to (Information 9) displayed on the operation / display panel 16A, will be described with reference to Figures 11 to 16. Note that components common to each time series graph are given the same reference numerals and detailed description thereof will be omitted.

[0132] 11 is an example of a time series graph E10 that displays the measured power generation amount and expected power generation amount of the power plant 40 on a monthly basis according to the second embodiment. The time series graph E10 of this embodiment is a graph with the monthly time series on the horizontal axis and the power generation amount on the vertical axis. The time series graph E10 includes a polygonal line E11 that indicates the measured power generation amount, polygonal lines E12, E13, E14, E15, and E16 that indicate the expected power generation amount corresponding to a predetermined exceedance probability, and an auxiliary line AL that indicates the range of the exceedance probability.

[0133] The polygonal line E11 is a polygonal line connecting points that indicate the total value of the measured power generation amount for each month. In this embodiment, the polygonal line E11 is, as an example, displayed as a thick solid line from April 2020 to March 2023. April 2020 to March 2023 is an example of a "predetermined period."

[0134] The polygonal line E12 indicates the expected power generation amount corresponding to P10. The polygonal line E12 is a polygonal line connecting the expected power generation amount for each month corresponding to P10 calculated by the calculation unit 21. In this embodiment, the polygonal line E12 is, as an example, displayed as a dashed line with a peak value decreasing every year from April 2020 to March 2024. In addition, the polygonal line E13 indicates the expected power generation amount corresponding to P25, the polygonal line E14 indicates the expected power generation amount corresponding to P50, the polygonal line E15 indicates the expected power generation amount corresponding to P75, and the polygonal line E16 indicates the expected power generation amount corresponding to P90. The polygonal lines E13 to E16 are similar to the polygonal line E12, and therefore detailed description thereof will be omitted. In addition, the polygonal line E14 in this embodiment is displayed as a thick dashed line.

[0135] The auxiliary line AL is a straight line connecting the expected power generation amounts corresponding to P10, P25, P50, P75, and P90 for each month. In this embodiment, the auxiliary line AL is shown as a dashed line, for example.

[0136] In this way, by displaying the polygonal line E11, which indicates the measured power generation amount, together with the polygonal lines E12 to E16, which indicate the expected power generation amount corresponding to a predetermined exceedance probability, the measured power generation amount and the expected power generation amount for each month can be compared. Also, by displaying the expected power generation amount corresponding to P50 as a bold dashed line, the measured power generation amount and the standard value of the expected power generation amount can be easily compared. Note that the polygonal lines E12 to E16 are displayed with their peak values decreasing year by year, indicating that the expected power generation amount is gradually decreasing as the output of the power plant 40 decreases.

[0137] 12 is an example of a time series graph S10 that displays the measured amount of solar radiation and the expected amount of solar radiation at the power plant 40 on a monthly basis according to the second embodiment. The time series graph S10 of this embodiment is a graph with the monthly time series on the horizontal axis and the amount of solar radiation on the vertical axis. The time series graph S10 includes a polygonal line S11 that indicates the measured amount of solar radiation, polygonal lines S12, S13, S14, S15, and S16 that indicate the expected amount of solar radiation corresponding to a predetermined exceedance probability, and an auxiliary line AL.

[0138] The polygonal line S11 is a polygonal line connecting points indicating the total value of the measured solar radiation for each month. In this embodiment, the polygonal line S11 is displayed as a thick solid line from April 2020 to March 2023, as an example.

[0139] The polygonal line S12 indicates the expected solar radiation corresponding to P10. The polygonal line S12 is a polygonal line connecting the expected solar radiation for each month corresponding to P10 calculated by the calculation unit 21. In this embodiment, the polygonal line S12 is displayed as a dashed line from April 2020 to March 2024, for example. In addition, the polygonal line S13 indicates the expected solar radiation corresponding to P25, the polygonal line S14 indicates the expected solar radiation corresponding to P50, the polygonal line S15 indicates the expected solar radiation corresponding to P75, and the polygonal line S16 indicates the expected solar radiation corresponding to P90. The polygonal lines S13 to S16 are similar to the polygonal line S12, and therefore detailed description thereof will be omitted. In addition, the polygonal line S14 in this embodiment is displayed as a thick dashed line.

[0140] In this way, by displaying the polygonal line S11 showing the measured solar radiation amount together with the polygonal lines S12 to S16 showing the expected solar radiation amount corresponding to a predetermined exceedance probability, the measured solar radiation amount for each month and the expected solar radiation amount for each month can be displayed in a comparable manner. In addition, by displaying the expected solar radiation amount corresponding to P50 as a bold dashed line, the measured solar radiation amount and the standard value of the expected solar radiation amount can be displayed in an easily comparable manner.

[0141] 13 is an example of a time series graph E20 that displays the measured power generation amount and expected power generation amount of the power plant 40 on an annual basis according to the second embodiment. The time series graph E20 of this embodiment is a graph with the yearly time series on the horizontal axis and the power generation amount on the vertical axis. The time series graph E20 is configured to include a broken line E21 that indicates the measured power generation amount, straight lines E22, E23, E24, E25, and E26 that indicate the expected power generation amount corresponding to a predetermined exceedance probability, and an auxiliary line AL that indicates the range of the exceedance probability.

[0142] The polygonal line E21 is a polygonal line connecting points indicating the total value of the measured power generation amount for each year. In this embodiment, the polygonal line E21 is displayed as a thick solid line from 2017 to 2023, for example.

[0143] Line E22 indicates the expected power generation amount corresponding to P10. Line E22 is a line showing the expected annual power generation amount corresponding to P10 calculated by the calculation unit 21. In this embodiment, line E22 is, as an example, a dashed line that slopes gently downward from 2017 to 2030. Line E23 indicates the expected power generation amount corresponding to P25, line E24 indicates the expected power generation amount corresponding to P50, line E25 indicates the expected power generation amount corresponding to P75, and line E26 indicates the expected power generation amount corresponding to P90. Lines E23 to E26 are similar to line E22, and therefore detailed description thereof will be omitted. Lines E23 to E26 may use the exceedance probability calculated by correcting the standard deviation in the calculation unit 21 using the method described in JP 2023-134273 A. Line E24 in this embodiment is displayed as a thick dashed line.

