Solar equipment diagnostic system

Abstract

To provide a solar equipment diagnostic system that can suitably diagnose the amount of energy used by solar equipment.SOLUTION: A diagnostic system 1 performs a diagnosis on the amount of energy of a solar power generation panel 2 that obtains energy using sunlight, and includes a diagnostic model creation unit that creates a diagnostic model on the basis of learning data on the solar power generation panel 2 measured during a learning period, an estimated value calculation unit that uses the diagnostic model to calculate an estimated amount of power generated by the solar power generation panel 2 during a determination period on the basis of the determination data on the solar power generation panel 2 measured during the determination period after the learning period has elapsed, a deviation information acquisition unit that can acquire a deviation rate that indicates the deviation between the actual amount of power generated by the solar power generation panel 2 measured during the determination period and the estimated amount of power generated, and an abnormality factor determination unit that can determine the cause of an abnormality related to the amount of energy of the solar power generation panel 2 on the basis of the deviation rate.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a technology for a system capable of performing diagnosis regarding the amount of energy of equipment that utilizes sunlight. [Background technology]

[0002] BACKGROUND ART Conventionally, there are known techniques capable of diagnosing the amount of energy (amount of power generation) of devices that utilize sunlight, such as solar panels, as described in Patent Document 1, for example.

[0003] Patent Document 1 describes a system that can determine whether a decrease in power generation due to a malfunction has occurred using data such as the amount of power generated by a solar power generation system. The system described in Patent Document 1 creates estimation parameters by learning data such as the amount of power generated, and determines that a decrease in power generation due to a malfunction has occurred if a value based on the difference between the amount of power generated estimated by the estimation parameters and the amount of power actually measured by the solar power generation system on a certain day is equal to or greater than a threshold value.

[0004] Here, it is predicted that as time passes after installation of equipment such as solar panels, a discrepancy will occur between the estimated power generation amount and the actually measured power generation amount due to factors such as the accumulation of dirt, the addition or removal of equipment, etc. If the discrepancy widens, it may become difficult to determine whether there is a malfunction in the solar panels, etc. based on the threshold value, and it may become difficult to appropriately diagnose the power generation amount of the solar power generation system. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent No. 6608619 Summary of the Invention [Problem to be solved by the invention]

[0006] The present invention has been made in consideration of the above-described circumstances, and the problem that it aims to solve is to provide a diagnosable solar power equipment diagnostic system that can suitably diagnose the amount of energy of solar power equipment. [Means for solving the problem]

[0007] The problem to be solved by the present invention is as described above, and the means for solving this problem will now be described.

[0008] That is, claim 1 provides a solar power equipment diagnostic system for diagnosing the amount of energy of solar power equipment that obtains energy using sunlight, and includes: a diagnostic model creation unit that creates a diagnostic model based on learning data related to the solar power equipment measured during a learning period; an estimate calculation unit that uses the diagnostic model to calculate an estimate of the amount of energy of the solar power equipment during a judgment period based on judgment data related to the solar power equipment measured during the judgment period after the learning period has elapsed; a deviation information acquisition unit that can acquire deviation information indicating the deviation between the estimated value and the actual value of the amount of energy of the solar power equipment measured during the judgment period; and an abnormality factor determination unit that can determine the cause of an abnormality related to the amount of energy of the solar power equipment based on the deviation information.

[0009] Claim 2 provides a solar power equipment diagnostic system for diagnosing the amount of energy of solar power equipment that obtains energy using sunlight, and includes: a diagnostic model creation unit that creates a diagnostic model based on learning data related to the solar power equipment measured during a learning period; an estimate calculation unit that uses the diagnostic model to calculate an estimate of the amount of energy of the solar power equipment during a judgment period based on judgment data related to the solar power equipment measured during the judgment period after the learning period has elapsed; a deviation information acquisition unit that can acquire deviation information indicating the deviation between the estimated value and the actual value of the amount of energy of the solar power equipment measured during the judgment period; and a diagnostic model update unit that updates the diagnostic model based on the deviation information.

[0010] In claim 3, the system includes an abnormality factor determination unit that can determine the cause of an abnormality related to the energy amount of the solar power equipment based on the deviation information, and a diagnostic model update unit that updates the diagnostic model based on the deviation information, wherein the cause of an abnormality related to the energy amount of the solar power equipment includes a factor related to a change in the specifications of the solar power equipment, and the diagnostic model update unit updates the diagnostic model when the determination result of the abnormality factor determination unit is a factor related to a change in the specifications of the solar power equipment.

[0011] In claim 4, the deviation information acquisition unit can acquire, as the deviation information, a deviation rate, which is a rate of difference between the estimated value and the actual measured value.

[0012] In claim 5, a pyranometer capable of measuring the amount of solar radiation is provided, and factors related to changes in the specifications of the solar power equipment include the addition of the solar power equipment, and when the deviation rate continues to increase and there is no change in the amount of solar radiation, the abnormality factor determination unit determines that the solar power equipment has been added and outputs the determination result.

[0013] In claim 6, factors related to changes in the specifications of the solar power equipment include the reduction of the solar power equipment, and when the deviation rate drops sharply and the change in the ratio between the estimated value and the actual measured value is constant, it is determined that the solar power equipment has been reduced, and the determination result is output.

[0014] In claim 7, the diagnostic model update unit updates the diagnostic model by causing the diagnostic model creation unit to create a second diagnostic model different from the first diagnostic model, which is the diagnostic model before the update, using the learning data measured in a new learning period.

[0015] In claim 8, the diagnostic model update unit updates the diagnostic model by correcting the first diagnostic model using the deviation rate until the second diagnostic model is created. [Effects of the Invention]

[0016] The present invention has the following effects.

[0017] In the present invention, it is possible to suitably carry out diagnosis regarding the amount of energy used by solar power equipment. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a schematic diagram showing the configuration of a diagnostic system according to an embodiment of the present invention; [Figure 2] 4 is a flowchart showing a process executed by the diagnostic system. [Figure 3] 4 is a flowchart showing an abnormality diagnosis process. [Figure 4] 10 is a flowchart showing the continuation of the abnormality diagnosis process. [Figure 5] A table showing information on deviation rates, possible causes, and required actions. [Figure 6] (a) A graph showing an example of deviation rate trends (rising, falling, constant deviation). (b) A graph showing an example of a case where deviation is continuous and a case where deviation is temporary. [Figure 7] 1A is a graph showing an example of a case where the deviation rate changes suddenly and slowly, and FIG. 1B is a graph showing an example of a case where the absolute value of the deviation rate is large and small. [Figure 8] (a) A graph showing an example of the relationship between the amount of solar radiation and the amount of power generated when the result of the abnormality diagnosis process is "no abnormality." (b) A graph showing an example of the relationship between the amount of solar radiation and the amount of power generated when the result of the abnormality diagnosis process is "addition of panels." (c) A graph showing an example of the relationship between the amount of solar radiation and the amount of power generated when the result of the abnormality diagnosis process is "pyranometer failure." [Figure 9] 10 is a graph showing an example of a power generation amount ratio. [Figure 10] FIG. 10 is an explanatory diagram showing the timing for generating a diagnostic model. DETAILED DESCRIPTION OF THE INVENTION

[0019] The configuration of a diagnostic system 1 according to one embodiment of the present invention will be described below with reference to FIG.

