Comprehensive diagnosis system for photovoltaic power generation facility using string selection and pattern analysis

Abstract

The present invention relates to a comprehensive diagnosis system for a photovoltaic power generation facility and, more specifically, to a comprehensive diagnosis system for a photovoltaic power generation facility using string selection and pattern analysis, which classifies strings according to device information of each string and a change pattern of an index affecting a failure, and detects a string showing a different change pattern of an index in the same classification as a string in which an abnormality related to the corresponding index has occurred, thereby enabling accurate identification of an abnormal state regardless of various conditions and environments of the string.

Description

A comprehensive diagnostic system for solar power plants through string screening and pattern analysis.

[0001] The present invention relates to a comprehensive diagnosis system for solar power generation facilities, and more particularly, to a comprehensive diagnosis system for solar power generation facilities through string selection and pattern analysis, which classifies strings according to device information of each string and a change pattern of an indicator that affects a failure, and detects a string that shows a different change pattern of an indicator in the same classification as a string in which an abnormality has occurred with respect to the indicator, thereby enabling accurate identification of an abnormal state regardless of various conditions and environments of the string.

[0002] Solar power, a renewable energy source, has seen a surge in demand recently due to its numerous advantages, and technologies to improve power generation efficiency have also been advancing rapidly. In particular, solar power generation systems are being installed in various forms, including rooftops, floating structures, and even building-integrated photovoltaic (BIPV) systems that are integrated into buildings.

[0003] These solar power generation devices have problems with their power generation efficiency declining due to various reasons such as shading, breakdown, and aging during the operation process. Recently, the importance of maintenance and repairs is increasing as much as the development of new solar power generation devices.

[0004] In order to efficiently maintain and repair solar power generation equipment, it is important to accurately understand the status of the solar power generation equipment. Conventionally, as in the patent document below, a method is used to diagnose the status by measuring each status of the solar power generation equipment and comparing it with a reference value, or predicting the power generation amount of the solar power generation equipment and comparing the current power generation amount with the predicted power generation amount.

[0005] However, since each solar power generation device has different specifications and characteristics, and the environment changes differently depending on the installation location, it is difficult to accurately set the standards for each device or accurately predict the amount of power generated, and thus the accuracy of status diagnosis using conventional methods is very low.

[0006] (Patent Document) Patent Publication No. 10-2292748 (registered on August 17, 2021) "Solar Power Generation and Control System, and Operating Method of Solar Power Generation and Control System"

[0007] The present invention has been devised to solve the above problems.

[0008] The purpose of the present invention is to provide a comprehensive diagnosis system for solar power generation facilities through string selection and pattern analysis, which classifies strings according to the device information of each string and the change pattern of an indicator that affects a failure, and detects a string that shows a different change pattern of an indicator in the same classification as a string in which an abnormality has occurred with respect to the indicator, thereby enabling accurate identification of an abnormal state regardless of various conditions and environments of the string.

[0009] The present invention aims to provide a comprehensive diagnosis system for solar power generation facilities through string selection and pattern analysis, which enables accurate detection of strings in which imbalance has occurred by calculating the degree of imbalance in the output of solar modules according to the degree of imbalance in the voltage between modules in a string and the degree of voltage fluctuation, and detecting strings in which imbalance has occurred using a change pattern in the state of output imbalance.

[0010] The purpose of the present invention is to provide a comprehensive diagnosis system for solar power generation facilities through string selection and pattern analysis, which enables detection of the cause of an imbalance state according to an imbalance index, thereby enabling a quick and accurate response to an imbalance state.

[0011] The purpose of the present invention is to provide a comprehensive diagnosis system for solar power generation facilities through string selection and pattern analysis, which enables classification and comparison of strings by analyzing a change pattern in the error between the predicted power generation amount and the measured power generation amount of a string, and enables more accurate detection of strings in which power generation amount has decreased by utilizing the area on the IV coordinate plane.

[0012] The purpose of the present invention is to provide a comprehensive diagnosis system for solar power generation facilities through string selection and pattern analysis that enables rapid response to failures by comparing the area of ​​each region on the IV coordinate plane for strings detected to have an abnormality due to a decrease in power generation and diagnosing the type of failure.

[0013] The present invention provides a comprehensive diagnosis system for solar power generation facilities through string selection and pattern analysis, which measures insulation resistance by applying voltage to a string for a certain period of time, calculates a change index indicating the degree of change in insulation resistance over a certain period of time or a kick index indicating the degree of rapid change per unit time, and detects a string in which insulation resistance deterioration has occurred by using the change index of insulation resistance or the change pattern of the kick index, thereby increasing the accuracy of detection.

[0014] In order to achieve the above-mentioned purpose, the present invention is implemented by an embodiment having the following configuration.

[0015] According to one embodiment of the present invention, a comprehensive diagnosis system for a solar power generation facility according to the present invention is characterized by including a string classification unit that classifies strings according to device information on strings of a solar power generation facility, a pattern analysis unit that analyzes a change pattern of indicators that affect a failure in each classification of strings, a pattern classification unit that classifies strings having similar change patterns of each indicator within strings of the same classification, and an abnormal string detection unit that compares change patterns of indicators between strings of the same classification and detects strings having different change patterns as abnormal.

