Abnormality inspection method and abnormality inspection device

Abstract

To provide an abnormality inspection method in which the influence of a factor depending on an installation condition can be eliminated, the accuracy of determining an abnormality is improved, and an automatic determination can be made.SOLUTION: An abnormality inspection method for detecting an abnormality in a facility generating power with a solar battery cell is performed by an abnormality inspection device that determines an abnormality detection target that is abnormal on the basis of data on the power generation amounts of a plurality of abnormality detection targets. The method includes a correction step of correcting the data on the power generation amounts of the abnormality detection targets on the basis of factors depending on the installation conditions of the abnormality detection targets, a deviation value calculation step of obtaining, for a group consisting of several abnormality detection targets, a deviation value of the power generation amount of each of the abnormality detection targets on the basis of the data on the power generation amounts corrected by the correction step, and a determination step of determining an abnormality detection target that is abnormal on the basis of the deviation values of the respective abnormality detection targets calculated by the deviation value calculation step.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an abnormality inspection method and an abnormality inspection device for photovoltaic power generation. [Background technology]

[0002] Due to the effects of global warming, solar power generation, which can generate electricity without using fossil fuels, has attracted attention, and solar power plants are being established all over the country. Recently, solar power plants known as mega solar power plants have also appeared. Solar power generation facilities consist of one or more arrays in which modules (panels), each of which has solar cells connected in series, are connected in series to form a string, and these strings are further combined in parallel.

[0003] In a photovoltaic power plant, in order to obtain a stable amount of power generation, it is important to monitor equipment such as photovoltaic power generation strings and arrays, to find the occurrence and location of an abnormality early, and to perform maintenance inspection such as repairing or replacing the abnormal part. For this reason, various anomaly determination devices for determining anomalies in photovoltaic power generation equipment have been proposed.

[0004] For example, since the amount of power generated by photovoltaic power generation depends on the amount of solar radiation and the environmental temperature (panel temperature), it is conceivable to detect anomalies by installing a solar radiation meter and a thermometer at a photovoltaic power plant to measure the amount of solar radiation and the temperature of the panels and determining whether the expected amount of power generation predicted based on the measurement results is being obtained. However, solar radiation meters and thermometers have measurement errors, and strictly speaking, it is not possible to obtain an accurate expected amount of power generation, making it difficult to determine whether an abnormality exists.

[0005] As a solution to this problem, for example, Patent Document 1 (JP 2012-190947 A) provides an anomaly detection system in which, in a solar power generation system consisting of multiple solar power generation devices, a change-over switch is provided for each device to control its operation, and at a preset period, a power generation measuring device measures the measurement value when a device is stopped (change-over switch is off) and the measurement value when each device is operating, and determines whether each device has failed based on the magnitude of the difference between the measured values.

[0006] Furthermore, for example, Patent Document 2 (JP 2015-99858 A) provides an abnormality determination device that includes a current detection unit that detects the string current of each string, and a deviation calculation unit that calculates an average value of the string currents detected from multiple strings and calculates the deviation from the average value for each string current, and determines which strings among multiple strings are abnormal based on the deviation of each string current calculated by the deviation calculation unit. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] JP 2012-190947 A [Patent Document 2] JP 2015-99858 A Summary of the Invention [Problem to be solved by the invention]

[0008] However, in the anomaly detection system of the cited document 1, it is necessary to provide a changeover switch for each of a plurality of photovoltaic power generation devices and to turn the changeover switch on and off, which increases costs. In addition, it is necessary to stop each device in sequence to perform a fault diagnosis, which causes a problem that the photovoltaic power generation system is essentially out of operation during the fault diagnosis.

[0009] The abnormality determination device of Patent Document 2 does not require a changeover switch as in Patent Document 1. However, the abnormality determination device of Patent Document 2 performs abnormality determination based on the deviation between the average value of the string current obtained in a certain time period (time point) and the string current in the same time period (time point), and therefore does not take into consideration the installation conditions (including the installation environment) of each string, which change from moment to moment, resulting in a problem that it may be impossible to distinguish whether the deviation in each string current is due to an abnormality in the string or due to a factor related to the installation conditions.

[0010] SUMMARY OF THE PRESENT EMBODIMENT An object of the present invention is to provide an abnormality inspection method capable of solving the above problems. [Means for solving the problem]

[0011] In order to solve the above problems, An abnormality inspection method for detecting an abnormality in equipment that generates power using solar cells, the method being performed by an abnormality inspection device that determines whether an abnormality detection target is abnormal based on power generation amount data of a plurality of abnormality detection targets, comprising: a correction step of correcting the power generation amount data of the abnormality detection target based on factors due to an installation condition of the abnormality detection target; a deviation value calculation step of calculating a deviation value of the power generation amount of each of the abnormality detection targets in a group consisting of a plurality of the abnormality detection targets based on the power generation amount data corrected in the correction step; a determination step of determining whether the abnormality detection target is abnormal based on the deviation value of each of the abnormality detection targets calculated in the deviation value calculation step; The present invention provides an abnormality inspection method having the steps of:

[0012] In the anomaly inspection method configured as described above, a correction step performs correction based on factors related to the installation conditions of the abnormality detection targets, and a deviation value calculation step calculates a deviation value of the power generation amount of each of the abnormality detection targets in a group consisting of multiple abnormality detection targets based on the power generation amount data.The abnormality detection targets are then judged to be abnormal based on the deviation values ​​of each of the abnormality detection targets thus calculated. Effect of the Invention

[0013] According to the anomaly inspection method of the present invention, the influence of factors due to the installation conditions of the object of anomaly detection can be eliminated, so that the accuracy of anomaly determination for the object of anomaly detection is improved and automatic determination becomes possible. [Brief description of the drawings]