[0020] The diagnostic system 1 according to this embodiment is capable of diagnosing the amount of energy of the solar power generation panel 2 (diagnosing an abnormality in the output of the solar power generation panel 2, which will be described later). The diagnostic system 1 and the solar power generation panel 2 are installed in a facility (for example, a factory) of a predetermined business operator (hereinafter also referred to as "the business operator").

[0021] The solar power generation panel 2 is capable of generating electricity using sunlight. The solar power generation panel 2 is installed in a sunny location, such as the roof of a facility (such as a factory). The solar power generation panel 2 is installed using an appropriate support tool so that it is tilted at an angle that allows it to easily receive sunlight.

[0022] The facility of the operator is equipped with a storage battery that can charge and discharge the power obtained from the solar power generation panel 2, a power conditioner that can convert the power as needed, and an EMS (energy management system) that can control the operation of the storage battery and the power conditioner. The solar power generation panel 2, the storage battery, the power conditioner, and the EMS constitute a solar power generation system. Note that the storage battery, the power conditioner, and the EMS are not shown in FIG. 1. The EMS can acquire information such as the output (power generation amount) of the solar power generation panel 2 using various sensors (not shown).

[0023] In the above-described solar power generation system, it is expected that an abnormality will occur in the output of the solar power generation panel 2 over time. Here, "abnormality" refers to a continuous or temporary deviation of the amount of power generated by the solar power generation panel 2 from the predicted amount of power generation (the estimated power generation amount described below). Note that the "output of the solar power generation panel 2" can be the power converted by the power conditioner. Causes of the abnormality include, for example, soiling, a malfunction of the solar power generation panel 2, and the addition or removal of solar power generation panels 2 (see FIG. 5). The diagnostic system 1 can diagnose abnormalities in the output of the solar power generation panel 2. Note that the diagnosis of abnormalities and the causes of the abnormality will be described in detail later.

[0024] The diagnostic system 1 includes a control device 10. The control device 10 is capable of processing various types of information. A general personal computer, a server, or the like can be used as the control device 10. The control device 10 includes a storage unit 11, a control unit 12, a communication unit 13, an input unit 14, and a display unit 15.

[0025] The storage unit 11 stores various programs (such as a diagnostic model to be described later) and various acquired information. The storage unit 11 is configured with a HDD, RAM, ROM, and the like.

[0026] The control unit 12 executes the programs stored in the storage unit 11. The control unit 12 is configured by a CPU.

[0027] The communication unit 13 is capable of communicating with external devices. The communication unit 13 can exchange information with external devices via various communication means such as the Internet. By performing communication using the communication unit 13, the control device 10 can access, for example, an EMS or an external server. This allows the control device 10 to obtain information obtained by the EMS, information from various websites stored on the server, and the like.

[0028] The input unit 14 is used to input various types of information and is composed of a keyboard, a mouse, and the like.

[0029] The display unit 15 displays various types of information and is configured by, for example, a liquid crystal display.

[0030] The control device 10 can acquire data necessary for diagnosing an abnormality by communicating using the communication unit 13. The data necessary for diagnosing an abnormality includes "amount of solar radiation," "temperature," and "amount of power generation."

[0031] The "amount of solar radiation" is the amount of solar radiation at the location where the solar power generation panel 2 is installed. As the "amount of solar radiation", global solar radiation, direct solar radiation, etc. can be used. The "amount of solar radiation" is obtained, for example, by a pyranometer installed near the solar power generation panel 2.

[0032] The "temperature" is the temperature at the location where the solar power generation panel 2 is installed. The "temperature" is obtained by a thermometer installed near the solar power generation panel 2, for example.

[0033] The "power generation amount" is the amount of power (kWh) generated by the solar power generation panel 2. The "power generation amount" is acquired by, for example, the EMS.

[0034] As described above, in this embodiment, abnormality diagnosis is performed using data on the "power generation amount" of the solar power generation panel 2 and the weather conditions related to power generation, namely, "amount of solar radiation" and "temperature."

[0035] The control device 10 performs communication using the communication unit 13 to acquire data on the amount of solar radiation, temperature, and power generation amount acquired by devices such as a pyranometer, a thermometer, and an EMS.

[0036] In addition, instead of a configuration in which the control device 10 acquires the "amount of solar radiation" and "temperature" from devices such as a pyranometer or thermometer installed in the facility of the business operator, a configuration in which the control device 10 acquires the "amount of solar radiation" and "temperature" using information external to the facility, such as weather forecast information (weather forecast, etc.) transmitted from a public meteorological institution, may also be adopted.

[0037] 2, the above-described diagnostic system 1 (control device 10) can execute an "abnormality diagnosis process" that uses the above-described data on "amount of solar radiation," "air temperature," and "amount of power generation" to diagnose abnormalities in the output of the photovoltaic power generation panel 2, a "diagnostic model creation process" that creates a diagnostic model used in the abnormality diagnosis process, and a "diagnostic model recreation process" that recreates a diagnostic model based on the analysis results of the abnormality diagnosis process. The processes (controls) executed by the control device 10 will be described below.

[0038] First, the "diagnostic model creation process" will be described. The diagnostic model creation process is a process for creating a diagnostic model using data on "solar radiation amount," "temperature," and "power generation amount" (hereinafter referred to as "learning data") acquired during a predetermined learning period (step S10). The diagnostic model creation process is executed, for example, in response to a user's operation via the input unit 14. The diagnostic model creation process may also be executed automatically by the control device 10 in response to the elapse of a predetermined learning period. Note that instead of being triggered by the predetermined learning period, the process may also be triggered by the acquisition of a predetermined amount of learning data.

[0039] The diagnostic model predicts (estimates) the amount of power generated by the solar panel 2 using "judgment data" described below. The diagnostic model is created by machine learning. Various methods such as decision trees and neural networks can be used for machine learning.

[0040] In this embodiment, the learning period is set to one year. The control device 10 creates a diagnostic model using learning data acquired at predetermined intervals (e.g., every hour) over the learning period (one year). In the diagnostic model creation process, the control device 10 creates a diagnostic model by learning the relationship between the "power generation amount" during the learning period and the weather conditions related to power generation, namely, "solar radiation" and "temperature."

[0041] In the example shown in FIG. 10, after the solar power generation panel 2 was installed, operation of the solar power generation panel 2 began on January 1, 2020. In this case, the control device 10 creates a diagnostic model using learning data from a learning period (first learning period) from immediately after operation of the solar power generation panel 2 began until January 1, 2021. Note that, hereinafter, the diagnostic model created using the learning data from the first learning period may be referred to as the "first diagnostic model." The first diagnostic model is created based on data from a time when it is estimated that no abnormality has yet occurred in the output of the solar power generation panel 2. For this reason, the first diagnostic model is formed so as to be able to estimate the amount of power generation when no abnormality has occurred.