[0016] According to another embodiment of the present invention, in the comprehensive diagnosis system for a solar power generation facility according to the present invention, the string classification unit is characterized by including a module specification collection module that collects specification information of a solar module included in a string, a module count collection module that collects information on the number of solar modules included in the string, a capacity information collection module that collects capacity information of an inverter connected to the string, and a string selection module that selects and classifies similar strings within a set range according to module specifications, module count, and inverter capacity.

[0017] According to another embodiment of the present invention, in the comprehensive diagnosis system for a solar power generation facility according to the present invention, the string classification unit includes an irradiance collection module that collects irradiance information for a string, and a module temperature collection module that collects temperature information of a solar module, and the string sorting module is characterized in that it classifies strings having irradiance and module temperature per unit period within a similar range into the same string group.

[0018] According to another embodiment of the present invention, in the comprehensive diagnosis system for a solar power generation facility according to the present invention, the pattern analysis unit includes an imbalance pattern analysis unit that analyzes a change pattern of the degree of imbalance of solar modules in a string, and the imbalance pattern analysis unit is characterized by including a voltage imbalance calculation unit that calculates the degree of imbalance for voltage between modules constituting the string, a fluctuation abnormality calculation unit that calculates the degree of abnormality according to voltage and current fluctuations of the string, an imbalance index calculation unit that calculates an imbalance index indicating the degree of imbalance between modules according to the degree of voltage imbalance and the degree of fluctuation abnormality, and an imbalance index analysis unit that analyzes a change pattern of the imbalance index.

[0019] According to another embodiment of the present invention, in the comprehensive diagnosis system for a solar power generation facility according to the present invention, the voltage imbalance calculation unit is characterized by including a string voltage measurement module that measures the voltage of power output from a string, a module voltage measurement module that measures the voltage of a specific module in the string, and a voltage imbalance coefficient calculation module that calculates a voltage imbalance coefficient indicating the degree of voltage imbalance between modules by subtracting a value obtained by multiplying the number of solar modules included in the string by the voltage of the specific module from the string voltage.

[0020] According to another embodiment of the present invention, in the comprehensive diagnosis system for a solar power generation facility according to the present invention, the voltage imbalance calculation unit is characterized in that it includes a coefficient correction module that corrects a voltage imbalance coefficient according to the amount of solar radiation and the module temperature.

[0021] According to another embodiment of the present invention, in the comprehensive diagnosis system for a solar power generation facility according to the present invention, the fluctuation abnormality calculation unit is characterized by including a voltage measurement module that measures a voltage output from a string for a certain period of time, a current measurement module that measures a current output from a string for a certain period of time, and a power fluctuation coefficient calculation module that calculates a value of a ratio of voltage change to current change for a ratio of voltage to current per unit time for a certain period of time and calculates a power fluctuation coefficient representing the degree of voltage and current fluctuation by the average value thereof.

[0022] According to another embodiment of the present invention, in the comprehensive diagnosis system for a solar power generation facility according to the present invention, the fluctuation abnormality calculation unit is characterized in that it includes a coefficient adjustment module that increases the scale while changing the standard for the normal state of the power fluctuation coefficient to 0.

[0023] According to another embodiment of the present invention, in the comprehensive diagnosis system for solar power generation facilities according to the present invention, the coefficient adjustment module is characterized in that it calculates the adjusted power variation coefficient by adjusting the power variation coefficient by mathematical expression 3. (Mathematical expression 3) Pf = (1-Pd)*10 (where, Pf is the adjusted power variation coefficient, and Pd is the initial power variation coefficient)

[0024] According to another embodiment of the present invention, in the comprehensive diagnosis system for a solar power generation facility according to the present invention, the imbalance index calculation unit is characterized by including a voltage imbalance coefficient loading module for loading a voltage imbalance coefficient, a power variation coefficient loading module for loading a power variation coefficient, and an imbalance index calculation module for calculating an imbalance index indicating the degree of imbalance in output between modules by multiplying the voltage imbalance coefficient and the power variation coefficient.

[0025] According to another embodiment of the present invention, a comprehensive diagnosis system for a solar power generation facility according to the present invention includes a module imbalance diagnosis unit that diagnoses the cause of the imbalance when the imbalance of a string is detected by comparing the change pattern of the imbalance index through the abnormal string detection unit, and the module imbalance diagnosis unit includes an imbalance index loading module that loads the imbalance index, and an abnormal information diagnosis module that diagnoses the cause of the imbalance according to the imbalance index, and the abnormal information diagnosis module is characterized in that when the imbalance index is positive, it diagnoses it as module damage, shading, or contamination, and when the imbalance index is negative, it diagnoses it as PID, cell crack, or insulation resistance reduction.