[0014] [Figure 1] 1 is a block diagram showing an example of the configuration of an abnormality inspection system to which an embodiment of an abnormality inspection method according to the present invention is applied; [Diagram 2] 2 is a diagram showing an example of the configuration of a photovoltaic power plant that is an inspection target in the anomaly inspection system of the example of FIG. 1. [Diagram 3] 1. FIG. 4 is a diagram showing another example of the configuration of a photovoltaic power plant that is an inspection target in the anomaly inspection system in the example of FIG. [Figure 4] 10A and 10B are diagrams showing an example of collected raw power generation data in the embodiment of the anomaly inspection method according to the present invention; [Diagram 5] 11A and 11B are diagrams showing examples of deviation value data calculated from collected power generation amount data in the embodiment of the anomaly inspection method according to the present invention. [Figure 6] 13 is a diagram showing another example of deviation value data calculated from collected power generation amount data in the embodiment of the anomaly inspection method according to the present invention. FIG. [Figure 7] FIG. 2 is a diagram showing a part of a flowchart for explaining the operation of a main part of an embodiment of an abnormality inspection method according to the present invention. [Figure 8] FIG. 2 is a diagram showing a part of a flowchart for explaining the operation of a main part of an embodiment of an abnormality inspection method according to the present invention. [Figure 9] 13 is a diagram showing another example of the configuration of a photovoltaic power plant to be inspected in an abnormality inspection system to which an embodiment of the abnormality inspection method according to the present invention is applied. FIG. [Figure 10] 13 is a diagram showing another example of the configuration of a photovoltaic power plant to be inspected in an abnormality inspection system to which an embodiment of the abnormality inspection method according to the present invention is applied. FIG. [Figure 11] 13 is a diagram showing another example of the configuration of a photovoltaic power plant to be inspected in an abnormality inspection system to which an embodiment of the abnormality inspection method according to the present invention is applied. FIG. [Figure 12] 13 is a diagram showing another example of the configuration of a photovoltaic power plant to be inspected in an abnormality inspection system to which an embodiment of the abnormality inspection method according to the present invention is applied. FIG. [Figure 13] FIG. 13 is a diagram showing another example of the configuration of an abnormality inspection system to which the embodiment of the abnormality inspection method according to the present invention is applied. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] Hereinafter, an embodiment of the anomaly inspection method according to the present invention will be described with reference to the drawings. FIG. 1 is a block diagram showing an example of the configuration of an anomaly inspection system to which an embodiment of the anomaly inspection method according to the present invention is applied. In the example of the anomaly inspection system in FIG. 1, the inspection target is a photovoltaic power plant 1, and a remote monitoring server 2 and an anomaly inspection server 3 are connected to this photovoltaic power plant 1 via a network 4. In this embodiment, the photovoltaic power plant 1 to be inspected has the configuration shown in FIG. 2 or FIG. 3, and the target for abnormality detection is a string unit.

[0016] [Explanation of the configuration example of solar power plant 1] The solar power plant 1 in the example of FIG. 2 includes a plurality of arrays 13 in which a plurality of strings 12, each of which is formed by connecting modules (panels) 11 in series, each of which has solar cell cells connected in series, are connected in parallel. The power generation output (DC) of each of the plurality of strings 12 in each array 13 is supplied to a connection box 14 provided for each array 13. The connection box 14 synthesizes (adds) the power generation output of each of the plurality of strings 12 in each array 13 connected thereto, and supplies the result to a power conditioner 15. The power conditioner 15 receives and synthesizes (adds) the DC power generation output from the plurality of connection boxes 14, converts it to AC, and outputs it to a substation 16. The output of the power conditioner 15 may be used for selling electricity as in the example shown in the figure, or may be used for a load.

[0017] 2, the strings 12 are treated as units for detecting abnormalities in the abnormality inspection, and power generation detection and transmission devices PDs that detect the amount of power generated by each string 12 and transmit the detected amount to the remote monitoring server 2 via the network 4 (either wirelessly or via a wired connection) are provided in the junction box 14 for each string 12. As will be described later, it becomes possible to diagnose abnormalities for each string 12 based on the amount of power generated detected by the power generation detection and transmission devices PDs. Note that the power generation detection and transmission devices PDs may be provided for each string 12 in the array 13, rather than in the junction box 14.

[0018] The solar power plant 1 in the example of Fig. 3 also includes a plurality of arrays 13 in which a plurality of strings 12, each of which is formed by connecting modules (panels) 11 in series, are connected in parallel. In the example of Fig. 3, the power generation output (DC) of each of the plurality of strings 12 in each array 13 is supplied to a power conditioner 17 provided for each array 13. The power conditioner 17 combines (adds) the DC power generation outputs of the plurality of strings 12 in each array 13 connected thereto, converts it to AC, and supplies it to a current collection box 18. The current collection box 18 combines the AC power generation outputs from the plurality of power conditioners 17 and supplies them to each of the loads 16.

[0019] 3, the string 12 is treated as the unit of abnormality detection in the abnormality inspection, and power generation detection and transmission devices PDs that detect the amount of power generated in each string 12 and transmit the amount of power generated to the remote monitoring server 2 via the network 4 are provided in the PCS 17 for each string 12, making it possible to diagnose abnormalities for each string 12 based on the amount of power generated detected by the power generation detection and transmission devices PDs. Note that the power generation detection and transmission devices PDs may be provided for each string 12 in the array 13, rather than in the PCS 17.

[0020] In this embodiment, each of the power generation detection and transmission devices PDs includes a transmission unit that sequentially transmits data on the detected amount of power generation of the string 12 (power generation data) over time. In this case, each of the power generation detection and transmission devices PDs includes a storage unit that stores identification information unique to each device, and transmits the power generation data with the identification information added thereto. In this embodiment, each of the power generation detection and transmission devices PDs also transmits time information indicating the time when the power generation amount was detected. In this embodiment, each of the power generation detection and transmission devices PDs transmits the power generation data with the identification information and time information added thereto to the remote monitoring server 2 via the network 4. The power generation detection and transmission devices PDs may be configured to transmit the power generation data to the remote monitoring server 2 via a wired connection.

[0021] In this example, the power generation detection and transmission device PDs has a clock circuit with a calendar function, and obtains the time (year, month, day, hour, minute, and second) when the power generation amount is detected from the clock circuit, and transmits the time together with the identification information to be transmitted. Note that the time information to be transmitted by adding to the power generation amount data may be the transmission time of the power generation amount data.