[0144] In this way, by displaying the broken line E21, which shows the measured power generation, alongside the straight lines E22 to E26, which show the expected power generation corresponding to a specified exceedance probability, the measured power generation for each year and the expected power generation for the year can be compared. Furthermore, by displaying the expected power generation corresponding to P50 as a bold dashed line, the measured power generation for each year and the standard value of the expected power generation for the year can be easily compared. Furthermore, the straight lines E22 to E26 are displayed in a gradual downward sloping pattern, indicating that the expected power generation will gradually decrease due to the decrease in output of power plant 40 from 2017 to 2030.

[0145] 14 is an example of a time series graph S20 that displays the measured amount of solar radiation and the expected amount of solar radiation at the power plant 40 on an annual basis according to the second embodiment. The time series graph S20 of this embodiment is a graph with the yearly time series on the horizontal axis and the amount of solar radiation on the vertical axis. The time series graph S20 includes a broken line S21 that indicates the measured amount of solar radiation, straight lines S22, S23, S24, S25, and S26 that indicate the expected amount of solar radiation corresponding to a predetermined exceedance probability, and an auxiliary line AL.

[0146] The polygonal line S21 is a polygonal line connecting points indicating the total value of the measured solar radiation for each year. In this embodiment, the polygonal line S21 is displayed as a thick solid line from 2017 to 2023, for example.

[0147] Line S22 indicates the expected solar radiation corresponding to P10. Line S22 is a line indicating the expected annual solar radiation corresponding to P10 calculated by the calculation unit 21. In this embodiment, line S22 is, as an example, a dashed line displayed parallel to the horizontal axis from April 2017 to 2025. Line S23 indicates the expected solar radiation corresponding to P25, line S24 indicates the expected solar radiation corresponding to P50, line S25 indicates the expected solar radiation corresponding to P75, and line S26 indicates the expected solar radiation corresponding to P90. Lines S23 to S26 are similar to line S22, and therefore detailed description thereof will be omitted. Lines S23 to S26 may use exceedance probabilities calculated by correcting the standard deviation in the calculation unit 21 using the method described in JP 2023-134273 A. Line S24 in this embodiment is displayed as a thick dashed line.

[0148] In this way, by displaying the broken line S21 showing the measured solar radiation amount together with the straight lines S22 to S26 showing the expected solar radiation amount corresponding to a predetermined exceedance probability, the measured solar radiation amount for each year and the expected solar radiation amount for the year can be displayed in a comparable manner. In addition, by displaying the expected solar radiation amount corresponding to P50 as a bold dashed line, the measured solar radiation amount for each year and the standard value of the expected solar radiation amount for the year can be displayed in an easily comparable manner.

[0149] FIG. 15 is an example of a time series graph E30 that displays the sum of measured power generation and the sum of expected power generation of multiple power plants 40 on an annual basis according to the second embodiment. The time series graph E30 of this embodiment is a graph with the time series on an annual basis on the horizontal axis and the power generation amount on the vertical axis. The time series graph E30 includes a polygonal line E31 that indicates the sum of measured power generation, polygonal lines E32, E33, E34, E35, and E36 that indicate the sum of expected power generation corresponding to a predetermined exceedance probability, and an auxiliary line AL that indicates the range of the exceedance probability. The sum of measured power generation is an example of the "total power generation." The sum of expected power generation is an example of the "total expected power generation."

[0150] The polygonal line E31 is a polygonal line connecting points indicating the total amount of power generation measured for each year at a plurality of power plants 40. In this embodiment, the polygonal line E31 is displayed as a thick solid line from 2010 to 2030, as an example.

[0151] The polygonal line E32 indicates the total expected power generation corresponding to P10. The polygonal line E32 is a polygonal line showing the total expected power generation corresponding to P10 for each year at multiple power plants 40. In this embodiment, the polygonal line E32 is displayed as a dashed line from 2010 to 2055, for example. The polygonal line E32 is displayed as an upward slope from 2014 to 2021, a gentle downward slope from 2021 to 2032, and a downward slope from 2032 to 2038. The polygonal line E33 indicates the total expected power generation corresponding to P25, the polygonal line E34 indicates the total expected power generation corresponding to P50, the polygonal line E35 indicates the total expected power generation corresponding to P75, and the polygonal line E36 indicates the total expected power generation corresponding to P90. The polygonal lines E33 to E36 are similar to the polygonal line E32, and therefore detailed description thereof will be omitted. For the polygonal lines E33 to E36, the exceedance probability calculated by correcting the standard deviation in the calculation unit 21 according to the method described in JP 2023-134273 A may be used. Note that the polygonal line E34 in this embodiment is displayed as a thick dashed line.

[0152] In this way, by displaying line E31, which shows the total measured power generation, alongside lines E32-E36, which show the total expected power generation corresponding to a given exceedance probability, the total measured power generation and the total expected power generation for each year can be compared. Furthermore, by displaying the total expected power generation corresponding to P50 as a bold dashed line, the total measured power generation and the standard value of the total expected power generation for each year can be easily compared. Lines E32-E36 are displayed in an upward sloping pattern, indicating, for example, that the total expected power generation increased from 2014 to 2021 due to the addition of additional power plants 40. Lines E32-E36 are displayed in a gradual downward sloping pattern, indicating that the number of registered power plants 40 did not change significantly from 2021 to 2032, but the total expected power generation gradually decreased due to the decline in output of several power plants 40. Furthermore, the broken lines E32 to E36 are displayed in a downward sloping pattern, indicating that the total expected power generation is decreasing due to the removal of some power plants 40 from the list between 2032 and 2038.