[0026] According to another embodiment of the present invention, in the comprehensive diagnosis system for a solar power generation facility according to the present invention, the pattern analysis unit includes a power generation pattern analysis unit that analyzes a change pattern with respect to an error between a predicted power generation amount and a measured power generation amount of a string, and the power generation pattern analysis unit includes a power generation prediction unit that predicts the power generation amount of each string of a solar power generation device, a power generation measurement unit that measures the current power generation amount of a string in real time, and an error analysis unit that analyzes a change pattern with respect to an error between the predicted and measured power generation amounts, and the error analysis unit is characterized in that it analyzes a change pattern with respect to an area by region on an IV coordinate plane according to the predicted power generation amount and the measured power generation amount.

[0027] According to another embodiment of the present invention, in the comprehensive diagnosis system for solar power generation facilities according to the present invention, the error analysis unit is characterized in that it includes an Isc area calculation module that calculates the area of ​​an Isc area formed by a line connecting points on an IV coordinate plane according to voltage and current values ​​of predicted and measured power generation and a line connecting points indicating short-circuit current, a Voc area calculation module that calculates the area of ​​a Voc area formed by a line connecting points on an IV coordinate plane according to voltage and current values ​​of predicted and measured power generation and a line connecting points indicating open-circuit voltage, and a change pattern analysis module that analyzes a change pattern of the area of ​​the Isc area or the area of ​​the Voc area.

[0028] According to another embodiment of the present invention, a comprehensive diagnosis system for a solar power generation facility according to the present invention includes a power generation diagnosis unit that diagnoses an abnormal cause for a decrease in power generation when a change pattern of an area of ​​an Isc area or an area of ​​a Voc area is different and is detected as an abnormal string, and the power generation diagnosis unit is characterized by including an area-area loading module that loads information on the areas of the Isc area and the Voc area, an area-area comparison module that compares the loaded areas of the Isc area and the Voc area, and a decrease cause detection module that detects a cause for a decrease in power generation based on a result of the comparison of areas.

[0029] According to another embodiment of the present invention, in the comprehensive diagnosis system for a solar power generation facility according to the present invention, the degradation cause detection module is characterized in that, if the area of ​​the Isc region is larger than the area of ​​the Voc region, it determines that there is an abnormality due to an increase in the series resistance, and if the area of ​​the Voc region is larger than the area of ​​the Isc region, it determines that there is an abnormality due to a decrease in the module parallel resistance.

[0030] According to another embodiment of the present invention, in the comprehensive diagnosis system for a solar power generation facility according to the present invention, the pattern analysis unit includes an insulation resistance pattern analysis unit that analyzes a change pattern of an index related to insulation resistance of a string, and the insulation resistance pattern analysis unit includes a change pattern analysis unit that analyzes a change pattern for a degree of insulation resistance change over a set period of time, and the change pattern analysis unit is characterized by including a first insulation resistance measurement module that measures insulation resistance after an initial period of time has elapsed, a second insulation resistance measurement module that measures insulation resistance after a set period of time has elapsed from the initial period of time, a change index calculation module that calculates a change index indicating a degree of change in insulation resistance according to a ratio of the second insulation resistance to the first insulation resistance, and an index pattern analysis module that analyzes a change pattern of the calculated change index.

[0031] According to another embodiment of the present invention, in the comprehensive diagnosis system for a solar power generation facility according to the present invention, the pattern analysis unit includes an insulation resistance pattern analysis unit that analyzes a change pattern of an index related to insulation resistance of a string, and the insulation resistance pattern analysis unit includes a kick index analysis unit that analyzes a change pattern of a kick index indicating a degree of rapid change in insulation resistance per unit time during a set period of time, and the kick index analysis unit is characterized in that it includes a voltage application module that applies voltage to the string for a certain period of time, an insulation resistance measurement module that measures insulation resistance at unit time intervals according to the voltage application, a kick index calculation module that calculates a kick index indicating a degree of change in insulation resistance per unit time during a certain period of time, and a kick index change analysis module that analyzes a change pattern of the calculated kick index.

[0032] According to another embodiment of the present invention, in the comprehensive diagnosis system for a solar power generation facility according to the present invention, the kick index calculation module is characterized in that it calculates the time kick index by the following mathematical expression 4.

[0033] (Equation 4)

[0034]

[0035] According to another embodiment of the present invention, in the comprehensive diagnosis system for a solar power generation facility according to the present invention, the kick index analysis unit is characterized by including a voltage adjustment module that allows measurement of insulation resistance while changing the voltage in steps.

[0036] According to another embodiment of the present invention, in the comprehensive diagnosis system for a solar power generation facility according to the present invention, the kick index calculation module is characterized in that it calculates the voltage kick index by the following mathematical expression 5.

[0037] (Equation 5)

[0038]

[0039] The present invention can obtain the following effects through the combination and use of the configuration described below with the previously described embodiment.

[0040] The present invention classifies strings according to the device information of each string and the change pattern of an indicator that affects a failure, and detects a string that shows a different change pattern of an indicator in the same classification as a string in which an abnormality has occurred with respect to the indicator, thereby enabling accurate identification of an abnormal state regardless of various conditions or environments of the string.