[0022] The power generation detection / transmission devices PDs detect and transmit the amount of power generation at an hourly or several hourly interval when the abnormality inspection is performed on a daily basis, for example, detect and transmit the amount of power generation at a daily interval, for example, at a specific time of a day when the abnormality inspection is performed on a monthly basis, and detect and transmit the amount of power generation at a monthly interval, for example, at a specific time on a specific day such as the last day of each month when the abnormality inspection is performed on a yearly basis.

[0023] In the example of Fig. 2, the power generation amount detection / transmission device PDs is provided for each string 2 in the junction box 14, and in the example of Fig. 3, the PCS 17. However, the detection and transmission of the power generation amount may be performed by different devices. That is, for example, the junction box 14 or the PCS 17 may be provided with a plurality of power generation amount detection devices for detecting the power generation amount for each string 12, and a transmission device for transmitting the power generation amount data (with identification information and time information) for each string detected by each of the plurality of power generation amount detection devices collectively to the remote monitoring server 2 via the network 4. When the detection and transmission of the power generation amount are performed by different devices, the transmission device may be provided in the PCS 15 in the example of Fig. 2, or in the current collection box 18 in the example of Fig. 3. In this case, the connection between the power generation amount detection device and the transmission device may be wireless or wired.

[0024] [Explanation of the configuration example of remote monitoring server 2] The remote monitoring server 2 includes a power generation data collection means 21 and a power generation data transfer means 22. The power generation data collection means 21 and the power generation data transfer means 22 are configured as functional means executed by a software program in a control unit 20 configured, for example, by a computer.

[0025] The power generation data collecting means 21 receives the power generation data sent from each of the power generation detection / transmission devices PDs in the photovoltaic power plant 1, classifies the data according to the identification information of each of the power generation detection / transmission devices PDs, and stores the data together with time information added to the power generation data. That is, the power generation data of each of the power generation detection / transmission devices PDs is stored as time-series data in a memory (buffer memory) built in the power generation data collecting means 21.

[0026] In this embodiment, the power generation amount detection / transmission device PDs detects the amount of power generation at a preset date and time, and the power generation amount data collection means 21 collects the power generation amount data based on a schedule in which the power generation amount detection / transmission device PDs detects the amount of power generation at a preset date and time, and transmits the detected data of the amount of power generation to the power generation amount data collection means 21. However, the power generation amount data may be collected by sending a transmission request to the power generation amount detection / transmission device PDs at a preset date and time by the power generation amount data collection means 21, and the power generation amount detection / transmission device PDs transmits the amount of power generation detected at that date and time in response to the request.

[0027] In this embodiment, the time information stored together with the power generation amount data is the power generation amount data with time information added thereto and transmitted from the power generation amount detection and transmission device PDs, but information on the reception time (year, month, day, hour, minute, and second) of the power generation amount data in the charge amount data collection means 21 may be used. In that case, the power generation amount detection and transmission device PDs does not need to add time information to the power generation amount data to be transmitted, and therefore does not need to be provided with a clock circuit with a calendar function.

[0028] In addition, when the photovoltaic power plant 1 is large-scale, the arrays 13 and strings 12 to be inspected may be divided into a plurality of groups, and each divided group may be assigned a different identification information, and an abnormality inspection may be performed for each group to determine whether or not an abnormality exists. In this case, the power generation amount data transmitted from the power generation amount detection / transmission device PDs is assigned with the identification information of the group in addition to the identification information of the power generation amount detection / transmission device PDs.

[0029] When the power generation data transfer means 22 receives a request to transfer power generation data from the abnormality inspection server 3, it transmits the power generation data (including identification information and time information) stored in the buffer memory of the power generation data collection means 21 to the abnormality inspection server 3.

[0030] [Explanation of an example configuration of anomaly inspection server 3] The abnormality inspection server 3 includes a power generation amount data obtaining means 31, a correction means 32, a deviation value calculation means 33, an abnormality determination means 34, a data / result storage means 35, and a determination result notifying means 36. The power generation amount data obtaining means 31, the correction means 32, the deviation value calculation means 33, the abnormality determination means 34, the data / result storage means 35, and the determination result notifying means 36 are configured as functional means executed by a software program in a control unit 30 configured by, for example, a computer.

[0031] The power generation data acquisition means 31 transmits a request for transferring power generation data to the remote monitoring server 2 at a time set according to a predetermined repetition period of the abnormality inspection, and acquires the power generation data sent from the remote monitoring server 2 in response to the request and stores it in a buffer memory. For example, when the abnormality inspection is repeatedly performed on a daily basis, the power generation data acquisition means 31 acquires and stores one day's worth of power generation data (time series data) detected at a time in one hour or several hours at a set time, such as midnight of the following day. For example, when the abnormality inspection is performed on a monthly basis, the power generation data acquisition means 31 acquires and stores one month's worth of power generation data (time series data) detected at a specific time on a daily basis at a set time, such as the first day of the following month. For example, when the abnormality inspection is performed on a yearly basis, the power generation data acquisition means 31 acquires and stores one year's worth of power generation data (time series data) detected at a specific time on a specific day, such as the last day of each month, at a set time, such as the first day of the first month of the following year.

[0032] In this case, the power generation data is detected for each string 12 as described above, and since the power generation data is added with identification information corresponding to each string 12, the power generation data acquisition means 31 stores the power generation data by classifying it into units of each string using the identification information. Figure 4 shows an example of the acquired power generation data (raw data). In this Figure 4, the vertical axis indicates the amount of power generation and the horizontal axis indicates time, and it shows one month's worth of power generation data acquired daily in the case of performing an abnormality inspection on a monthly basis.

[0033] The correction means 32 corrects the obtained power generation amount data based on factors depending on the installation conditions of each string 12. The correction means 32 pre-stores, for each string, information on the installation conditions determined when the photovoltaic power plant 1 is installed and correction information depending on the installation conditions based on other factors. The stored correction information is a correction coefficient value determined based on factors of the installation conditions, and by multiplying the obtained power generation amount data by the correction coefficient value, the power generation amount data is corrected so that the power generation amount data can be compared under the same conditions.

[0034] The factors of the installation conditions for obtaining the correction information are, for example, the number and capacity of modules (panels) for each string 12, the panel azimuth angle, the panel mounting angle, the amount of overloading, and other special factors (partial shading, dirt on the panel surface, etc.). The amount of solar radiation for each string 12 and the environmental temperature may also be included as factors.