[0153] 16 is an example of a time series graph S30 according to the second embodiment, which displays the average values of measured solar radiation and average values of expected solar radiation on an annual basis for a plurality of power plants 40. The time series graph S30 of this embodiment is a graph with the time series on an annual basis on the horizontal axis and the solar radiation on the vertical axis. The time series graph S30 includes a polygonal line S31 indicating the average value of measured solar radiation, polygonal lines S32, S33, S34, S35, and S36 indicating average values of expected solar radiation corresponding to a predetermined exceedance probability, and an auxiliary line AL.

[0154] The polygonal line S31 is a polygonal line connecting points indicating the average values of the solar radiation measured for each year at a plurality of power plants 40. In this embodiment, the polygonal line S31 is displayed as a thick solid line from 2000 to 2020, as an example.

[0155] The polygonal line S32 indicates the average value of the expected solar radiation corresponding to P10. The polygonal line S32 is a polygonal line showing the average value of the expected solar radiation for each year corresponding to P10 calculated by the calculation unit 21. In this embodiment, the polygonal line S32 is, as an example, a dashed line that slopes downward to the right from 2000 to 2024. The polygonal line S33 indicates the expected solar radiation corresponding to P25, the polygonal line S34 indicates the expected solar radiation corresponding to P50, the polygonal line S35 indicates the expected solar radiation corresponding to P75, and the polygonal line S36 indicates the expected solar radiation corresponding to P90. The polygonal lines S33 to S36 are similar to the polygonal line S32, and therefore detailed description thereof will be omitted. The polygonal lines S33 to S36 may use a value obtained by weighting the exceedance probability calculated by the calculation unit 21 by correcting the standard deviation using the method described in JP 2023-134273 A, using the power generation capacity of the power plant. In this embodiment, the broken line S34 is displayed as a thick dashed line.

[0156] In this way, by displaying the polygonal line S31, which indicates the average value of measured solar radiation, together with the polygonal lines S32 to S36, which indicate the average value of expected solar radiation corresponding to a predetermined exceedance probability, the average value of measured solar radiation for each year and the average value of expected solar radiation for each year can be compared. Furthermore, by displaying the average value of expected solar radiation corresponding to P50 as a bold dashed line, the average value of measured solar radiation for each year and the standard average value of expected solar radiation for each year can be easily compared. The polygonal lines S32 to S36 are displayed in a downward sloping pattern, which indicates, for example, that the average value of expected solar radiation decreased due to the removal of a power plant 40 with high solar radiation from 2004 to 2005. Furthermore, although not shown, the polygonal line S32 is displayed in an upward sloping pattern, which indicates that the average value of expected solar radiation increased due to the addition of a power plant 40 with high solar radiation.

[0157] (rating display) Next, evaluation, which is an example of the information (information 10) displayed on the operation / display panel 16A, will be described with reference to FIG.

[0158] 17 is a diagram showing an example of a screen display showing evaluations of measured power generation and measured solar radiation according to the second embodiment. The power generation system 10 of this embodiment displays an evaluation period, an evaluation of measured power generation using the exceedance probability, an evaluation of measured solar radiation using the exceedance probability, and an evaluation of the facilities of the power plant 40. The power generation system 10 may display an evaluation of either the measured power generation or the measured solar radiation, or may display an evaluation of the climate of the location of the power plant 40.

[0159] As shown in Figure 17(A), if the evaluation by the performance evaluation unit 29 is "exceedance probability of measured power generation ≥ exceedance probability of measured solar radiation," the evaluation period, the evaluation of measured power generation using the exceedance probability, and the evaluation of measured solar radiation using the exceedance probability are displayed. If the measured power generation is about P70 and the measured solar radiation is about P70, for example, a message such as "The performance for month XX, 2023, was as follows. Power generation: about P70 of expected power generation. Solar radiation: about P70 of expected solar radiation. 'Power generation has been lower than P50, but solar radiation is about the same.'" is displayed.

[0160] As shown in FIG. 17(B), if the evaluation by the performance evaluation unit 29 is "Exceedance probability of measured power generation < Exceedance probability of measured solar radiation," an alert display, the evaluation period, the evaluation of measured power generation using the exceedance probability, the evaluation of measured solar radiation using the exceedance probability, and an evaluation of the power plant 40's facilities are displayed. For example, if the measured power generation is approximately P70 and the measured solar radiation is approximately P50, a message such as "Alert: Actual results for month ▲ of 2023 were as follows: Power generation: Approximately P70 of expected power generation Solar radiation: Approximately P50 of expected solar radiation 'The actual power generation has been trending lower than the expected solar radiation. Please check for any abnormalities at the power plant.'" is displayed. The background color of the evaluation shown in FIG. 17(B) is displayed in a color (e.g., yellow) different from the background color of the evaluation shown in FIG. 17(A) (e.g., white).

[0161] (Future trends in power generation) 18 is an example of a time series graph E40 displaying a future trend in the amount of power generated by a power plant 40 according to the second embodiment. The time series graph E40 of this embodiment is a graph with the horizontal axis representing a time series in years and the vertical axis representing the amount of power generated integrated over the year. The time series graph E40 includes a polygonal line E41 showing the amount of power generated, a polygonal line E42 showing the moving average of the amount of power generated, a straight line E43 showing a regression line approximating the moving average of the measured amount of power generated, and a straight line E44 showing the predicted amount of power generated. The straight line E44 is also displayed in an area E45 that displays a predicted amount of power generation in the future.

[0162] The polygonal line E41 is a polygonal line connecting points indicating the total value of the amount of power generated for each year calculated from the amount of measured solar radiation. In this embodiment, the polygonal line E41 is displayed as a solid line from 1990 to 2023, as an example.

[0163] The polygonal line E42 is a polygonal line that connects the 10-year moving average values of the amount of power generation calculated from the amount of measured solar radiation. In this embodiment, the polygonal line E42 is displayed as a dashed line from 2006 to 2023.