[0041] The present invention calculates the degree of imbalance in the output of a solar module based on the degree of imbalance in the voltage between modules in a string and the degree of voltage fluctuation, and detects a string in which an imbalance has occurred using a change pattern in the state of output imbalance, thereby enabling accurate detection of a string in which an imbalance has occurred.

[0042] The present invention has the effect of enabling the cause of an imbalance state to be detected according to an imbalance index, thereby enabling a response to an imbalance state to be made quickly and accurately.

[0043] The present invention has the effect of enabling more accurate detection of strings in which power generation has decreased by utilizing the area on the IV coordinate plane while enabling classification and comparison of strings by analyzing the change pattern of the error between the predicted power generation amount and the measured power generation amount of the string.

[0044] The present invention has the effect of enabling a rapid response to a fault by comparing the area of ​​each region on the IV coordinate plane for a string detected to have an abnormality due to a decrease in power generation and diagnosing the type of fault.

[0045] The present invention measures insulation resistance by applying voltage to a string for a certain period of time, calculates a change index indicating the degree of change in insulation resistance over a certain period of time or a kick index indicating the degree of rapid change per unit time, and detects a string in which insulation resistance has deteriorated by using the change index of insulation resistance or the change pattern of the kick index, thereby having the effect of increasing the accuracy of detection.

[0046] Figure 1 is a block diagram showing the configuration of a comprehensive diagnosis system for solar power generation facilities through string selection and pattern analysis according to one embodiment of the present invention.

[0047] Figure 2 is a block diagram showing the configuration of the string classification unit.

[0048] Figure 3 is a block diagram showing the configuration of the pattern analysis unit.

[0049] Figure 4 is a block diagram showing the configuration of the imbalance pattern analysis unit.

[0050] Figure 5 is a block diagram showing the configuration of the voltage imbalance calculation unit.

[0051] Figure 6 is a reference diagram showing an example of voltage measurement by a voltage imbalance calculation unit.

[0052] Figure 7 is a block diagram showing the configuration of the variable abnormality calculation system.

[0053] Figure 8 is a graph showing an example of voltage change according to string status.

[0054] Figure 9 is a block diagram showing the configuration of the imbalance index calculation unit.

[0055] Figure 10 is a block diagram showing the configuration of the power generation pattern analysis unit.

[0056] Figure 11 is a block diagram showing the configuration of the power generation prediction unit.

[0057] Figure 12 is a block diagram showing the configuration of the error analysis unit.

[0058] Figure 13 is a block diagram showing the configuration of the insulation resistance pattern analysis unit.

[0059] Figure 14 is a graph showing an example of a change index.

[0060] Figure 15 is a graph showing an example of insulation resistance measurement by the kick index analysis unit.

[0061] Figure 16 is a block diagram showing the configuration of the module imbalance diagnosis unit.

[0062] Figure 17 is a reference diagram showing the operating point on the IV curve according to the imbalance index.

[0063] Figure 18 is a block diagram showing the configuration of the power generation diagnostic unit.

[0064] Figure 19 is a reference diagram showing the IV graph used by the power generation diagnostic unit.

[0065] *Explanation of symbols used in drawings

[0066] 1: String classification section 2: Pattern analysis section

[0067] 21: Unbalance Pattern Analysis Section 211: Voltage Unbalance Calculation Section

[0068] 212: Fluctuation and Anomaly Calculation Section 213: Imbalance Index Calculation Section

[0069] 214: Imbalance Index Analysis Department 22: Power Generation Pattern Analysis Department

[0070] 221: Power generation prediction unit 222: Power generation measurement unit

[0071] 223: Error Analysis Department 23: Insulation Resistance Pattern Analysis Department

[0072] 231: Change Pattern Analysis Department 232: Kick Index Analysis Department

[0073] 3: Pattern classification section 4: Abnormal string detection section

[0074] 5: Module imbalance diagnosis section 6: Power generation diagnosis section

[0075] Hereinafter, preferred embodiments of a comprehensive diagnosis system for solar power generation facilities through string selection and pattern analysis according to the present invention will be described in detail with reference to the attached drawings. In the following description of the present invention, if it is determined that a detailed description of a known function or configuration may unnecessarily obscure the gist of the present invention, the detailed description will be omitted. Throughout the specification, when a part is said to "include" a certain component, this does not mean that other components are excluded, but that other components can be further included, unless specifically stated to the contrary. In addition, terms such as "... part", "... module" described in the specification mean a unit that processes at least one function or operation, and this can be implemented by hardware, software, or a combination of hardware and software.

[0076] Hereinafter, a comprehensive diagnosis system for a solar power generation facility through string selection and pattern analysis according to an embodiment of the present invention will be described with reference to FIGS. 1 to 19. The comprehensive diagnosis system for a solar power generation facility includes a string classification unit (1) that classifies strings according to device information on strings of a solar power generation facility, a pattern analysis unit (2) that analyzes a change pattern of indicators that affect a failure in each classification of strings, a pattern classification unit (3) that classifies strings having similar change patterns of each indicator within strings of the same classification, an abnormal string detection unit (4) that compares change patterns of indicators between strings of the same classification to detect strings with different change patterns as abnormal, a module imbalance diagnosis unit (5) that diagnoses the cause of the imbalance when imbalance of a string is detected by comparing change patterns of an imbalance index through the abnormal string detection unit, and a power generation diagnosis unit (6) that diagnoses the cause of an abnormality due to a decrease in power generation.