[0035] The deviation value calculation means 33 calculates the deviation value for each string 12 based on the power generation amount data corrected by the correction means 32, using the following (Equation 1).

[0036] Deviation value = (power generation of the relevant string 12 - average power generation of all strings 12) ÷ standard deviation ×10+50 (Formula 1) In this embodiment, the deviation value calculation means 33 calculates the deviation value for each string 12 at each time point of the power generation amount data, which is time series data. That is, in this example, the deviation value is obtained as time series data. Fig. 5 is an example of time series data of the deviation value calculated for each string 12 calculated from the power generation amount data (raw data) shown in Fig. 4. The vertical axis indicates the deviation value, and the horizontal axis indicates time.

[0037] The abnormality determination means 34 determines whether a string 12 is abnormal based on the time series data of the deviation value calculated by the deviation value calculation means 33. In this example, the abnormality determination means 34 performs two types of determination. In the first determination, when the time series data of the deviation value calculated by the deviation value calculation means 33 shows a sudden deterioration from a steady deviation value of around 50 as shown by the thick line in Fig. 6, the string 12 exhibiting such a deviation value change is determined to be abnormal. In this case, the criterion for "sudden deterioration" is, for example, a deterioration of the deviation value by "5" or more, or a deterioration of the deviation value by 10% or more.

[0038] In the second judgment, the abnormality judgment means 34 first provisionally judges, as an abnormal string, a string 12 whose time-series data of the deviation value calculated by the deviation value calculation means 33 is constantly low enough to be assumed to be abnormal. In provisionally judging a string as abnormal, for example, in the case of relative evaluation, a method is used in which strings 12 within the lowest 10% of deviation values ​​are judged as abnormal, or strings 12 exhibiting each of the lowest five deviation values ​​are judged as abnormal, or strings 12 with a deviation value of 40 or less are judged as abnormal.

[0039] As described above, since the strings 12 are ranked based on the relative evaluation of the deviation values ​​and provisionally determined to be abnormal, there is a risk that even normal strings 12 may be erroneously determined to be abnormal. Therefore, in the second determination, the abnormality determination means 34 further performs a significant difference test on the power generation amount of the strings 12 provisionally determined to be abnormal based on the deviation values ​​calculated by the deviation value calculation means 33. In this case, the significant difference test uses the power generation amount data corrected by the correction means 32. Then, in the second determination, the strings 12 determined to have a significant difference in the significant difference test are determined to be abnormal, and the strings determined to have no significant difference are not determined to be abnormal.

[0040] In this significant difference test, a significant difference test is performed to compare the power generation amount of a string determined to be normal in the deviation value evaluation with the power generation amount of a string determined to be abnormal. The significant difference test is a known statistical method, and therefore details are omitted here. Note that the provisional abnormality determination and significant difference test in the second determination may be performed using a value at a specific sampling point in time of the power generation amount, or may use the entire time series data of the power generation amount.

[0041] In this case, the strings determined to be normal by the deviation value evaluation used in the significant difference test are those having a deviation value that is consistently close to 50 from among all the strings 12 in the photovoltaic power plant 1. Alternatively, the strings determined to be normal by the deviation value evaluation used in the significant difference test may be those having a deviation value that is consistently close to 50 from among the array 13 that includes the string 12 determined to be abnormal. In the latter case, a normal string is determined from among strings having an installation situation or environment similar to that of the string 12 determined to be abnormal, so that it is expected that a more effective significant difference test can be performed.

[0042] The abnormality determination means 34 generates a list (abnormality list) of strings 12 determined to be abnormal as described above as a determination result. In this abnormality list, identification information of the strings 12 determined to be abnormal is recorded.

[0043] The data / result storage means 35 stores the raw power generation data obtained from the remote monitoring server 2, the power generation data corrected by the correction means 32, and the time series data of the deviation value calculated by the deviation value calculation means 33, as well as stores an anomaly list as the judgment result generated by the anomaly judgment means 34.

[0044] The judgment result notifying means 36 reads out the abnormality list of the judgment results stored in the data / result storage means 35, and notifies the judgment result by display and / or voice (including voice messages, alarm sounds, etc.). In this case, since the abnormality list contains identification information of the strings 12 judged to be abnormal as described above, the judgment result notifying means 36 notifies the strings 12 judged to be abnormal so that they can be distinguished from other strings 12 as follows.

[0045] That is, in this embodiment, the abnormality inspection server 3 stores a correspondence table between the multiple arrays 13 in the photovoltaic power plant 1 and each of the multiple strings 12 constituting each array, and the identification information of the strings 12, and it is possible to determine, from the correspondence table, in which array 13 and in which position the string 12 corresponding to each identification information is located. Therefore, in the determination result notifying means 36, in the photovoltaic power plant 1, the position of the string 12 determined to be abnormal can be detected by the identification information in the abnormality list.

[0046] In this embodiment, the determination result notifying means 36 displays, for example, a schematic diagram that makes it possible to distinguish the positions of the multiple arrays 13 in the photovoltaic power plant 1 and the strings 12 that constitute each array 13, and displays the strings 12 at positions determined to be abnormal in the schematic diagram so that they can be distinguished from other strings by flashing or surrounding them with a thick frame, so that they can be seen at a glance. Then, the discovery of an abnormal string 12 is notified by an alarm sound, etc.

[0047] In this embodiment, the determination result notifying means 36 also transmits the anomaly list to a notification destination registered in advance. The registered notification destination may be the manager of the photovoltaic power plant 1 or the like, and the determination result notifying means 36 registers, for example, an email address of the notification destination, and the anomaly list is transmitted by email, for example, as the body of an email or as an attachment.

[0048] Therefore, the manager of the photovoltaic power plant 1, for example, can store in a personal computer or smartphone a correspondence table between the multiple arrays 13 of the photovoltaic power plant 1 and each of the strings 12 constituting each array, and the identification information of the strings 12, in the same manner as the abnormality inspection server 3, and can determine from the correspondence table which array 13 and which string 12 corresponds to each identification information. For example, a schematic diagram that enables the determination of the positions of the multiple arrays 13 of the photovoltaic power plant 1 and the strings 12 constituting each array can be displayed on a personal computer or smartphone, and the string 12 at a position determined to be abnormal based on the abnormality list can be displayed at a glance by flashing or surrounding it with a thick frame so as to be distinguishable from other strings.