[0164] Line E43 represents a regression line that approximates a 10-year moving average of the amount of power generation calculated from the amount of measured solar radiation. Line E43 in this embodiment is a solid line that rises to the right from 1990 to 2023. Line E44 is a line that represents the predicted amount of power generation in the future. Line E44 in this embodiment is a dotted line that rises to the right from 2023 to 2030. Line E43 and line E44 are lines that use the slope of the regression line calculated by the calculation unit 21.

[0165] In this way, by displaying both the polygonal line E41, which indicates the amount of power generation calculated from the measured amount of solar radiation, and the straight line E44, which indicates the predicted amount of power generation, the amount of power generation calculated from the measured amount of solar radiation for each year and the future trend of the amount of power generation can be compared. Also, a polygonal line E42, which indicates a 10-year moving average, is displayed, and a straight line E43, which indicates a regression line approximating the 10-year moving average, is displayed in an upward sloping manner to the right, thereby indicating that the amount of power generation has been on an upward trend from 2006 to 2023, for example. Furthermore, by displaying the straight line E43, which indicates a regression line approximating the 10-year moving average, and the straight line E44, which indicates the predicted amount of power generation, in an upward sloping manner to the right, for example, it indicates that the amount of power generation up to 2023 is on an upward trend, and therefore the future amount of power generation is also on an upward trend. Although not shown, if the straight line E43, which indicates a regression line approximating the 10-year moving average, and the straight line E44, which indicates the predicted amount of power generation, are displayed in a downward sloping manner to the right, it indicates that the future amount of power generation is on a downward trend.

[0166] (flowchart) Fig. 19 is a flowchart showing an example of the flow of a performance display process for displaying performance data of the power plant 40 according to the second embodiment. Fig. 20 is a flowchart showing an example of the flow of the performance display process following Fig. 19. The performance display process is executed, for example, by a user operating the operation / display panel 16A.

[0167] 19, the CPU 10A acquires and stores data on the amount of solar radiation and the amount of power generated. For example, the CPU 10A acquires data on the amount of solar radiation and the amount of power generated for each target power plant 40 in 30-minute increments on the previous day, and continues to store the data for each target power plant 40.

[0168] In step 202, CPU 10A determines whether or not there is a loss or missing data. If CPU 10A determines that there is a loss or missing data (step 202: Y), the process proceeds to step 204. On the other hand, if CPU 10A determines that there is no loss or missing data (step 202: N), the process proceeds to step 206.

[0169] In step 204, CPU 10A issues an alert for missing or missing data. Then, CPU 10A proceeds to step 206.

[0170] In step 206, CPU 10A branches the process depending on the unit to be displayed and managed. If the unit to be displayed and managed is the monthly value for each power plant 40 (step 206: each power plant (monthly value)), CPU 10A proceeds to step 208. If the unit to be displayed and managed is the yearly value for each power plant 40 (step 206: each power plant (yearly value)), CPU 10A proceeds to step 212. If the unit to be displayed and managed is the yearly value for all power plants 40 (step 206: all power plants (yearly value)), CPU 10A proceeds to step 218.

[0171] In step 208, CPU 10A determines whether one month's worth of measured solar radiation and power generation data has been accumulated. If CPU 10A determines that data has been accumulated (step 208: Y), the process proceeds to step 210. On the other hand, if CPU 10A determines that data has not been accumulated (step 208: N), the process proceeds to step 216.

[0172] In step 210, CPU 10A integrates the data of the measured amount of solar radiation and the measured amount of power generation for one month into the actual values. Specifically, CPU 10A integrates the accumulated data for one month into the actual values of the corresponding power plant 40.

[0173] In step 212, CPU 10A determines whether one year's worth of measured solar radiation and power generation data has been accumulated. If CPU 10A determines that data has been accumulated (step 212: Y), the process proceeds to step 214. On the other hand, if CPU 10A determines that data has not been accumulated (step 212: N), the process proceeds to step 216.

[0174] In step 214, CPU 10A integrates the data of the measured amount of solar radiation and the measured amount of power generation for one year into the actual values. Specifically, CPU 10A integrates the accumulated data for one year into the actual values of the corresponding power plant 40.

[0175] In step 216, the CPU 10A executes an expected value calculation process, which will be described later, for each power plant 40. By performing the expected value calculation process for each power plant 40, the CPU 10A calculates the expected power generation amount and expected solar radiation amount for each power plant 40 that correspond to a predetermined exceedance probability.

[0176] In step 218, CPU 10A determines whether or not data for all registered power plants 40 has been acquired. If CPU 10A determines that data for all registered power plants 40 has been acquired (step 218: Y), it proceeds to step 220. On the other hand, if CPU 10A determines that data for all registered power plants 40 has not been acquired (step 218: N), it returns to step 200.

[0177] In step 220, CPU 10A branches the process depending on the index to be displayed. If the index to be displayed is the amount of power generation (step 220: amount of power generation), CPU 10A proceeds to step 222. On the other hand, if the index to be displayed is the amount of solar radiation (step 220: amount of solar radiation), CPU 10A proceeds to step 226.

[0178] In step 222, CPU 10A determines whether one year's worth of measured power generation data has been accumulated. If CPU 10A determines that data has been accumulated (step 222: Y), the process proceeds to step 224. On the other hand, if CPU 10A determines that data has not been accumulated (step 222: N), the process proceeds to step 230.

[0179] In step 224, CPU 10A adds up the data of the measured power generation amount for one year of each power plant 40 and integrates it into an actual value. Specifically, CPU 10A integrates the total sum of the measured power generation amount for one year of all registered power plants 40 into an actual value.

[0180] In step 226, CPU 10A determines whether one year's worth of measured solar radiation data has been accumulated. If CPU 10A determines that data has been accumulated (step 226: Y), the process proceeds to step 228. On the other hand, if CPU 10A determines that data has not been accumulated (step 226: N), the process proceeds to step 230.