[0042] After completing the creation of the diagnostic model, the control device 10 stores the diagnostic model in the storage unit 11 and terminates the diagnostic model creation process.

[0043] Next, the abnormality diagnosis process shown in Figures 2 and 3 will be described. The abnormality diagnosis process is a process for diagnosing an abnormality in the output of the photovoltaic power generation panel 2 using data on "amount of solar radiation," "temperature," and "amount of power generation" (hereinafter referred to as "determination data") acquired during a predetermined determination period.

[0044] In the abnormality diagnosis process, an abnormality in the output of the solar power generation panel 2 is diagnosed based on the discrepancy between the amount of power generated by the solar power generation panel 2 during a determination period and the estimated amount of power generated by the diagnostic model based on the determination data. In the following description, it is assumed that the abnormality diagnosis process is executed using the first diagnostic model. The abnormality diagnosis process is executed (started) at any timing after the diagnostic model is created (after the diagnostic model creation process is completed). The abnormality diagnosis process is started, for example, by a user operation via the input unit 14. Furthermore, the abnormality diagnosis process may be started automatically by the control device 10, for example, when the diagnostic model creation process is completed.

[0045] When the abnormality diagnosis process is started, the control device 10 performs a diagnosis every time a predetermined judgment period elapses (executes the process of step S14, which will be described later). In this embodiment, the predetermined judgment period is set to one day. In this embodiment, the control device 10 performs a diagnosis, for example, at midnight on the day of the judgment.

[0046] Each step of the process will be described below with reference to the flowchart shown in Fig. 2. In step S11, the control device 10 acquires data for determination ("amount of solar radiation," "temperature," and "power generation amount"). Specifically, the control device 10 acquires data for determination for each predetermined period (for example, one hour) on the day of determination. The data for determination includes data acquired during the time period when the solar power generation panel 2 is generating power (for example, the time period from sunrise to sunset). After performing the process of step S11, the control device 10 proceeds to the process of step S12. The timing for acquiring the data for determination is not limited to midnight on the day of determination, but can be any timing.

[0047] In step S12, the control device 10 calculates an estimation result of the amount of power generated by the photovoltaic panel 2 on the day of determination (hereinafter referred to as "estimated power generation amount") based on the determination data and the diagnostic model. The estimated power generation amount is the amount of power generation estimated by the diagnostic model based on the "amount of solar radiation" and "temperature" on the day of determination, which are included in the determination data. In this embodiment, the control device 10 calculates the estimated power generation amount for each hour (1 hour), day (the day of determination), and month (the month including the day of determination). Note that the monthly estimated power generation amount can be the total value of the estimated power generation amounts for each day for one month. After performing the process of step S12, the control device 10 proceeds to the process of step S13.

[0048] In step S13, the control device 10 calculates the deviation rate of the actually measured power generation amount from the estimated power generation amount. Here, the "actually measured power generation amount" is the amount of power generation that is actually measured. The value of the determination data (hourly power generation amount) acquired in step S11 is used as the actually measured power generation amount.

[0049] Furthermore, the "deviation rate" is the ratio of the deviation between the estimated power generation amount and the measured power generation amount (the value obtained by subtracting the estimated power generation amount from the measured power generation amount) for a certain power generation amount (estimated power generation amount). If the value of the measured power generation amount is smaller than the estimated power generation amount, the deviation rate is indicated by a negative value (for example, -10%). In this embodiment, the control device 10 calculates the deviation rate for each hour (each hour on the day of determination), day (the day of determination), and month (the month including the day of determination). After performing the process of step S13, the control device 10 proceeds to the process of step S14.

[0050] In step S14, the control device 10 diagnoses whether there is an abnormality in the output of the photovoltaic power generation panel 2 and analyzes the cause of the abnormality. In this embodiment, the control device 10 diagnoses whether there is an abnormality in the output of the photovoltaic power generation panel 2 and analyzes the cause of the abnormality by executing the processes of the flowcharts shown in Figures 3 and 4. Each process will be described below using the flowcharts shown in Figures 3 and 4.

[0051] In step S101, the control device 10 acquires the deviation rates calculated in step S13. That is, the control device 10 acquires the deviation rates for each hour, day, and month. After performing the process of step S101, the control device 10 proceeds to the process of step S102.

[0052] In step S102, the control device 10 determines whether a deviation equal to or greater than a threshold continues to occur (step S102). Any preset value can be used as the threshold. In step S102, the determination can be made for each hour, day, or month. The threshold can be set for each hour, day, or month. Below, as an example of the determination in step S102, an example will be described in which a daily deviation rate is used to determine whether a deviation equal to or greater than a threshold continues to occur.

[0053] Here, "continuous occurrence" refers to occurrence at a rate equal to or greater than a certain rate over a certain period of time. For example, if the number of days on which the daily deviation rate is equal to or greater than a threshold value occurs at a rate equal to or greater than a certain rate over a certain period of time (e.g., the most recent month), the control device 10 determines that a deviation equal to or greater than the threshold value is occurring continuously. Note that instead of the above embodiment, the control device 10 can also determine that a deviation equal to or greater than the threshold value is occurring continuously if, for example, days on which the absolute value of the daily deviation rate is equal to or greater than the absolute value of the threshold value occur consecutively for a certain period of time (e.g., several days).

[0054] Even if a deviation of a threshold or more occurs, if the period during which the deviation occurred is less than a certain percentage of a certain period or if the deviation did not occur continuously for a certain period or more, the control device 10 determines that the deviation of a threshold or more does not occur continuously. In this case, the control device 10 determines that the deviation is occurring temporarily.

[0055] FIG. 6(b) shows examples of cases where it is determined that a deviation is occurring continuously and cases where it is not occurring continuously (occurring temporarily) using a graph showing the change in the deviation rate over time. Note that the graphs in FIGS. 6 and 7 show moving averages of the deviation rate that change over time. In the example, the solid line shows the deviation rate when it is determined that no abnormality is occurring in the output of the photovoltaic power generation panel 2 ("no abnormality"). Here, even if no particular abnormality is occurring in the output of the photovoltaic power generation panel 2, it is predicted that the measured power generation amount will deviate from the estimated power generation amount due to deterioration of the photovoltaic power generation panel 2. Therefore, the deviation rate shown by the solid line decreases slightly over time. The deviation in the deviation rate shown by the solid line is less than the threshold value. Therefore, when the deviation rate changes as shown by the solid line, it is determined that a deviation is not occurring continuously.

[0056] In addition, the example shows the deviation rate when it is determined that deviations above the threshold are occurring continuously (successively) using a dashed line. The example shows an example of a case where the deviation rate is decreasing. The deviation rate shown by the dashed line is significantly lower than the deviation rate shown by the solid line.

[0057] In the example, the deviation rate when it is determined that deviation is temporarily occurring is shown by a dashed line. The deviation rate shown by the dashed line drops sharply only at certain times (hours, days, months). More specifically, the deviation rate shown by the dashed line drops sharply only at certain times compared to the slope of the deviation rate for "no abnormality." Furthermore, the deviation rate shown by the dashed line changes in roughly the same way as the deviation rate for "no abnormality" except for the certain periods.