[0049] The determination result notifying means 36 may be provided in the remote monitoring server 2 instead of in the abnormality inspection server 3, and the abnormality list may be sent from the abnormality inspection server 3 to the remote monitoring server 2.

[0050] [Explanation of an example of operation of anomaly detection server 3] Next, an example of the operation of the abnormality inspection server 3 will be described. Figs. 7 and 8 are diagrams showing flowcharts for explaining an example of the operation of mobile inspection in the abnormality inspection server 3 in this embodiment. In the following explanation, each step of the flowcharts in Figs. 7 and 8 will be explained as being executed by the control unit 30 of the abnormality inspection server 3 according to a software program. Note that what is described as an abnormality detection target in Figs. 7 and 8 is the string 12 in this example, so in the following explanation, the abnormality detection target will be replaced with the string 12.

[0051] In this embodiment, the control unit 30 starts the abnormality inspection process from "START" in FIG. 7 at a time that is predetermined according to the period of the abnormality inspection, such as daily, monthly, or yearly.

[0052] In this example, the control unit 30 first sends a request to obtain power generation data to the remote monitoring server 2, obtains the power generation data (time series data; see Figure 4) required for inspection from the remote monitoring server 2, and stores the obtained power generation data in a buffer memory (step S101).

[0053] Next, the control unit 30 corrects the power generation amount data for each of the strings 12 using a correction coefficient value that is determined and stored based on factors related to the installation conditions of each of the strings 12 (step S102).

[0054] Next, the control unit 30 uses the power generation amount data corrected in step S102 to calculate the deviation value of each string 12 using the above-mentioned (Equation 1), and obtains time series data of the deviation value of each string 12 as shown in Figure 5 (step S103).

[0055] Next, the control unit 30 judges whether or not there is a string 12 whose deviation value has suddenly deteriorated from the time series data of the deviation value (step S104). In this step S104, when a string 12 exhibiting deterioration such as a sudden drop is judged in the time series data of the deviation value, for example as shown by the thick line in Fig. 6, the control unit 30 registers the identification information of the string 12 in the abnormality list (step S105). In this case, when the control unit 30 judges in step S104 that multiple strings 12 exhibiting deterioration such as a sudden drop in the deviation value are judged, the control unit 30 registers the identification information of all of the multiple strings 12 in the abnormality list.

[0056] Then, if it is determined in step S104 that there is no string 12 exhibiting a deterioration such as a sudden drop in the deviation value, then after step S105, the control unit 30 selects the string 12 with the lowest deviation value from among the strings 12 exhibiting steadily low deviation values ​​in the time series data of the deviation values ​​for each of the strings 12 calculated in step S103 (step S106).

[0057] Next, the control unit 30 selects, from among all the strings 12 in the photovoltaic power plant 1, strings 12 whose deviation values ​​are constantly close to 50 and which are evaluated as normal (step S107).

[0058] Next, the control unit 30 performs a significant difference test between the power generation amount (the power generation amount corrected by the correction means 32) of the lowest string 12 having a constantly low deviation value selected in step S106 and the power generation amount (the power generation amount corrected by the correction means 32) of the normal string 12 selected in step S107 (step S111 in FIG. 8). Next, the control unit 30 determines whether or not there is a significant difference as a result of the significant difference test in step S111 (step S112).

[0059] Then, when it is determined in step S112 that there is a significant difference, the control unit 30 determines the lowest string 12 having a consistently low deviation value selected in step S106 and for which it has been determined that there is a significant difference, as an abnormal string, and registers its identification information in the abnormality list (step S113).

[0060] Next, the control unit 30 selects the string 12 with the next lowest deviation value (the next string 12) from among the strings 12 with a constantly low deviation value (step S114). Next, the control unit 30 returns the process to step S111 and performs a significant difference test between the power generation amount (the power generation amount corrected by the correction means 32) of the next string 12 with a constantly low deviation value selected in step S114 and the power generation amount (the power generation amount corrected by the correction means 32) of the normal string 12 selected in step S107. Then, when it is determined in step S112 that there is a significant difference, the control unit 30 repeats the processes of steps S113 and S114, and then returns the process to step S111 again.

[0061] If it is determined in step S112 that there is no significant difference, the control unit 30 determines that the next string 12, which constantly exhibits a low deviation value, is not abnormal, does not test for a significant difference in the amount of power generated between the string 12 with a larger deviation value than that and a normal string 12, and outputs an abnormality list in which the identification information of the abnormal string 12 is registered in steps S105 and S113 (step S115). In this example, the output of the abnormality list in step S115 is performed by displaying and / or notifying the determination result by voice (including voice message, alarm sound, etc.) based on the abnormality list, as described above, or by sending the abnormality list by email to a notification destination registered in advance.

[0062] 7 and 8, the normal string 12 used for the significant difference test in step S107 is selected from all the strings 12 in the photovoltaic power plant 1, but as described above, it may be selected from the array 13 including the string 12 that is the subject of the significant difference test and that exhibits a steadily low value. In that case, if the array including the string 12 with the next lowest standard deviation value selected in step S114 is different from the array to which the string 12 used in the previous significant difference test belongs, the normal string 12 to be used for the significant difference test is reselected.

[0063] [Other embodiments or modifications] In the above-described embodiment, the target for abnormality detection is each of the strings 12, but it may be each of the arrays 13. In that case, in the case of a photovoltaic power plant configuration in which a junction box 14 is provided as in the example of Fig. 2, as shown in Fig. 9, each junction box 14 is provided with a power generation detection and transmission device PDa that detects the amount of power generation obtained by combining (adding) the power generation outputs of the multiple strings 12 of the array 13 connected to the junction box 14. Based on the amount of power generation detected by this power generation detection and transmission device PDa, it becomes possible to perform abnormality diagnosis for each array 13 and / or each junction box 14.