[0181] In step 228, CPU 10A calculates a weighted average of the data on the amount of solar radiation measured at each power plant 40 for one year by the power generation capacity of each power plant 40, and adds the weighted average to the actual value. Specifically, CPU 10A adds the average value of the amount of solar radiation measured, calculated by calculation unit 21 based on the amount of solar radiation for one year at all registered power plants 40, to the actual value.

[0182] In step 230, the CPU 10A executes the expected value calculation process, which will be described later, for all the power plants 40. By the expected value calculation process for all the power plants 40, the CPU 10A calculates the expected power generation amount and expected solar radiation amount for all the power plants 40 that correspond to a predetermined exceedance probability.

[0183] In step 232, the CPU 10A displays time series graphs of the measured power generation amount and the expected power generation amount, as well as time series graphs of the measured solar radiation amount and the expected solar radiation amount. For example, when displaying monthly values for each power plant 40, the CPU 10A displays the time series graphs of Figures 11 and 12. When displaying yearly values for each power plant 40, the CPU 10A displays the time series graphs of Figures 13 and 14. When displaying yearly values for all power plants 40, the CPU 10A displays the time series graphs of Figures 15 and 16. Note that the CPU 10A may display only one of the time series graphs of the measured power generation amount and the expected power generation amount, and the time series graphs of the measured solar radiation amount and the expected solar radiation amount.

[0184] In step 234 of FIG. 20, the CPU 10A evaluates the measured amount of solar radiation and the measured amount of power generation using the exceedance probability.

[0185] In step 236, CPU 10A determines whether the evaluation of the measured power generation amount is lower than the evaluation of the measured solar radiation amount. If CPU 10A determines that the evaluation is lower (step 236: Y), it proceeds to step 240. If CPU 10A determines that the evaluation is not lower (step 236: N), it proceeds to step 238.

[0186] In step 238, CPU 10A displays the evaluation of the measured amount of solar radiation and the measured amount of power generation. As an example, CPU 10A displays the message shown in Fig. 17(A). Then, CPU 10A ends the performance display process.

[0187] In step 240, CPU 10A displays an evaluation of the measured amount of solar radiation and the measured amount of power generation, and an alert regarding the equipment of power plant 40. As an example, CPU 10A displays the message shown in Fig. 17(B). Then, CPU 10A ends the performance display process.

[0188] 21 is a flowchart showing an example of the flow of the expected value calculation process for each power plant 40 according to the second embodiment. The expected value calculation process for each power plant 40 is executed, for example, in step 216 in FIG.

[0189] 21, CPU 10A acquires sunshine duration data for the past 10 years. CPU 10A acquires sunshine duration data for the past 10 years observed at a meteorological observation station (e.g., an AMeDAS observation station) located closest to power plant 40, for example.

[0190] In step 252, CPU 10A calculates the average value and standard deviation of the expected amount of solar radiation from the sunshine duration included in the sunshine duration data. Specifically, CPU 10A converts the sunshine duration to solar radiation, performs bias correction on the converted solar radiation to match the location of power plant 40, and calculates the average value and standard deviation of the expected amount of solar radiation.

[0191] In step 254, the CPU 10A calculates the average value and standard deviation of the expected power generation from the calculated expected amount of solar radiation. Specifically, the CPU 10A converts the expected amount of solar radiation into the expected power generation, and calculates the average value and standard deviation of the expected power generation.

[0192] In step 256, CPU 10A branches the process depending on the unit for calculating the expected value. If the unit for calculating the expected value is a monthly value (step 256: monthly value), CPU 10A proceeds to step 258. On the other hand, if the unit for calculating the expected value is an annual value (step 256: annual value), CPU 10A proceeds to step 260.

[0193] In step 258, CPU 10A calculates the expected solar radiation and expected power generation amount for each month corresponding to a predetermined exceedance probability using the monthly average value and standard deviation. Then, CPU 10A ends the expected value calculation process for each power plant 40.

[0194] In step 260, CPU 10A corrects the standard deviation for each month in accordance with the yearly coefficient of variation. Specifically, CPU 10A corrects the standard deviation of the expected solar radiation for each month by multiplying the expected solar radiation for each month by the coefficient of variation of the expected solar radiation for each power plant 40. CPU 10A also corrects the standard deviation of the expected power generation for each month by multiplying the expected power generation for each month by the coefficient of variation of the expected power generation for each power plant 40.

[0195] In step 262, CPU 10A calculates the expected amount of solar radiation and expected amount of power generation for each month corresponding to a predetermined exceedance probability, using the average value for each month and the corrected standard deviation.

[0196] In step 264, CPU 10A sums up the calculated expected insolation and expected power generation for each month to calculate the annual expected insolation and expected power generation corresponding to a predetermined exceedance probability. Specifically, CPU 10A sums up the calculated expected insolation for each month for each predetermined exceedance probability to calculate the annual expected insolation for the predetermined exceedance probability. CPU 10A also sums up the calculated expected power generation for each month for each predetermined exceedance probability to calculate the annual expected power generation corresponding to the predetermined exceedance probability. Then, CPU 10A ends the expected value calculation process for each power plant 40.

[0197] 22 is a flowchart showing an example of the flow of the expected value calculation process for all power plants 40 according to the second embodiment. The expected value calculation process for each power plant 40 is executed, for example, in step 230 of FIG.

[0198] Steps 270 to 274 in FIG. 22 are similar to steps 250 to 254 in FIG. 21, and therefore detailed description thereof will be omitted.

[0199] 22, CPU 10A determines whether calculations have been made for all registered power plants 40. If CPU 10A determines that calculations have been made for all registered power plants 40 (step 276: Y), CPU 10A proceeds to step 278. On the other hand, if CPU 10A determines that calculations have not been made for all registered power plants 40 (step 276: N), CPU 10A returns to step 270.