[0058] If the control device 10 determines that a deviation equal to or greater than the threshold continues to occur (step S102: YES), the control device 10 proceeds to the process of step S110. On the other hand, if the control device 10 determines that a deviation equal to or greater than the threshold does not continue to occur (step S102: NO), the control device 10 proceeds to the process of step S103.

[0059] In step S103, the control device 10 calculates the average value of the deviation rates. Specifically, the control device 10 calculates the average value of the daily deviation rates using the hourly deviation rates (daily deviation rates). The control device 10 also calculates the average value of the monthly deviation rates using the monthly deviation rates. After performing the process of step S103, the control device 10 proceeds to the process of step S104.

[0060] In step S104, the control device 10 determines whether the deviation is large only at a specific time or in a specific month. In step S104, the control device 10 determines whether a temporary deviation occurs only at a specific time or in a specific month. That is, when a deviation equal to or greater than the threshold occurs but the deviation does not occur continuously (step S103: NO), the control device 10 determines whether the deviation equal to or greater than the threshold occurs only at a specific time (time period) or in a specific month. When determining whether a deviation occurs only at a specific time, the control device 10 compares, for example, the deviation rate for each hour (every hour) on the day of determination with a threshold. When determining whether a deviation occurs only in a specific month, the control device 10 compares, for example, the average monthly deviation rate calculated in step S103 with a threshold.

[0061] If the control device 10 determines that the deviation is large only at a specific time or in a specific month (step S104: YES), the control device 10 proceeds to the processing of step S105. In this case, it is estimated that a temporary deviation of the measured power generation amount from the estimated power generation amount has occurred (see the deviation rate indicated by the dashed line in FIG. 6(b)). On the other hand, if the control device 10 determines that the deviation is not large only at a specific time or in a specific month (step S104: NO), the control device 10 proceeds to the processing of step S109.

[0062] In step S105, the control device 10 determines whether the deviation rate determined in step S104 to be large only for a specific time or a specific month is increasing or decreasing. In this embodiment, the control device 10 determines whether the deviation rate is increasing or decreasing based on the change (moving average) of the deviation rate. Specifically, the control device 10 determines that the deviation rate is increasing if the slope at the time (hour) when a deviation equal to or greater than the threshold occurred in the graph showing the moving average of the deviation rate shown in FIG. 6(b) is upward, and determining that the slope is decreasing if the slope is downward. If the control device 10 determines that the deviation rate is increasing (step S105: YES), the control device 10 proceeds to the processing of step S106. On the other hand, if the control device 10 determines that the deviation rate is decreasing (step S105: NO), the control device 10 proceeds to the processing of step S108.

[0063] In step S106, the control device 10 determines that the cause of the abnormality in the output of the photovoltaic power generation panel 2 is "seasonal / time-of-day influence on the pyranometer." That is, the processes from step S102 to step S106 above indicate that the actual measured power generation amount is temporarily deviating (increasing) from the estimated power generation amount. In this case, the assumed cause of the abnormality is thought to be the influence on the pyranometer due to the season or time-of-day (see FIG. 5). After performing the process of step S106, the control device 10 proceeds to the process of step S107.

[0064] In step S107, the control device 10 determines that there is no particular action that needs to be taken (the cause has been eliminated) in creating a diagnostic model for the cause determined in the processing of step S106 (see FIG. 5). After performing the processing of step S107, the control device 10 ends the abnormality diagnosis processing.

[0065] Furthermore, in step S105, if it is determined that the deviation rate is decreasing (step S102: decreasing), the control device 10 proceeds to step S108, where it determines that the cause of the abnormality in the output of the photovoltaic power generation panel 2 is "seasonal / time-of-day influence on the photovoltaic power generation panel 2." That is, the processing contents of steps S102 to S105 and step S108 indicate that the actual measured power generation amount is temporarily deviating (decreasing) from the estimated power generation amount. In this case, the assumed cause of the abnormality is thought to be the influence on the photovoltaic power generation panel 2 due to the season or time-of-day (see FIG. 5).

[0066] After performing the process of step S108, the control device 10 proceeds to the process of step S107 and determines that the cause has been eliminated. After performing the process of step S107, the control device 10 ends the abnormality diagnosis process.

[0067] Furthermore, in step S104, if it is determined that the deviation is not large only at a specific time or a specific month (step S104: NO), the control device 10 determines in step S109 that there is "no abnormality." That is, the processes from step S102 to step S104 above show that the measured power generation amount does not deviate from the estimated power generation amount either continuously or temporarily (see the deviation rate indicated by the solid line in FIG. 6(b)). In this case, the control device 10 determines that no abnormality has occurred in the output of the photovoltaic power generation panel 2. After performing the process of step S109, the control device 10 ends the abnormality diagnosis process.

[0068] If it is determined in step S102 that a deviation equal to or greater than the threshold value continues to occur (step S102: YES), the control device 10 proceeds to step S110, where it determines the trend of the deviation rate. Specifically, in step S110, the control device 10 determines whether the deviation rate determined to continue to occur will change over time in an "increasing," "decreasing," or "constant deviation" manner.

[0069] The graph in FIG. 6(a) shows an example of the trend of the deviation rate. In this embodiment, the control device 10 judges whether the deviation rate is "rising," "falling," or "constant deviation" based on the graph of the deviation rate of "normal," which is shown by the solid line. In the illustrated example, the deviation rate judged to be "rising" is shown by the dashed-dotted line. The control device 10 judges the trend of the deviation rate to be "rising" if the slope of the deviation rate in the graph is greater than the slope of the graph of the deviation rate of "normal" and points upward.

[0070] In the example shown, deviation rates that are determined to be "decreasing" are indicated by dashed lines. The control device 10 determines that the trend of the deviation rate is "decreasing" when the slope of the deviation rate in the graph is greater than the slope of the graph of the deviation rate for "normal" and points downward.

[0071] In the example shown, the deviation rate determined to be a "constant deviation" is indicated by a two-dot chain line. The control device 10 determines that the tendency of the deviation rate is a "constant deviation" when the slope of the deviation rate in the graph is roughly the same as the slope of the graph of the deviation rate for "no abnormality."

[0072] In the above example, a graph that changes with a constant slope is shown as an example of a graph showing the tendency of the deviation rate, but it is also possible to use a graph in which the deviation rate changes in a broken line shape.

[0073] If the control device 10 determines that the deviation rate is trending "up" (step S110: up), it proceeds to processing of step S111. If the control device 10 determines that the deviation rate is trending "constant deviation" (step S110: constant deviation), it proceeds to processing of step S117. If the control device 10 determines that the deviation rate is trending "down" (step S110: down), it proceeds to processing of step S120.