[0064] In the example of Figure 9, a power generation detection / transmission device PDa is provided in each connection box 14, but instead of in the connection box 14, a configuration may be adopted in which multiple power generation detection / transmission devices PDa for each array 13 are provided in the PCS 15 at a portion that receives the power generation output from each connection box 14.

[0065] Also, similarly to the above, instead of providing the generated power detection / transmission device PDa, the generated power detection device and the transmission device may be provided separately.

[0066] In addition, in the case of a solar power plant configuration similar to the example of Figure 3, each power conditioner 17 is provided with a power generation detection and transmission device PDp that detects the power generation amount obtained by combining (adding) the power generation outputs of multiple strings of the array 13 connected to the power conditioner 17, as shown in Figure 10.

[0067] The amount of power generated detected by the power generation detection / transmission device PDp may be either DC or AC. When detecting and transmitting the amount of DC power generated, the power generation detection / transmission device PDp is provided on the input side of the power conditioner 17 to which the array 13 is connected, and when detecting and transmitting the amount of AC power generated, the power conditioner 17 is provided on the output side to which the current collection box 18 is connected. Based on the amount of power generated detected by this power generation detection / transmission device PDp, it becomes possible to diagnose abnormalities for each array 13 and / or each power conditioner 17.

[0068] When detecting and transmitting the amount of AC power generated for each array 13, the power generation detection / transmission device PDp may be provided in the current collection box 18 instead of the power conditioner 17.

[0069] In this case, each of the power generation detection and transmission device PDa in the example of Fig. 9 or the power generation detection and transmission device PDp in the example of Fig. 10 has a function of adding unique identification information to each and transmitting power generation data, similar to the power generation detection and transmission device PDs. Then, similar to the above-mentioned embodiment, the deviation value of the power generation amount in the array 13 unit is calculated, and similar to the above-mentioned example, a significant difference test is performed based on a sudden change in the deviation value and the power generation amount, and an abnormality judgment is performed in the array 13 unit. Note that the array 13 evaluated as normal to be used in the significant difference test in the array 13 unit in this example is selected from the whole.

[0070] In the example of Fig. 9, it is possible to diagnose an abnormality not only in the array 13 but also in the process of combining the power generation outputs of multiple strings of the array 13 in the junction box 14. Similarly, in the example of Fig. 10, it is possible to diagnose an abnormality in the process of combining the power generation outputs of multiple strings of the array 13 in the power conditioner 17 and converting the combined power generation output from DC to AC. However, in order to diagnose an abnormality in the DC to AC conversion function in the power conditioner 17, the power generation detection / transmission device PDp detects the power generation amount of the converted AC.

[0071] 9 and 10, the above-mentioned diagnostic method using only the deviation value of the array 13 unit cannot distinguish whether the abnormality is in the array 13 or in the junction box 14 or power conditioner 17. An example that solves this problem is shown in FIGS.

[0072] The example in Figure 11 is an improved example of the example in Figure 9, and is configured such that not only is a power generation detection / transmission device PDa provided in the connection box 14, but also a power generation detection / transmission device PDs is provided that detects and transmits the power generation amount of each of the multiple strings 12 in each array 13, as in the example in Figure 2.

[0073] In addition, the example of Figure 12 is an improved example of the example of Figure 10, and not only is a power generation detection and transmission device PDp provided for each power conditioner 17, but also a power generation detection and transmission device PDs is provided to detect and transmit the power generation amount of each of the multiple strings 12 in each array 13, as in the example of Figure 3.

[0074] According to the configuration example of Figure 11 or Figure 12, abnormalities can be detected at the array 13, connection box 14, or power conditioner 17 level by abnormality judgment using a deviation value of the power generation amount data detected by the power generation amount detection and transmission device PDa provided in the connection box 14 or the power generation amount detection and transmission device PDp provided in the power conditioner 17, and abnormalities can be detected at the array 13, connection box 14, or power conditioner 17 level by abnormality judgment using a deviation value of the power generation amount data detected by the power generation amount detection and transmission device PDs provided in each of the strings 12.

[0075] Therefore, when the array 13, the connection box 14, or the power conditioner 17 is judged to be abnormal by an abnormality judgment using a deviation value of the power generation data detected by the power generation detection / transmission device PDa or the power generation detection / transmission device PDp, if it is judged that there is no string judged to be abnormal among the strings 12 of the array 13 judged to be abnormal, it can be judged that the connection box 14 or the power conditioner 17 is abnormal.

[0076] 11, the power generation detection / transmission device PDa may be provided not in the junction box 14 but in a portion of the PCS 15 that receives the power generation output from each junction box 14. Also, as described above, the power generation detection / transmission device PDp may be provided not in the power conditioner 17 but in a portion of the current collection box 18 that receives the power generation output from each power conditioner 17 in the example of FIG.

[0077] [Effects of the embodiment] In the anomaly inspection method of the above embodiment, since the determination is not made directly from the power generation amount data for each string or array that is the target of the anomaly detection, but the deviation value of the power generation amount data for each string or array is used, a highly accurate anomaly detection capability can be obtained. That is, when the vertical axis is the power generation amount as shown in Fig. 4, the time series data of multiple strings or arrays overlap each other, making it difficult to determine an anomaly, but when the vertical axis is the deviation value as shown in Fig. 5, the differences between the time series data of multiple strings or arrays become prominent, making it easy to determine an anomaly.

[0078] In particular, when time-series data of the deviation value is used, a sudden drop (deterioration) of the deviation value can be determined as an abnormality in the object of the abnormality detection.

[0079] According to the anomaly inspection method of the above embodiment, the power generation amount data is corrected using a correction coefficient value based on factors caused by the installation condition of the anomaly detection target, so that the influence of the installation condition of the anomaly detection target can be eliminated, the accuracy of the anomaly judgment is improved, and the anomaly judgment can be performed automatically. Another advantage is that no new equipment such as a changeover switch is required.

[0080] Furthermore, in the anomaly inspection method of the above-described embodiment, an abnormality detection target with a low deviation value is not judged to be abnormal as is, but a significant difference test is performed to compare the power generation amount of the abnormality detection target judged to be abnormal with the power generation amount of a normal abnormality detection target, and then an abnormality judgment is made. Therefore, in this respect as well, the accuracy of the judgment is improved and automatic judgment is possible.