[0200] In step 278, CPU 10A branches the process depending on the index to be calculated. If the index to be calculated is the amount of power generated (step 278: amount of power generated), CPU 10A On the other hand, if the index to be calculated is the amount of solar radiation (step 278: amount of solar radiation), CPU 10A proceeds to step 286.

[0201] In step 280, CPU 10A corrects the standard deviation of the expected power generation amount for each month of each power plant 40 in accordance with the annual coefficient of variation of all power plants 40. Specifically, CPU 10A corrects the standard deviation of the expected power generation amount for each month by multiplying the expected power generation amount for each month of each power plant 40 by the annual coefficient of variation of the expected power generation amount for all power plants 40.

[0202] In step 282, the CPU 10A uses the monthly average value and the corrected standard deviation to calculate the expected annual power generation amount corresponding to the predetermined exceedance probability for each power plant 40. Specifically, the CPU 10A adds up the calculated expected power generation amounts for each month for each predetermined exceedance probability to calculate the expected annual power generation amount corresponding to the predetermined exceedance probability for each power plant 40.

[0203] In step 284, CPU 10A adds up the annual expected power generation amounts of each power plant 40 to calculate the annual expected power generation amount corresponding to the predetermined exceedance probability for all power plants 40. Specifically, CPU 10A adds up the calculated annual expected power generation amounts of each power plant 40 for each predetermined exceedance probability to calculate the annual expected power generation amount corresponding to the predetermined exceedance probability for all power plants 40. Then, CPU 10A ends the expected value calculation process for all power plants 40.

[0204] In step 286, CPU 10A corrects the standard deviation of the expected solar radiation for each month of each power plant 40 in accordance with the annual coefficient of variation for all power plants 40. Specifically, CPU 10A corrects the standard deviation of the expected solar radiation for each month by multiplying the expected solar radiation for each month of each power plant 40 by the annual coefficient of variation for the expected solar radiation for all power plants 40.

[0205] In step 288, CPU 10A uses the monthly average value and the corrected standard deviation to calculate the expected annual amount of solar radiation corresponding to the predetermined exceedance probability for each power plant 40. Specifically, CPU 10A adds up the calculated expected monthly amount of solar radiation for each predetermined exceedance probability to calculate the expected annual amount of solar radiation corresponding to the predetermined exceedance probability for each power plant 40.

[0206] In step 290, CPU 10A weights and averages the annual expected insolation for each power plant 40 in accordance with the power generation capacity of each power plant 40, and calculates the annual expected insolation corresponding to the predetermined exceedance probability for all power plants 40. Specifically, CPU 10A weights and averages the calculated annual expected insolation for each power plant 40 in accordance with the ratio of the power generation capacity of each power plant 40 for each predetermined exceedance probability, and calculates the average value of the annual expected insolation corresponding to the predetermined exceedance probability for all power plants 40. CPU 10A then terminates the expected value calculation process for all power plants 40.

[0207] 23 is a flowchart showing an example of the flow of a trend display process for displaying the future trend of expected power generation according to Embodiment 2. The trend display process is executed, for example, by the user operating the operation / display panel 16A.

[0208] 23, the CPU 10A acquires data on the amount of measured solar radiation. Specifically, the CPU 10A acquires the data on the amount of measured solar radiation from the history database 32 (see FIG. 3).

[0209] In step 302, CPU 10A calculates the amount of power generation from the acquired measured solar radiation data. Specifically, CPU 10A calculates the amount of power generation from the acquired measured solar radiation data in step 302. CPU 10A calculates the amount of power generation by year from 1990 to 2023, for example.

[0210] In step 304, CPU 10A calculates a moving average value of the amount of power generation over 10 years based on the calculated amount of power generation. For example, CPU 10A calculates a moving average value of the amount of power generation over 10 years from 2006 to 2023.

[0211] In step 306, CPU 10A calculates the slope of a regression line that approximates the calculated moving average value. For example, CPU 10A calculates the slope of a regression line that approximates the calculated moving average value of the power generation amount from 2006 to 2023.

[0212] In step 308, CPU 10A displays the future trend of the power generation amount based on the calculated slope of the regression line. For example, if the calculated slope of the regression line is a positive value, CPU 10A evaluates that the future trend of the power generation amount is an upward trend and displays a message saying, "As a result of analyzing data from the past few years, the power generation amount is likely to increase by ●% next year." Then, CPU 10A ends the trend display process. Note that CPU 10A may also display, for example, a time series graph (see FIG. 18) showing the future trend of the power generation amount.

[0213] (Summary of the second embodiment) The power generation system 10 of this embodiment displays on the operation / display panel 16A a time series graph of the measured power generation amount measured at one or more power plants 40 and a time series graph of the expected power generation amount with a predetermined exceedance probability based on sunshine duration data for the past 10 years or more at the location of the power plants 40. Therefore, according to the power generation system 10 of this embodiment, it is possible to evaluate the performance (e.g., power generation amount) of the power plants 40 using the exceedance probability calculated from past weather data.

[0214] The power generation system 10 of this embodiment displays on the operation / display panel 16A a time series graph of the measured solar radiation measured at one or more power plants 40 and a time series graph of the expected solar radiation with a predetermined exceedance probability based on sunshine duration data for the past 10 years or more at the location of the power plant 40. Therefore, the power generation system 10 of this embodiment can evaluate the solar radiation at the power plant 40 using the exceedance probability calculated from past weather data.

[0215] The power generation system 10 of this embodiment displays a time series graph E10 (see FIG. 11) that displays the measured power generation amount and expected power generation amount on a monthly basis of the power plant 40. Therefore, according to the power generation system 10 of this embodiment, the time series graph of the measured power generation amount on a monthly basis can be compared with the time series graph of the expected power generation amount with a predetermined exceedance probability on a monthly basis, and therefore the transition of the measured power generation amount on a monthly basis can be visually evaluated.