[0074] In step S111, the control device 10 determines whether the absolute value of the deviation rate is "large" or "small." The graph in FIG. 7(b) shows an example of a change in the absolute value of the deviation rate. In this embodiment, it is determined whether the absolute value of the deviation rate after a change greater than the slope of the graph of the deviation rate for "no abnormality" is greater by a predetermined value or more compared to the value (absolute value) on the graph of the deviation rate for "no abnormality." The deviation rate shown by the dashed line in the example shows an example in which the absolute value of the deviation rate after change does not change by a predetermined value or more compared to the absolute value of the deviation rate shown by the solid line. The deviation rate shown by the dashed line in the example shows an example in which the absolute value of the deviation rate after change is approximately the same as the deviation rate shown by the solid line. The deviation rate shown by the dashed line in the example shows an example in which the absolute value is "large." That is, in the example shown, the absolute value of the deviation rate after the change, indicated by the dashed line, is larger than the absolute value of the deviation rate indicated by the solid line by a predetermined value or more. If the control device 10 determines that the absolute value of the deviation rate is "large" (step S111: YES), it proceeds to the processing of step S112. On the other hand, if the control device 10 determines that the absolute value of the deviation rate is "small" (step S111: NO), it proceeds to the processing of step S118.

[0075] In step S112, the control device 10 determines the trends in the amount of solar radiation and the amount of power generation. More specifically, the control device 10 determines whether the amount of power generation is increasing without any change in the trend in the amount of solar radiation, or whether the amount of solar radiation is decreasing without any change in the trend in the amount of power generation. In step S112, the control device 10 makes the above determination based on determination data for a predetermined period (e.g., several days) up to the determination date. For example, if the amount of solar radiation and the amount of power generation on a certain day have changed (increased or decreased) by more than a predetermined percentage compared to the amount of solar radiation and the amount of power generation on the previous day, the control device 10 determines that the amount of solar radiation and the amount of power generation have increased or decreased. Furthermore, if the amount of solar radiation and the amount of power generation on a certain day have not changed by more than a predetermined percentage compared to the amount of solar radiation and the amount of power generation on the previous day, the control device 10 determines that there is no change.

[0076] The table shown in Fig. 8 shows trends in the amount of solar radiation and the amount of power generation. The table shown in Fig. 8(a) shows an example where there is no abnormality (change) in the amount of solar radiation or the amount of power generation. The table shown in Fig. 8(b) shows an example where the amount of power generation is increasing, as indicated by the filled-in area of ​​the table. The table shown in Fig. 8(c) shows an example where the amount of solar radiation is decreasing, as indicated by the filled-in area of ​​the table.

[0077] When the control device 10 determines that the content of the determination data shows that there is no change in the trend of the amount of solar radiation and that the amount of power generation is increasing, as in the table of Fig. 8(b), the control device 10 proceeds to processing in step S113. On the other hand, when the content of the determination data shows that there is a decrease in the amount of solar radiation and that there is no change in the trend of the amount of power generation, as in the table of Fig. 8(c), the control device 10 proceeds to processing in step S115. Note that when the content of the determination data is not any of the above examples, the control device 10 ends the abnormality diagnosis processing.

[0078] In step S113, the control device 10 determines that the cause of the abnormality in the output of the photovoltaic power generation panel 2 is "panel addition (addition of the photovoltaic power generation panel 2)." That is, according to the contents of the processing from step S102 and step S110 to step S113, it is shown that the measured amount of power generation continuously diverges (increases) from the estimated amount of power generation, the absolute value of the deviation rate is relatively large, there is no change in the trend of the amount of solar radiation, and the amount of power generation is increasing. In this case, it is considered that the assumed cause of the current abnormality is the addition of the photovoltaic power generation panel 2 itself (see FIG. 5). After performing the processing of step S113, the control device 10 proceeds to the processing of step S114.

[0079] In step S114, the control device 10 determines that the necessary measure for dealing with the cause determined in the processing of step S113 is to recreate the diagnostic model so as to reflect the addition of the photovoltaic power generation panel 2 ("recreating the diagnostic model") (see FIG. 5). The recreation of the diagnostic model is performed by executing a diagnostic model recreation process (step S15) to be described later. After performing the processing of step S114, the control device 10 ends the abnormality diagnosis process.

[0080] In step S115, which is performed when it is determined in step S112 that the content of the determination data indicates a decrease in the amount of solar radiation and no change in the trend of the amount of power generation, the control device 10 determines that the cause of the abnormality in the output of the photovoltaic power generation panel 2 is a "failure of the actinometer." That is, according to the content of the processing in steps S102, S110 to S112, and S115, the measured amount of power generation continues to diverge (increase) from the estimated amount of power generation, the absolute value of the deviation rate is relatively large, the amount of solar radiation is decreasing, and no change in the trend of the amount of power generation is occurring. In this case, the assumed cause of the abnormality is considered to be a failure of the actinometer (see FIG. 5).

[0081] After performing the process of step S115, the control device 10 proceeds to the process of step S116 and determines that the cause has been eliminated. After performing the process of step S116, the control device 10 ends the abnormality diagnosis process.

[0082] Furthermore, in step S110, if it is determined that the tendency of the deviation rate is "constant deviation" (step S110: constant deviation), the control device 10 proceeds to step S117, where it determines that the cause of the abnormality in the output of the photovoltaic power generation panel 2 is "deviation between the diagnostic model and the actual device, equipment update." That is, the contents of the processes in steps S102, S110, and S117 indicate that the actual measured power generation amount continuously deviates at a constant rate from the estimated power generation amount. In this case, it is estimated that the cause of the abnormality this time is that there was originally an error (deviation) between the estimated power generation amount of the diagnostic model and the actual measured power generation amount of the actual device, or that the equipment (for example, equipment related to the output of the photovoltaic power generation panel 2, such as a power conditioner) has been updated (see FIG. 5).

[0083] After performing the process of step S117, the control device 10 proceeds to the process of step S114 and determines that the necessary measure for the above-mentioned cause is to create a diagnostic model again ("recreate diagnostic model") (see FIG. 5). After performing the process of step S114, the control device 10 ends the abnormality diagnosis process.

[0084] In step S111, if the absolute value of the deviation rate is determined to be "small" (step S111: small), the control device 10 proceeds to step S118, where it determines that the cause of the abnormality in the output of the photovoltaic power generation panel 2 is "cleaning." That is, the contents of the processes in steps S102, S110, S111, and S118 indicate that the actual measured power generation amount continuously deviates (increases) from the estimated power generation amount, and that the absolute value of the deviation rate is relatively small. In this case, it is considered that the deviation rate increased because the soiled photovoltaic power generation panel 2 was cleaned (see FIG. 5).

[0085] After performing the process of step S118, the control device 10 proceeds to the process of step S119 and determines that no action is required for the above cause (see FIG. 5). After performing the process of step S119, the control device 10 ends the abnormality diagnosis process.