[0077] The present invention relates to a system for diagnosing abnormal conditions in solar power generation, more precisely, abnormal conditions in strings, and detects abnormal strings by utilizing change patterns of indicators that affect failures in solar power generation facilities. Conventionally, failures in solar power generation facilities have been diagnosed by simply comparing indicators that affect failures with established reference values. However, there has been a problem that accurate abnormality detection is difficult due to the characteristics of indicators that change according to various environments, specifications, and conditions. Therefore, the present system classifies similar strings into the same string group based on not only basic device information of the strings but also change patterns of each indicator, and detects strings in which abnormalities have occurred by comparing change patterns within the classified string group, thereby increasing the accuracy of abnormality detection. In particular, this system enables accurate diagnosis of each abnormal condition by using unique indicators that indicate an imbalance condition between modules within a string, a state of reduced power generation, and a state of reduced insulation resistance, thereby enabling classification and pattern analysis of strings. In addition, it enables diagnosis of the cause of the imbalance condition and the state of reduced power generation, thereby enabling a quick and accurate response to the abnormal condition.

[0078] The above solar power generation facility real-time monitoring system can enable remote monitoring of multiple solar power generation facilities, and can enable monitoring by remotely receiving voltage, current, insulation resistance, etc. measured through a connection box, etc.

[0079] The above string classification unit (1) is configured to classify strings according to their characteristics, and classifies strings with similar basic device information and status information into the same string group. The above string classification unit (1) may include a module specification collection module (11), a module quantity collection module (12), an irradiance collection module (13), a module temperature collection module (14), an inverter capacity collection module (15), and a string selection module (16).

[0080] The above module specification collection module (11) is configured to collect specification information of solar modules included in a string, and can collect and store information such as manufacturer and item in advance.

[0081] The above module count collection module (12) is configured to collect information on the number of solar modules included in a string, and can collect and store information on the number of solar modules connected in series in advance.

[0082] The above-mentioned irradiance collection module (13) is configured to collect irradiance information for a string, and can be measured and stored through a separate sensor.

[0083] The above module temperature collection module (14) is configured to collect temperature information of a solar module, and can receive and store information from a separate sensor that measures module temperature.

[0084] The above inverter capacity collection module (15) is configured to collect information on the capacity of the inverter to which the string is connected, and collects and stores in advance the information on the inverter to which the string of each solar power generation facility is connected.

[0085] The above string sorting module (16) is configured to sort strings with similar conditions and classify them into the same string group. First, similar strings within a certain range are classified according to the specifications of the solar module, the number of modules, and the inverter capacity. In addition, the string sorting module (16) can classify strings with similar ranges of irradiance and module temperature per unit period into the same string group. For example, strings with similar daily average irradiance and module temperature within a certain range can be classified into the same string group.

[0086] The above pattern analysis unit (2) is configured to analyze a change pattern of an indicator that affects a failure of a string, and can analyze a change pattern regarding the degree of imbalance between modules within a string, a change pattern regarding the degree of reduction in power generation, and a change pattern regarding the degree of change in insulation resistance. To this end, the pattern analysis unit (2) may include an imbalance pattern analysis unit (21), a power generation pattern analysis unit (22), and an insulation resistance pattern analysis unit (23).

[0087] The above-mentioned imbalance pattern analysis unit (21) is configured to analyze a change pattern regarding the degree of imbalance of solar modules within a string, and analyzes a comprehensive change pattern of the degree of imbalance that comprehensively considers the degree of imbalance of voltage between modules and the degree of voltage fluctuation of the string. To this end, the above-mentioned imbalance pattern analysis unit (211) may include a voltage imbalance calculation unit (211), a fluctuation abnormality calculation unit (212), an imbalance index calculation unit (213), and an imbalance index analysis unit (214).

[0088] The voltage imbalance calculation unit (211) above is configured to calculate the degree of voltage imbalance between solar modules in a string, and in particular, uses the voltage output from the string and the voltage measured from a specific module in the string. Conventionally, in order to detect voltage imbalance between modules in a string, the voltage of each module had to be measured and compared, but in this case, there was a problem that installation and maintenance costs increased. Therefore, the voltage imbalance calculation unit (211) calculates the degree of voltage imbalance by comparing the voltage of the string and the voltage of a specific module multiplied by the number of modules, thereby simplifying installation and maintenance and reducing cost and time. In other words, if there is no imbalance between solar modules, the voltage of the string will be equal to the voltage of a specific module multiplied by the number of modules, and thus the degree of voltage imbalance can be calculated based on the difference. In addition, since the degree of voltage imbalance changes depending on the amount of solar radiation and the module temperature, the degree of voltage imbalance is calculated by reflecting this. To this end, the voltage imbalance calculation unit (211) may include a string voltage measurement module (211a), a module voltage measurement module (211b), a voltage imbalance coefficient calculation module (211c), and a coefficient correction module (211d).