[0216] The power generation system 10 of this embodiment displays a time series graph S10 (see FIG. 12 ) that displays the measured solar radiation and expected solar radiation of the power plant 40 on a monthly basis. Therefore, the power generation system 10 of this embodiment can compare the time series graph of the measured solar radiation on a monthly basis with the time series graph of the expected solar radiation with a predetermined exceedance probability on a monthly basis, allowing visual evaluation of the trend in the measured power generation amount on a monthly basis. Furthermore, the power generation system 10 of this embodiment can compare the time series graph E10 that displays the measured solar radiation and expected solar radiation of the power plant 40 on a monthly basis with the time series graph S10 that displays the measured solar radiation and expected solar radiation of the power plant 40 on a monthly basis, allowing visual evaluation.

[0217] The power generation system 10 of this embodiment displays a time series graph E20 (see FIG. 13) that displays the measured power generation amount and expected power generation amount on an annual basis of the power plant 40. Therefore, according to the power generation system 10 of this embodiment, the time series graph of the measured power generation amount on an annual basis can be compared with the time series graph of the expected power generation amount with a predetermined exceedance probability on an annual basis, and therefore the transition of the measured power generation amount on an annual basis can be visually evaluated.

[0218] The power generation system 10 of this embodiment displays a time series graph S20 (see FIG. 14 ) that displays the measured solar radiation and expected solar radiation of the power plant 40 on an annual basis. Therefore, the power generation system 10 of this embodiment can compare the time series graph of the measured solar radiation on an annual basis with the time series graph of the expected solar radiation with a predetermined exceedance probability on an annual basis, allowing visual evaluation of the trend in the measured power generation on an annual basis. Furthermore, the power generation system 10 of this embodiment can visually evaluate the trend by comparing the time series graph E20 that displays the measured solar radiation and expected solar radiation of the power plant 40 on an annual basis with the time series graph S20 that displays the measured solar radiation and expected solar radiation of the power plant 40 on an annual basis. Furthermore, the power generation system 10 of this embodiment can comprehensively manage the measured power generation of multiple power plants 40 located throughout the country. Furthermore, the power generation system 10 can manage whether multiple power plants 40 are operating properly.

[0219] The power generation system 10 of this embodiment displays a time series graph E30 (see FIG. 15 ) that displays the measured power generation amount and expected power generation amount on an annual basis for the multiple power plants 40. Therefore, according to the power generation system 10 of this embodiment, the time series graph of the measured power generation amount on an annual basis for the multiple power plants 40 can be compared with the time series graph of the expected power generation amount with a predetermined exceedance probability on an annual basis for the multiple power plants 40, and therefore the transition of the measured power generation amount on an annual basis for the multiple power plants 40 can be visually evaluated.

[0220] The power generation system 10 of this embodiment displays a time series graph S30 (see FIG. 16 ) that displays the measured solar radiation and expected solar radiation for multiple power plants 40 on an annual basis. Therefore, the power generation system 10 of this embodiment can compare the time series graph of the measured solar radiation for multiple power plants 40 on an annual basis with the time series graph of the expected solar radiation with a predetermined exceedance probability for multiple power plants 40 on an annual basis, allowing visual evaluation of the trend in the measured solar radiation on an annual basis. Furthermore, the power generation system 10 of this embodiment can visually evaluate the trend by comparing the time series graph E30 that displays the measured power generation and expected power generation for multiple power plants 40 on an annual basis with the time series graph S30 that displays the measured solar radiation and expected solar radiation for multiple power plants 40 on an annual basis. Furthermore, the power generation system 10 of this embodiment can comprehensively manage the measured solar radiation for multiple power plants 40 located throughout the country.

[0221] The power generation system 10 of this embodiment displays a time series graph E40 (see FIG. 18) that displays the amount of power generation calculated from the total amount of solar radiation and the predicted amount of power generation. Therefore, the power generation system 10 of this embodiment allows the user to obtain an outlook on the amount of power generation of the power plant 40.

[0222] (Modification of the second embodiment) The modified example of the second embodiment is characterized in that, in addition to the contents of the second embodiment, the output control described in the first embodiment is executed. The contents specific to the modified example will be described below.

[0223] FIG. 24 is a schematic configuration diagram of a power generation system 10 according to a modified example of the second embodiment.

[0224] The power generation system 10 of the modified example communicates with a power company 20, an external weather management server 30, and a power plant 40.

[0225] The information management unit 26 in the modified example prepares the following information as notification contents. (Information 6) Measured power generation (measured and available power generation) (Information 7) Measured solar radiation (measured and available solar radiation) (Information 8) Expected power generation and probability of exceedance (calculated from statistical data) (Information 9) Expected solar radiation and exceedance probability (calculated from statistical data) (Information 10) Abnormality judgment 1 (probability of exceeding measured power generation < probability of exceeding measured solar radiation) (Information 5) Abnormality judgment 2 (effective power generation amount - measured power generation amount ≠ 0) (Information 11) Abnormality judgment (Abnormality judgment 1 ∩ Abnormality judgment 2 ≒ Possibility of abnormality at the power plant)

[0226] In the power generation system 10 of the modified example, a decrease in the measured power generation amount as a result of output control by the power company 20 may result in (information 10) abnormality judgment 1. Therefore, if both (information 10) abnormality judgment 1 and (information 5) abnormality judgment 2 are met, it may be determined that there is a possibility that an abnormality has occurred in the power plant 40 (information 11). Note that (information 5) abnormality judgment 2 of the modified example is similar to the (information 5) abnormality judgment managed by the information management unit 26 of the first embodiment (see FIG. 3).