[0086] If it is determined in step S110 that the deviation rate is trending downward (step S110: downward), the control device 10 proceeds to step S120, where it determines whether the deviation rate is rapidly decreasing (gradual). The graph in FIG. 7(a) shows an example of a case where the deviation rate changes (declines) rapidly and a case where the deviation rate changes (declines) gradually. The control device 10 determines that the deviation rate is rapidly decreasing if it decreases at a slope of a predetermined angle or more with respect to the deviation rate without abnormalities (solid line), as shown by the dotted line in the example. Furthermore, the control device 10 determines that the deviation rate is not rapidly decreasing (gradual) if it decreases at a slope of less than a predetermined angle with respect to the deviation rate without abnormalities (solid line), as shown by the dashed line in the example. After performing the process of step S120, the control device 10 proceeds to the process of step S121.

[0087] In step S121, the control device 10 determines whether the power generation ratio is generally constant (whether there is variation). Here, the "power generation ratio" is a value obtained by dividing the estimated power generation amount by the actually measured power generation amount. The estimated power generation amount and the actually measured power generation amount in fine weather are used to calculate the power generation ratio. In step S121, the control device 10 determines whether the change in the power generation ratio over time is generally constant. The graph shown in FIG. 9 shows the change in the power generation ratio over time. In the example, the power generation ratio shown by the solid line represents an example when there is no abnormality in the solar power generation panel 2. In addition, the power generation ratio shown by the dashed line in the example is set to be a value that is smaller by a certain percentage than the power generation ratio shown by the solid line. The control device 10 determines that the power generation ratio shown by the dashed line is generally constant. In addition, the power generation ratio shown by the dashed line in the example is set to be a shape that is not constant (has variation) compared to the power generation ratio shown by the solid line. The control device 10 determines that the power generation ratio indicated by the dashed line is not generally constant.

[0088] When the control device 10 determines that the power generation ratio is approximately constant (step S121: approximately constant), the control device 10 proceeds to the process of step S123. On the other hand, when the control device 10 determines that the power generation ratio is not approximately constant (varies) (step S121: varies), the control device 10 proceeds to the process of step S122.

[0089] In step S122, the control device 10 determines that the cause of the abnormality in the output of the photovoltaic power generation panel 2 is a "failure of the panel or the like." That is, according to the processing contents of steps S102, S110, and steps S120 to S122, the actual measured power generation amount is continuously and rapidly decreasing relative to the estimated power generation amount, indicating that the power generation amount ratio is fluctuating. In this case, the possible cause of the abnormality is considered to be a failure of the photovoltaic power generation panel 2 or a device (e.g., a power conditioner) connected to the photovoltaic power generation panel 2 (see FIG. 5).

[0090] After performing the process of step S112, the control device 10 proceeds to the process of step S116 and determines that the cause has been eliminated (see FIG. 5). After performing the process of step S116, the control device 10 ends the abnormality diagnosis process.

[0091] Furthermore, in step S123, which is performed when it is determined in step S121 that the power generation amount ratio is approximately constant (step S121: approximately constant), the control device 10 determines that the cause of the abnormality in the output of the photovoltaic power generation panel 2 is "panel removal (removal of the photovoltaic power generation panel 2)." That is, according to the contents of the processing of steps S102, S110, S120, S121, and S123, this indicates that the actual measured power generation amount is continuously and rapidly decreasing relative to the estimated power generation amount, and that the power generation amount ratio is approximately constant. In this case, it is considered that the assumed cause of the abnormality this time is the removal of the photovoltaic power generation panel 2 itself (see FIG. 5). After performing the processing of step S123, the control device 10 proceeds to the processing of step S124.

[0092] In step S124, the control device 10 determines that the necessary measure for dealing with the above-mentioned factor is to create a diagnostic model again ("recreate diagnostic model") so as to reflect the removal of the photovoltaic power generation panel 2 (see FIG. 5). After performing the process of step S124, the control device 10 ends the abnormality diagnosis process.

[0093] Furthermore, in step S125, which is performed if it is determined in step S120 that the decrease in the deviation rate is not a "sudden decrease" (is gradual), the control device 10 determines that the cause of the abnormality in the output of the photovoltaic power generation panel 2 is "soil." That is, the contents of the processes in steps S102, S110, S120, and S125 indicate that the actual measured power generation amount is continuously decreasing and gradually decreasing relative to the estimated power generation amount. In this case, it is considered that the decrease in the deviation rate is due to the occurrence of soiling on the photovoltaic power generation panel 2 (see FIG. 5).

[0094] After performing the process of step S125, the control device 10 proceeds to the process of step S126 and determines that the cause has been "eliminated" (see FIG. 5). After performing the process of step S126, the control device 10 ends the abnormality diagnosis process.

[0095] The abnormality diagnosis process has been described above. According to the process, it is possible to diagnose whether or not there is an abnormality in the output of the photovoltaic power generation panel 2 and analyze the possible causes of the abnormality using data on "solar radiation amount," "temperature," and "power generation amount." Furthermore, according to the process, it is possible to determine the necessary measures based on the possible causes of the abnormality. The control device 10 can display the results of the analysis of the factors and the results of the determination of the necessary measures on the display unit 15.

[0096] The user can use the analysis results of the above factors to determine whether or not countermeasures are necessary and to estimate the effectiveness of countermeasures. Specifically, if the abnormality diagnosis process determines that the output of the solar panel 2 is "soiled," the user can calculate the amount of power lost (unable to generate power) due to the soiling from the deviation rate calculated in the process. Furthermore, by multiplying the amount of power lost by the electricity selling price, the amount of loss over a certain period (e.g., one year) can be calculated. The user can make a decision on countermeasures by taking into account the results of comparing the amount of loss with the cost of cleaning the solar panel 2. Furthermore, if the solar panel 2 has been cleaned in the past (e.g., if the abnormality diagnosis process determines that "cleaning" is necessary), the amount of power generation restored by cleaning can also be calculated. In this case, the effectiveness of cleaning can also be taken into account when making a decision on countermeasures. The calculation of the amount of loss and the comparison of cleaning costs can also be performed automatically by the processing of the diagnostic system 1.

[0097] Furthermore, in this embodiment, in the abnormality diagnosis process, if the assumed cause of the abnormality is a change in the specifications of the solar power generation panel 2, such as adding or removing solar power generation panels 2, a discrepancy between the diagnostic model and the actual equipment, or an equipment update (steps S113, S117, and S123), a decision is made to "recreate the diagnostic model" so as to reflect the change in specifications.

[0098] Next, the "diagnostic model re-creation process" will be described with reference to Fig. 2 and Fig. 10. The diagnostic model re-creation process is a process for re-creating a diagnostic model when a determination is made in the abnormality diagnosis process that "diagnostic model re-creation" is made as a necessary measure (step S114, step S124). When the diagnostic model re-creation process is executed, new learning data is acquired during the learning period, and a diagnostic model is created using the learning data. Hereinafter, the diagnostic model created using the new learning data may be referred to as a "second diagnostic model."

[0099] In the example shown in Figure 10, a first diagnostic model created using learning data from the learning period (first learning period) from the start of operation of solar panel 2 (January 1, 2020) to January 1, 2021 is used until January 1, 2023 (anomaly diagnosis processing is being executed).