[0081] Furthermore, the anomaly inspection method of the above-described embodiment uses power generation data, which is basic data for a photovoltaic power plant and is the most easily obtainable data, and the power generation detection device and transmission device already installed in the photovoltaic power plant can use the data. This has the advantage that not only is a solar pyranometer and a thermometer unnecessary, but in some cases new equipment is not necessary.

[0082] [Other embodiments or modifications] In the anomaly inspection method of the above embodiment, a single photovoltaic power plant is assumed to be the facility to be inspected, and strings and arrays in the photovoltaic power generation system (photovoltaic power plant) are subject to anomaly detection. However, the present invention can also be applied to a case where anomaly inspection is performed on each of the photovoltaic power generation devices 6 installed in a plurality of dwelling units 5 existing within a predetermined area range AR as the facility to be inspected, as shown in Fig. 13, for example. In this case, the predetermined area range AR is set as the range of an area where natural environmental factors that affect photovoltaic power generation, such as weather and temperature, are approximately similar.

[0083] As shown in Fig. 13, in this example, the configuration of the photovoltaic power generation device 6 of each dwelling unit 5 can be, for example, the configurations shown in Fig. 2, 9, and 11. Note that the configuration of the photovoltaic power generation device 6 can also be the case where there is one array 13 in the configurations shown in Fig. 2, 9, and 11, and in that case, the function of the junction box 14 may be configured to be included in the power conditioner 17.

[0084] 13, the power generation amount data detected by the power generation amount detection and transmission devices PDs, PDa, PDp of the photovoltaic power generation device 6 in each dwelling unit 5 is added with the identification information assigned to each dwelling unit 5 in addition to the respective identification information. The power generation amount data detected by the power generation amount detection and transmission devices PDs, PDa, PDp may be sent directly from each of the power generation amount detection and transmission devices PDs, PDa, PDp to the remote monitoring server 2 via the network 4, but a transmission device may be separately provided in the photovoltaic power generation device 6 in each dwelling unit 5, and the transmission device may collect the power generation amount data from the power generation amount detection and transmission devices PDs, PDa, PDp using, for example, short-range wireless communication means or wired communication via a cable, and the collected power generation amount data may be transmitted collectively to the remote monitoring server 2.

[0085] The method of collectively transmitting the power generation amount data to the remote monitoring server 2 may be similarly used in the photovoltaic power plant 1 of the above-described embodiment.

[0086] 13, when installing the photovoltaic power generation device 6 in each dwelling unit 5, the worker performing the installation work collects installation status information for creating correction information based on the installation status, such as the number and capacity of modules (panels) for each string, panel azimuth angle, panel mounting angle, peak cut (output suppression), overload amount, and other special factors (partial shadow, panel surface dirt, etc.), and registers the collected installation status information in the abnormality inspection server 3. The abnormality inspection server 3 receives this installation status information as correction information.

[0087] In addition, in this example, the abnormality inspection server 3 detects the magnitude of the amount of power generation in the past under normal conditions for each dwelling unit 5 obtained from the remote monitoring server 2, and the difference in the detected magnitude of the amount of power generation is also used as correction information. This is because the magnitude of the amount of power generation in the normal conditions for each dwelling unit 5 corresponds to the above-mentioned installation status of the photovoltaic power generation device 6. Note that using the magnitude of the amount of power generation in the past under normal conditions as correction information is not limited to the example of Fig. 13, but is also possible in the examples of Figs. 2, 3, and 9 to 12 described above.

[0088] Then, the abnormality inspection server 3 uses the above-mentioned correction information to determine a correction coefficient value for each dwelling unit 5, and further for each string 12 and array 13, and stores them corresponding to the identification information of each dwelling unit 5 and the identification information of the abnormality inspection target, and uses them to correct the power generation amount data. That is, for example, when the correction coefficient value of the photovoltaic power generation device 6 of a dwelling unit 5 with a power generation amount of "100" is set to "1", the correction coefficient value of the photovoltaic power generation device 6 of a dwelling unit 5 with a power generation amount of "50", for example, is set to "2", and the correction coefficient value of the photovoltaic power generation device 6 of a dwelling unit 5 with a power generation amount of "200", for example, is set to "0.5", and correction is made so that the power generation amounts of the photovoltaic power generation devices 6 of the dwelling units 5 can be treated as being the same.

[0089] 13, the target of abnormality detection may be each photovoltaic power generation device 6. In that case, in the examples of Fig. 2, Fig. 9, and Fig. 11, a power generation amount detection and transmission device that detects the amount of power generated by the photovoltaic power generation device 6 and transmits the amount of power generated may be provided in the PCS 15 or the substation 16.

[0090] 13, an abnormality in the photovoltaic power generation device 6 of each dwelling unit 5 can be determined in the same manner as in the above-described embodiment, using the deviation value of the power generation amount data from the photovoltaic power generation device 6 of each dwelling unit 5. When the photovoltaic power generation device 6 of each dwelling unit 5 transmits power generation amount data for each string and / or array to the remote monitoring server 2, an abnormality in the photovoltaic power generation device 6 of each dwelling unit 5 can be determined for each string and / or array. In this case, in determining an abnormality for each string and / or array of the photovoltaic power generation device 6 of each dwelling unit 5, the group for calculating the deviation value may be multiple strings or multiple arrays in the photovoltaic power generation device 6 of the dwelling unit 5, or multiple strings or multiple arrays in the photovoltaic power generation devices 6 of all dwelling units 5 in a specified area range.

[0091] In the example of Fig. 13, since an abnormality determination can be automatically performed for each string or array for each dwelling unit 5 in which a photovoltaic power generation device 6 is installed within a predetermined area range AR, it is possible to provide appropriate and prompt after-sales service after the installation of the photovoltaic power generation device 6. In the example of Fig. 13, it is of course possible to include not only the dwelling unit 5 but also stores, facilities, factories, etc. equipped with photovoltaic power generation devices as the inspection targets.