[0227] In the modified example, the performance evaluation unit 29 evaluates the equipment of the power plant 40 based on the evaluation of the measured solar radiation using the exceedance probability, the evaluation of the measured power generation using the exceedance probability, and the evaluation of the actual power generation and the measured power generation. For example, when the measured solar radiation is about P50, the measured power generation is about P70, and (actual power generation) - (measured power generation) ≠ 0, the performance evaluation unit 29 evaluates that there is a possibility that an abnormality has occurred in the equipment of the power plant 40. Furthermore, when the measured solar radiation is about P50 and the measured power generation is about P70, the performance evaluation unit 29 may evaluate that there is a possibility that an abnormality has occurred in the equipment of the power plant 40, or that the abnormality is due to output control by the power company 20.

[0228] (Summary of Modifications of Second Embodiment) The power generation system 10 of this embodiment displays the possibility of an abnormality in the equipment of the power plant 40 or the possibility of output control by the power company 20 when the evaluation of the measured power generation amount based on the exceedance probability is lower than the evaluation of the measured solar radiation amount based on the exceedance probability. Therefore, the power generation system 10 of this embodiment can evaluate the cause of the decrease in power generation amount by taking into account the effects of the equipment of the power plant 40 and output control by the power company 20.

[0229] (Other embodiments) In the power generation system 10 of the second embodiment, the power generation system 10 may measure and display the temperature of the panel of the power generation device 14. The power generation system 10 may also analyze the trend of the panel temperature and the trend of the measured power generation amount by a statistical analysis method. Therefore, the power generation system 10 of this embodiment can manage the data of the panel temperature and can notify the user when there is a discrepancy between the trend of the panel temperature and the trend of the measured power generation amount.

[0230] In the power generation system 10 of the second embodiment, the power generation system 10 may be configured to update the output derating coefficient. The power generation system 10 manages the trend of output derating of the power plant 40, for example, by using a moving average calculated by dividing the measured amount of power generation by the measured amount of solar radiation. The power generation system 10 may then update the output derating coefficient in accordance with the trend of output derating of the power plant 40 managed by the power generation system 10. The power generation system 10 may also update the output derating coefficient in accordance with improvements in the quality and performance of the power generation device 14. Therefore, the power generation system 10 of this embodiment can use an output derating coefficient that is tailored to the actual state of the power plant 40, thereby improving the accuracy of calculation of the expected power generation amount.

[0231] Furthermore, the configurations of the power generation system 10 and the remote monitoring system 50 described in the above embodiment are merely examples, and may be changed depending on the situation without departing from the spirit of the invention.

[0232] Furthermore, the processing flow of the program described in the above embodiment is also an example, and unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged within the scope of the main idea.

[0233] In the above embodiment, the term "CPU" refers to a processor in a broad sense, and includes general-purpose processors such as a CPU (Central Processing Unit), and dedicated processors such as a GPU (Graphics Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), and a programmable logic device.

[0234] Furthermore, the operations of the processors in the above embodiments may not only be performed by a single processor, but may also be performed by multiple processors located at physically separate locations working together. Furthermore, the order of the operations of the processors is not limited to the order described in the above embodiments, and may be changed as appropriate.

[0235] In the above embodiment, the information processing program is pre-stored (installed) in ROM, but the present invention is not limited to this. The program may be provided in a form recorded on a recording medium such as a CD-ROM (Compact Disc Read Only Memory), a DVD-ROM (Digital Versatile Disc Read Only Memory), or a USB (Universal Serial Bus) memory. The program may also be downloaded from an external device via a network. [Explanation of symbols]

[0236] 10...power generation system, 12...power generation control unit, 14...power generation device, 14A...sunlight sensor, 16...user interface, 16A...operation / display panel, 18...power management unit, 20...power company, 22...output control instruction acquisition unit, 24...restoration unit, 26...information management unit, 28...power generation amount measurement unit, 30...external weather management server, 32...history database, 34...notification content acquisition unit, 36...output unit, 16B...notification device

Claims

1. A display method in a management system that manages one or more power plants that receive sunlight and generate electricity, A display method that simultaneously displays the measured power generation amount measured at the power plant and the expected power generation amount with a predetermined exceedance probability calculated based on past sunshine hours information in the area where the power plant is located.

2. In addition to claim 1, simultaneously displaying the measured solar radiation amount measured at the power plant and the expected solar radiation amount with a predetermined exceedance probability calculated based on the sunshine duration information; The display method according to claim 1 .

3. When the evaluation of the measured power generation amount based on the exceedance probability is lower than the evaluation of the measured solar radiation amount based on the exceedance probability, displaying the possibility of at least one of an abnormality in the power plant and a possibility of output control of the power plant. The display method according to claim 2.

4. simultaneously displaying the transition states of the measured power generation amount measured monthly at the power plant and the plurality of expected power generation amounts; The display method according to claim 1 .

5. In addition to claim 4, simultaneously displaying the transition states of the measured solar radiation measured monthly at the power plant and the expected solar radiation with a plurality of predetermined exceedance probabilities calculated based on the sunshine duration information; The display method according to claim 4.

6. simultaneously displaying the transition states of the measured power generation amount measured on an annual basis at the power plant and the plurality of expected power generation amounts; The display method according to claim 1 .

7. In addition to claim 6, simultaneously displaying the transition states of the measured solar radiation measured on an annual basis at the power plant and the expected solar radiation with a plurality of predetermined exceedance probabilities calculated based on the sunshine duration information; The display method according to claim 6.

8. a total value of the measured power generation amounts measured on an annual basis at the plurality of power plants and a transition state of each of the plurality of expected power generation amounts are simultaneously displayed; The display method according to claim 1 .

9. In addition to claim 8, simultaneously displaying the transition states of the average value of the measured solar radiation measured on an annual basis at the plurality of power plants and the expected solar radiation with a plurality of predetermined exceedance probabilities calculated based on the sunshine duration information; The display method according to claim 8.

10. A display method in a management system that manages one or more power plants that receive sunlight and generate electricity, A display method that simultaneously displays the transition states of the amount of power generated calculated based on past sunshine hours information in the area where the power plant is located and the predicted amount of power generated based on the amount of power generated.

Images