[0100] In the illustrated example, a determination to "recreate a diagnostic model" is made as of January 1, 2023. In this case, the control device 10 detects the determination and executes a diagnostic model re-creation process. In the diagnostic model re-creation process, the control device 10 creates a second diagnostic model using learning data acquired during a new learning period (one year until January 1, 2024) after January 1, 2023. After completing the creation of the second diagnostic model, the control device 10 stores the diagnostic model in the storage unit 11 and terminates the diagnostic model re-creation process. After January 1, 2024, after the second diagnostic model is created, the control device 10 executes an abnormality diagnosis process using the second diagnostic model.

[0101] If the first diagnostic model is used as is to perform the abnormality diagnosis process until the second diagnostic model is created, it is expected that it will be difficult to properly diagnose the solar power generation panel 2. Therefore, the diagnostic system 1 according to this embodiment corrects the value output using the first diagnostic model and estimates the power generation amount for the period until the second diagnostic model is created (the period from January 1, 2023 to January 1, 2024).

[0102] The graph shown in Figure 10 shows the amount of power generated during the period up until the second diagnostic model was created. In the example, the estimated amount of power generated using the first diagnostic model is shown by a solid line. The measured amount of power generated is shown by a dashed line. The measured amount of power generated is lower than the estimated amount of power generated (there is a deviation).

[0103] The control device 10 can execute a process to correct the estimated power generation amount based on the deviation rate calculated in the abnormality diagnosis process so that a value close to the actually measured power generation amount can be calculated. In the correction, the control device 10 calculates, for example, the difference between the estimated power generation amount and the actually measured power generation amount for each hour (for example, a value obtained by multiplying the estimated power generation amount by the deviation rate), and adds the difference to the estimated power generation amount for each hour to obtain the corrected power generation amount. In the example shown in the figure, the corrected power generation amount is indicated by a dashed line. By executing the above process, it is possible to obtain an estimated power generation amount that corresponds to changes in the specifications of the photovoltaic power generation panel 2 (such as the addition of panels) even during the period until the second diagnostic model is created.

[0104] The above describes the diagnostic system 1. Note that the control according to this embodiment is an example, and the control executed by the diagnostic system 1 is not limited to the above example, and any processing may be added or changed. Also, the specific numerical values ​​exemplified in the above description are an example, and can be changed as desired.

[0105] For example, in the above-described abnormality diagnosis process, in the process of step S102, a determination is made as to whether the change in the deviation rate is "continuous" or "temporary." However, instead of or in addition to the above determination, a determination as to whether the change in the deviation rate is "periodic" or not may be added. In this case, the determination result as to whether the change is "periodic" or not can be used for analyzing the cause.

[0106] In the above example, the estimated power generation amount and the measured power generation amount are obtained by hour (hour), day, and month, but the present invention is not limited to this example. For example, the estimated power generation amount and the measured power generation amount may be obtained by week, season (for example, every three months), or year.

[0107] Furthermore, in the above example, the diagnostic system 1 capable of diagnosing the photovoltaic power generation panel 2 has been described, but the present invention is not limited to the above example. For example, the diagnostic system 1 can also be applied to a solar heat collection panel (not shown) capable of collecting solar heat. That is, the diagnostic system 1 can also diagnose abnormalities in the solar heat collection panel instead of the photovoltaic power generation panel 2.

[0108] In this case, the diagnostic system 1 can execute the diagnostic model creation process, the abnormality diagnosis process, and the diagnostic model re-creation process based on the heat quantity of the solar thermal collection panel instead of the power generation amount of the solar photovoltaic power generation panel 2. Note that the contents of each process when the diagnostic system 1 is applied to a solar thermal collection panel are generally similar except for the point that the heat quantity is used instead of the power generation amount, so detailed explanations will be omitted.

[0109] As described above, the diagnostic system 1 (solar power equipment diagnostic system) according to this embodiment: A diagnostic system 1 that diagnoses the amount of energy of a solar power generation panel 2 (solar power equipment) that obtains energy by using sunlight, a diagnostic model creation unit (control device 10) that creates a diagnostic model based on learning data related to the solar power generation panel 2 measured during a learning period (step S10); an estimate value calculation unit (control device 10) that uses the diagnostic model to calculate an estimated amount of power generated by the solar power generation panel 2 during a judgment period based on judgment data related to the solar power generation panel 2 measured during the judgment period after the learning period has elapsed (step S12); and a deviation information acquisition unit (control device 10) capable of acquiring (step S13) deviation information (deviation rate) indicating a deviation between the actual power generation amount (actual measured value of the amount of energy) of the solar power generation panel 2 measured during the determination period and the estimated power generation amount; an abnormality factor determination unit (control device 10) that can determine the factor of an abnormality related to the amount of energy of the solar power generation panel 2 based on the deviation information (deviation rate) (step S14); It is equipped with the following.

[0110] This configuration makes it possible to suitably diagnose abnormalities in the output of the solar power generation panel 2. That is, by determining the cause of the abnormality in the output of the solar power generation panel 2 based on the deviation information (deviation rate), it is possible to suitably diagnose abnormalities in the output of the solar power generation panel 2.

[0111] Furthermore, the diagnostic system 1 according to this embodiment includes: A diagnostic system 1 that diagnoses the amount of energy of a solar power generation panel 2 (solar power equipment) that obtains energy by using sunlight, a diagnostic model creation unit (control device 10) that creates a diagnostic model based on learning data related to the solar power generation panel 2 measured during a learning period (step S10); an estimate value calculation unit (control device 10) that uses the diagnostic model to calculate an estimated amount of power generated by the solar power generation panel 2 during a judgment period based on judgment data related to the solar power generation panel 2 measured during the judgment period after the learning period has elapsed (step S12); and a deviation information acquisition unit (control device 10) capable of acquiring (step S13) deviation information (deviation rate) indicating a deviation between the actual power generation amount (actual measured value of the amount of energy) of the solar power generation panel 2 measured during the determination period and the estimated power generation amount; a diagnostic model update unit (control device 10) that updates the diagnostic model based on the deviation information (deviation rate) (step S15); It is equipped with the following.

[0112] This configuration makes it possible to suitably diagnose abnormalities in the output of the solar power generation panel 2. That is, by updating the diagnostic model based on the deviation information (deviation rate), it is possible to suitably diagnose abnormalities in the output of the solar power generation panel 2.

[0113] Furthermore, the diagnostic system 1 according to this embodiment includes: an abnormality factor determination unit (control device 10) that can determine the factor of an abnormality related to the amount of energy of the solar power generation panel 2 based on the deviation information; a diagnostic model update unit (control device 10) that updates the diagnostic model based on the deviation information; Equipped with The cause of the abnormality regarding the amount of energy of the solar power generation panel 2 includes a cause related to a change in the specifications of the solar power generation panel 2, The diagnostic model update unit (control device 10) If the determination result of the abnormality factor determination unit (control device 10) is that the factor is related to a change in the specifications of the solar power generation panel 2 (steps S113, S117, and S123), the diagnostic model is updated (steps S114 and S124).