[0089] The above string voltage measurement module (211a) is configured to measure the voltage output from the string, and can measure the voltage at the output terminal of the string as shown in Fig. 6.

[0090] The above module voltage measurement module (211b) is configured to measure the voltage of a specific module within a string, and measures the voltage of only one of a number of solar modules included in the string. For example, it can measure the voltage of the module at the final stage.

[0091] The above voltage imbalance coefficient calculation module (211c) is configured to calculate a voltage imbalance coefficient that indicates the degree of voltage imbalance of modules within a string, and can calculate the voltage imbalance coefficient by subtracting a value obtained by multiplying the voltage of a specific module by the number of modules from the string voltage. Accordingly, the greater the degree of voltage imbalance between modules within a string, the greater the voltage imbalance coefficient.

[0092] The above coefficient correction module (211d) is configured to correct the voltage imbalance coefficient according to standard conditions based on solar irradiance and module temperature, and the correction can be performed according to the following (Mathematical Formula 1). Accordingly, the voltage imbalance coefficient can be calculated according to the same standard for the strings.

[0093] (Equation 1)

[0094]

[0095] (Here, the module temperature coefficient is different for each module and is generally 0.4% / 1 degree)

[0096] The above fluctuation abnormality calculation unit (212) is configured to calculate the abnormality of the voltage fluctuation of the string, and reflects the voltage fluctuation degree in the calculation of the degree of imbalance by expressing the degree of voltage fluctuation in a numerical value. As shown in FIG. 8, in the case of a normal state, the string continues to fluctuate in a certain range of voltage as in ① and tracks the maximum power point. However, in the case where the voltage fluctuation range is too large or too small outside a certain range as in ② and ③, it is determined to be an abnormal state of fluctuation and the degree thereof is calculated. In addition, the fluctuation abnormality calculation unit (212) adjusts the scale and reference value to calculate the degree of imbalance by linking the abnormality of the voltage fluctuation with the voltage imbalance coefficient. To this end, the fluctuation abnormality calculation unit (212) may include a voltage measurement module (212a), a current measurement module (212b), a power fluctuation coefficient calculation module (212c), and a coefficient adjustment module (212d).

[0097] The above voltage measurement module (212a) is configured to measure the voltage output from the string, and calculates the degree of change per unit time by measuring for a certain period of time.

[0098] The above current measurement module (212b) is configured to measure the current output from the string, and measures it for a certain period of time like voltage to calculate the degree of change with the voltage.

[0099] The above power variation coefficient calculation module (212c) is configured to calculate the power variation coefficient that indicates the degree of voltage and current variation, and calculates the degree of voltage and current variation per unit time. For example, the above power variation coefficient calculation module (212c) can calculate the power variation coefficient as the value obtained by dividing the change range ratio of voltage and current by the size ratio of voltage and current, as shown in the following (Mathematical Expression 2). If there is no imbalance between modules, the power variation coefficient will have a value close to 1, and if the voltage variation range is large, it will have a value less than 1, and if the voltage variation range is small, it will have a value greater than 1.

[0100] (Equation 2)

[0101]

[0102] (I, V = current, voltage / dI, dV = fluctuations in current, voltage)

[0103] At this time, a large voltage change range means that a specific module has deteriorated or the power generation has decreased due to negative radiation, contamination, etc., and it means a state in which the voltage is changed greatly as in ② of Fig. 8 in order to find the maximum power point by the MPPT algorithm of the inverter. In addition, a small voltage change range and a power variation coefficient greater than 1 means a state in which the power generation performance of the module has significantly decreased as in ③ of Fig. 8 in which the voltage variation amount is almost non-existent compared to the current variation amount. The power variation coefficient calculation module (212c) may be configured to calculate the power variation coefficient per unit time, for example, 5 seconds or 10 seconds, and may be configured to determine the final power variation coefficient as the average value of the power variation coefficient per unit time for a certain period of time.

[0104] The above coefficient adjustment module (212d) is configured to adjust the final power variation coefficient calculated by the power variation coefficient calculation module (212c) to link it with the voltage imbalance coefficient, and can calculate the adjusted power variation coefficient by converting the standard of the normal state from 1 to 0 and increasing the scale, as shown below (Mathematical Formula 3).

[0105] (Equation 3)

[0106] Pf = (1-Pd)*10

[0107] (Here, Pf is the adjusted power variation coefficient, and Pd is the final power variation coefficient)

[0108] Therefore, in a normal state where there is no imbalance between modules, the adjusted power variation coefficient becomes 0, a power variation coefficient less than 1 is converted to a positive number, and a power variation coefficient greater than 1 is converted to a negative number.