[0092] In the above embodiment, the time series data of the deviation value is used to determine that a sudden change in the deviation value is an abnormality, but the power generation amount data of the abnormality detection target with a low deviation value does not need to be constantly low from the time series data, and the deviation value at a specific time point can be used. Therefore, even in a photovoltaic power generation system that does not constantly monitor the abnormality detection target as in the above embodiment, the present invention is also applicable to a one-off determination of whether the string, array, connection box, or power conditioner is abnormal when an abnormality occurs.

[0093] In the above-mentioned embodiment, the strings, arrays, junction boxes, and power conditioners are targeted for abnormality detection, but the photovoltaic power plant can also be targeted for abnormality detection. In that case, a system configuration is adopted in which a plurality of photovoltaic power plants are connected to the remote monitoring server 2 and the abnormality inspection server 3 via a network, and in each photovoltaic power plant, in the examples of Fig. 2, Fig. 9, and Fig. 11, a power generation amount detection and transmission device that detects and transmits the amount of power generated in the photovoltaic power plant 1 is provided in the PCS 15 or the substation 16, and in the examples of Fig. 3, Fig. 10, and Fig. 12, a power generation amount detection and transmission device that detects and transmits the amount of power generated in the photovoltaic power plant 1 is provided in the current collection box 18 or the substation 16. [Explanation of symbols]

[0094] 1...Photovoltaic power plant, 2...Remote monitoring server, 3...Anomaly inspection server, 4...Network, 11...Module, 12...String, 13...Array, 14...Connection box, 15, 17...Power conditioner, 16...Load, PDs, PDa, PDp...Power generation detection and transmission device

Claims

1. An abnormality inspection method for detecting an abnormality in equipment that generates power using solar cells, the method being performed by an abnormality inspection device that determines whether an abnormality detection target is abnormal based on power generation amount data of a plurality of abnormality detection targets, comprising: a correction step of correcting the power generation amount data based on factors caused by an installation condition of the abnormality detection target; a deviation value calculation step of calculating a deviation value of the power generation amount of each of the abnormality detection targets in a group consisting of a plurality of the abnormality detection targets based on the power generation amount data corrected in the correction step; a determination step of determining whether the abnormality detection target is abnormal based on the deviation value of each of the abnormality detection targets calculated in the deviation value calculation step; The abnormality inspection method includes the steps of:

2. The abnormality detection target is a string of solar panels connected in series.

2. The method for inspecting an abnormality according to claim 1.

3. The abnormality detection target is an array in which multiple strings of solar panels are connected in series.

2. The method for inspecting an abnormality according to claim 1.

4. A power generation amount detection device is provided for each power conditioner (PCS (Power Conditioning System)) that converts the generated DC voltage into AC voltage, to obtain the power generation amount data of the abnormality detection target.

2. The method for inspecting an abnormality according to claim 1.

5. The power generation amount data is time series data of power generation amount, The deviation value calculated in the deviation value calculation step and the deviation value used in the determination step are time series data of deviation values.

2. The method for inspecting an abnormality according to claim 1.

6. In the determination step, the abnormality detection target having a constantly low time series data of the deviation value is determined to be abnormal.

6. The method for inspecting an abnormality according to claim 5.

7. In the determination step, the abnormality detection target in which the time series data of the deviation value shows a sudden deterioration is determined to be abnormal.

6. The method for inspecting an abnormality according to claim 5.

8. a significant difference testing step for testing a significant difference between the power generation amount of the abnormality detection target determined to be abnormal in the determination step and the power generation amount of the abnormality detection target having the deviation value closest to 50, and determining that the abnormality detection target is abnormal if there is a significant difference 2. The method for inspecting an abnormality according to claim 1.

9. a significant difference testing step of testing a significant difference between the power generation amount of the abnormality detection target determined to be abnormal in the determination step and another abnormality detection target in a group to which the abnormality detection target determined to be abnormal belongs, the power generation amount of the other abnormality detection target having a deviation value closest to 50, and determining that the abnormality detection target is abnormal if there is a significant difference 2. The method for inspecting an abnormality according to claim 1.

10. An abnormality inspection method for detecting an abnormality in a photovoltaic power generation device installed in a dwelling unit within a specified area, the method being performed by an abnormality inspection device that determines whether the photovoltaic power generation device is abnormal based on power generation amount data from the photovoltaic power generation device, a correction step of correcting the power generation amount data based on factors related to an installation condition of the solar power generation device; a deviation value calculation step of calculating a deviation value of the power generation amount of each of the photovoltaic power generation devices in a group consisting of a plurality of the photovoltaic power generation devices within the predetermined area range based on the power generation amount data corrected in the correction step; a determination step of determining whether the abnormality detection target is abnormal based on the deviation value of each of the abnormality detection targets calculated in the deviation value calculation step; The abnormality inspection method includes the steps of:

11. a power generation amount detection device for obtaining the power generation amount data is provided for each string in which solar panels are connected in series and / or for each array in which a plurality of the strings are connected in the solar power generation device provided in the dwelling unit; In the deviation value calculation step, a deviation value of the amount of power generation of each of the strings and / or each of the arrays is calculated, In the determination step, the string and / or the array are determined to be abnormal based on the deviation value.

11. The method for inspecting an anomaly according to claim 10.

12. An abnormality inspection device for detecting an abnormality in equipment that generates electricity using solar cells, An acquisition means for acquiring power generation amount data of a plurality of abnormality detection targets; a correction means for correcting the power generation amount data acquired by the acquisition means based on factors due to an installation condition of the target for anomaly detection; a deviation value calculation means for calculating a deviation value of the amount of power generated by each of the abnormality detection targets in a group consisting of a plurality of the abnormality detection targets based on the power generation amount data corrected by the correction means; a determination means for determining whether the abnormality detection target is abnormal based on the deviation value of each of the abnormality detection targets calculated by the deviation value calculation means; An abnormality inspection device comprising:

13. and a significant difference testing means for testing a significant difference between the power generation amount of the abnormality detection object that has been determined to be abnormal by the determination means and the power generation amount of the abnormality detection object that has the closest deviation value to 50, and determining that the abnormality detection object is abnormal if there is a significant difference.

13. The abnormality inspection device according to claim 12.

14. The power generation amount data is time series data of power generation amount, The deviation value calculated by the deviation value calculation means and the deviation value used by the determination means are time series data of deviation values.

13. The abnormality inspection device according to claim 12.

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