[0114] With this configuration, it is possible to determine the cause of the change in the specifications of the photovoltaic power generation panel 2 based on the deviation information, and to update the diagnostic model based on the determination result.

[0115] The deviation information acquisition unit (control device 10) As the deviation information, a deviation rate, which is the rate of difference between the estimated amount of power generation and the actually measured amount of power generation, can be acquired (step S13).

[0116] With this configuration, it is possible to determine the cause of the change in the specifications of the photovoltaic power generation panel 2 based on the deviation rate.

[0117] Furthermore, the diagnostic system 1 according to this embodiment includes: Equipped with a pyranometer that can measure the amount of solar radiation, Factors related to changes in the specifications of the solar power generation panel 2 include: The addition of the solar power generation panel 2 is included, The abnormality factor determination unit If the deviation rate continues to increase and there is no change in the amount of solar radiation (steps S102, S112), it is determined that the solar power generation panel 2 has been added (step S113), and the determination result is output.

[0118] By configuring in this way, it is possible to suitably determine whether to add more photovoltaic panels 2 based on the deviation rate.

[0119] In addition, factors related to changes in the specifications of the solar power generation panel 2 include: The removal of the solar power generation panel 2 is included, If the deviation rate drops suddenly and the change in the ratio between the estimated power generation amount and the measured power generation amount remains constant (steps S120 and S121), it is determined that the photovoltaic power generation panel 2 is being removed (step S123), and the determination result is output.

[0120] By configuring in this way, it is possible to suitably determine whether to add more photovoltaic panels 2 based on the deviation rate.

[0121] The diagnostic model update unit (control device 10) The diagnostic model is updated by having the diagnostic model creation unit (control device 10) create a second diagnostic model that is different from the first diagnostic model, which is the diagnostic model before the update, using the learning data measured during the new learning period (step S15).

[0122] With this configuration, it is possible to obtain an estimated amount of power generation based on a new diagnostic model that corresponds to changes in the specifications of the photovoltaic power generation panel 2.

[0123] The diagnostic model update unit (control device 10) Until the second diagnostic model is created, the first diagnostic model is corrected using the deviation rate, thereby updating the diagnostic model.

[0124] By configuring in this manner, it is possible to obtain an estimated power generation amount that corresponds to changes in the specifications of the solar power generation panel 2 (such as adding more panels) even before new learning data is collected and a new diagnostic model is created.

[0125] The control device 10 according to this embodiment is an embodiment of the diagnostic model creation unit, the estimated value calculation unit, the deviation information acquisition unit, the abnormality factor determination unit, and the diagnostic model update unit according to the present invention. The solar power generation panel 2 according to this embodiment is one embodiment of the solar power equipment according to the present invention.

[0126] Although one embodiment of the present invention has been described above, the present invention is not limited to the above configuration, and various modifications are possible within the scope of the invention described in the claims.

[0127] For example, in the present embodiment, the diagnostic system 1 includes only the control device 10, but the present invention is not limited to this. For example, in addition to the control device 10, an actinometer, a thermometer, a solar power generation panel 2, and a solar heat collection panel may be included.

[0128] In addition, in this embodiment, the data used for diagnosis is the "amount of solar radiation," "temperature," and "amount of power generation (heat)," but the present invention is not limited to this. For example, other data may be used instead of or in addition to the "amount of solar radiation," "temperature," and "amount of power generation (heat)."

[0129] In addition, in the present embodiment, an example has been shown in which the diagnostic system 1 and the photovoltaic power generation panel 2 (solar heat collection panel) are applied to a facility of a business such as a factory, but the present invention is not limited to this. For example, the diagnostic system 1 and the photovoltaic power generation panel 2 (solar heat collection panel) may be applied to a house or the like. [Explanation of symbols]

[0130] 1 Diagnostic System 2. Solar panels 10 Control device

Claims

1. A solar power device diagnostic system that diagnoses the amount of energy of a solar power device that obtains energy by utilizing sunlight, a diagnostic model creation unit that creates a diagnostic model based on learning data related to the solar power equipment measured during a learning period; an estimated value calculation unit that calculates an estimated value of the amount of energy of the solar-powered device during a determination period after the learning period has elapsed, using the diagnostic model, based on determination data related to the solar-powered device measured during the determination period; a deviation information acquisition unit capable of acquiring deviation information indicating a deviation between an actual measurement value of the amount of energy of the solar device measured during the determination period and the estimated value; an abnormality factor determination unit capable of determining a factor of an abnormality related to the amount of energy of the solar power device based on the deviation information; Equipped with Solar equipment diagnostic system.

2. A solar power device diagnostic system that diagnoses the amount of energy of a solar power device that obtains energy by utilizing sunlight, a diagnostic model creation unit that creates a diagnostic model based on learning data related to the solar power equipment measured during a learning period; an estimated value calculation unit that calculates an estimated value of the amount of energy of the solar-powered device during a determination period after the learning period has elapsed, using the diagnostic model, based on determination data related to the solar-powered device measured during the determination period; a deviation information acquisition unit capable of acquiring deviation information indicating a deviation between an actual measurement value of the amount of energy of the solar device measured during the determination period and the estimated value; a diagnostic model update unit that updates the diagnostic model based on the deviation information; Equipped with Solar equipment diagnostic system.

3. an abnormality factor determination unit capable of determining a factor of an abnormality related to the amount of energy of the solar power device based on the deviation information; a diagnostic model update unit that updates the diagnostic model based on the deviation information; Equipped with The cause of the abnormality regarding the amount of energy of the solar power equipment includes a cause related to a change in the specifications of the solar power equipment; The diagnostic model update unit updating the diagnostic model when the determination result of the abnormality factor determination unit is a factor related to a change in the specifications of the solar power equipment; The solar power equipment diagnostic system according to claim 1 or 2.

4. The deviation information acquisition unit As the deviation information, a deviation rate, which is a ratio of a difference between the estimated value and the actual measured value, can be acquired. The solar power equipment diagnostic system according to claim 3 .

5. Equipped with a pyranometer that can measure the amount of solar radiation, Factors related to changes in the specifications of the solar equipment include: The expansion of the solar power equipment is included. The abnormality factor determination unit If the deviation rate continues to increase and there is no change in the amount of solar radiation, it is determined that the solar power equipment is being added, and a determination result is output. The solar power equipment diagnostic system according to claim 4.

6. Factors related to changes in the specifications of the solar equipment include: This includes reducing the installation of the solar power equipment. When the deviation rate drops sharply and the change in the ratio between the estimated value and the actual measurement value is constant, it is determined that the solar power equipment is being reduced, and a determination result is output. The solar power equipment diagnostic system according to claim 4.

7. The diagnostic model update unit updating the diagnostic model by causing the diagnostic model creation unit to create a second diagnostic model different from the first diagnostic model, which is the diagnostic model before updating, using the learning data measured in a new learning period; The solar power equipment diagnostic system according to claim 4.

8. The diagnostic model update unit updating the diagnostic model by correcting the first diagnostic model using the deviation rate until the second diagnostic model is created; The solar power equipment diagnostic system according to claim 7.

Images