[0109] The above-described imbalance index calculation unit (213) is configured to calculate an imbalance index indicating the degree of output imbalance of modules within a string, and calculates the degree of imbalance between modules by reflecting the degree of voltage imbalance calculated by the voltage imbalance calculation unit (211) and the degree of voltage fluctuation abnormality calculated by the fluctuation abnormality calculation unit (212). To this end, the imbalance index calculation unit (213) may include a voltage imbalance coefficient loading module (213a), a power fluctuation coefficient loading module (213b), and an imbalance index calculation module (213c).

[0110] The above voltage imbalance coefficient loading module (213a) is configured to load the voltage imbalance coefficient calculated by the voltage imbalance calculation unit (211), and loads the voltage imbalance coefficient calculated by the voltage imbalance coefficient calculation module (211c).

[0111] The above power variation coefficient loading module (213b) is configured to load the power variation coefficient calculated by the variation anomaly calculation unit (212), and loads the power variation coefficient adjusted by the coefficient adjustment module (212d).

[0112] The above-mentioned imbalance index calculation module (213c) is configured to calculate an imbalance index indicating the degree of imbalance between modules, and can calculate the imbalance index by multiplying a voltage imbalance coefficient and a power variation coefficient.

[0113] The above imbalance index analysis unit (214) is configured to analyze the change pattern of the imbalance index, and can analyze and store the change flow of the imbalance index calculated at regular intervals.

[0114] The above power generation pattern analysis unit (22) is configured to analyze the change pattern regarding the error between the predicted power generation and the measured power generation of the string, and analyzes the change pattern of the area of ​​each region on the IV coordinate plane according to the predicted power generation and the measured power generation. The area on the IV coordinate according to the difference between the predicted power generation and the measured power generation means a different state for each region, and by analyzing the change pattern of the area of ​​each region, an abnormal state due to a decrease in power generation can be accurately detected. The above power generation pattern analysis unit (22) may include a power generation prediction unit (221), a power generation measurement unit (222), and an error analysis unit (223).

[0115] The above power generation prediction unit (221) is configured to predict the power generation of a solar power generation facility, and can predict the power generation for each string. In particular, the power generation prediction unit (221) can increase the accuracy by predicting the power generation by reflecting the specifications and characteristics of each solar module, IV curve data, environmental information, and deterioration rate. To this end, the power generation prediction unit (221) may include a specification information collection module (221a), a number of information collection module (221b), a power generation information collection module (221c), an environmental information collection module (221d), an irradiance information collection module (221e), a temperature information collection module (221f), a deterioration rate calculation module (221g), and a predicted power generation generation module (221h).

[0116] The above specification information collection module (221a) is configured to collect specification information of solar modules included in a string, and can collect and store manufacturer and product information in advance.

[0117] The above-mentioned number information collection module (221b) is configured to collect information on the number of solar modules included in a string, and can generate prediction information by adding the predicted power generation information for each solar module according to the number of solar modules.

[0118] The above power generation information collection module (221c) is configured to collect information on the number of days of power generation of a solar power module, and can calculate and collect information on the number of days of power generation by accumulating and storing information on power generation from the time of installation.

[0119] The above environmental information collection module (221d) is configured to collect environmental information around the solar module, and can collect information on temperature, humidity, etc.

[0120] The above-mentioned solar irradiance information collection module (221e) is configured to collect solar irradiance information reaching a solar module, and can predict power generation using IV curve data according to the collected solar irradiance.

[0121] The above temperature information collection module (221f) is configured to collect module temperature information of a solar module, and can collect temperature information measured by a sensor installed in each solar module.

[0122] The above deterioration rate calculation module (221g) is configured to calculate the deterioration rate that indicates the degree of deterioration of a solar module, and calculates the deterioration rate based on the number of days of power generation collected by the power generation information collection module (221c) by reflecting the degree of deterioration by day determined by the characteristics of each specification of the solar module.

[0123] The above predicted power generation module (221h) is configured to predict the power generation of a string, and predicts the power generation by considering IV curve data according to solar irradiance and module temperature, environmental information, and deterioration rate. The prediction of the power generation according to the IV curve data and environmental information can be made experimentally or by analyzing measurement information collected from a solar power generation facility. For example, the correlation can be derived by learning by reflecting environmental information and deterioration rate in the power generation according to the IV curve data provided by the manufacturer of each solar module, and the power generation can be predicted using the derived correlation.

[0124] The above power generation measuring unit (222) is configured to measure the power generation of each string, and can calculate the power generation by measuring the voltage and current output from each string.

[0125] The above error analysis unit (223) is configured to analyze the change pattern regarding the error of the predicted and measured power generation, and in particular, to analyze the change pattern of the area of ​​the region connecting the location on the IV coordinate plane according to the power generation and the point indicating the short-circuit current and open-circuit voltage. Since each region according to the error of the power generation connecting the short-circuit current and open-circuit voltage shows a different area depending on the cause of the decrease in the power generation, the change in the area of ​​each region can be analyzed to enable accurate detection of an abnormal state. To this end, the error analysis unit (223) may include an Isc region calculation module (223a), a Voc region calculation module (223b), and a change pattern analysis module (223c).

[0126] The above Isc area calculation module (223a) is configured to calculate the area of ​​the Isc area formed by the point on the IV coordinate plane where the predicted power generation and measured power generation are indicated and the point (Isc) indicating the short-circuit current, and calculates the area ∆a in the graph shown in Fig. 19. The area ∆a is the area generated according to the difference between the predicted power generation and measured power generation, and a large area of ​​∆a means a decrease in current, i.e., an increase in the series resistance on the string.

[0127] The above Voc area calculation module (223b) is configured to calculate the area of ​​the Voc area formed by the point on the IV coordinate plane indicated by the predicted power generation and the measured power generation and the point (Voc) indicating the open circuit voltage, and calculates the area of ​​∆b in the graph illustrated in Fig. 19. The area of ​​∆b is also an area generated according to the difference between the predicted power generation and the measured power generation, and a large area of ​​∆b means a decrease in voltage, i.e., a decrease in parallel resistance in the string.

[0128] The above change pattern analysis module (223c) is configured to analyze the change pattern for the error of the predicted power generation amount and the measured power generation amount, and analyzes the change pattern for each area of ​​the Isc area (∆a) and the Voc area (∆b).

[0129] The above insulation resistance pattern analysis unit (23) is configured to analyze the change pattern of the indicator related to the insulation resistance of the string, and analyzes the change pattern of the degree of change in the insulation resistance measured over a set period of time. The decrease in the insulation resistance of solar power generation facilities is a major cause of fire, and is periodically checked, but in the past, it was done by comparing the measured insulation resistance with a reference value. Therefore, there was a problem that the change in insulation resistance due to environmental changes could not be reflected, and local defects and micro-deterioration of the insulation resistance could not be detected. Therefore, the insulation resistance pattern analysis unit (23) analyzes the change pattern of the insulation resistance, and in particular, rather than simply analyzing the change pattern of the insulation resistance value, it analyzes the change pattern of the indicator indicating the degree of change in the insulation resistance, thereby increasing the accuracy of the diagnosis. The above insulation resistance pattern analysis unit (23) can analyze the degree of change in insulation resistance over a certain period of time or the change pattern of a phenomenon of rapid increase, and for this purpose, can include a change pattern analysis unit (231) and a kick index analysis unit (232).

[0130] The above change pattern analysis unit (231) is configured to analyze the change pattern for the degree of change in insulation resistance over a set period of time, and analyzes the change pattern for the degree of change in insulation resistance after a set period of time has elapsed compared to the initial period of time after voltage is applied. Normally, the insulation resistance remains constant for the set period of time when voltage is applied, but if it increases or decreases, it means that an abnormality has occurred in the insulation resistance. Therefore, the change pattern analysis unit (231) can recognize that an abnormality has occurred in the insulation resistance by comparing the pattern in which the degree of change in insulation resistance, i.e., the degree of occurrence of an abnormality, is changed for strings in the same string group. To this end, the change pattern analysis unit (231) may include a first insulation resistance measurement module (231a), a second insulation resistance measurement module (231b), a change index calculation module (231c), and an index pattern analysis module (231d).

[0131] The above first insulation resistance measurement module (231a) is configured to measure the insulation resistance after a certain initial period of time has elapsed after voltage is applied. For example, when measuring the insulation resistance for 10 minutes, the insulation resistance can be measured after the initial lapse of 1 minute.

[0132] The above second insulation resistance measurement module (231b) is configured to measure insulation resistance after a set period of time has elapsed. For example, when measuring insulation resistance for 10 minutes, the insulation resistance can be measured after 10 minutes have elapsed.

[0133] The above change index calculation module (231c) is configured to calculate a change index indicating the degree of change in insulation resistance over a set period of time, and can calculate the change index according to the ratio of the second insulation resistance to the first insulation resistance. At this time, if the change index is 1 as in (1) of Fig. 14, it indicates a normal state in which there is no change in insulation resistance, and if it is less than 1 as in (2), the insulation resistance gradually decreases, indicating the degree of insulation deterioration due to cable moisture absorption and contamination, and if it is greater than 1 as in (3), the insulation resistance gradually increases, so corrosion, etc. due to cable drying can be suspected.

[0134] The above index pattern analysis module (231d) is configured to analyze the change pattern of the change index. Since the change index indicates the degree of abnormality in insulation resistance, it analyzes and compares the change pattern of insulation resistance between groups of identical strings, thereby enabling detection of strings having abnormal change patterns.

[0135] The kick index analysis unit (232) above is configured to analyze the kick index, which indicates the degree of rapid change in insulation resistance, and calculates the degree of rapid change per unit time for a certain period of time as the kick index, so that the change pattern can be analyzed. When an abnormality in the insulation resistance occurs, the insulation resistance not only changes within a set time like the change index, but also the rapid change is frequently repeated. Therefore, the kick index analysis unit (232) calculates the degree of rapid change as the kick index and compares the change pattern, thereby enabling more accurate abnormality detection regardless of the surrounding environmental conditions. To this end, the kick index analysis unit (232) may include a voltage application module (232a), a voltage adjustment module (232b), an insulation resistance measurement module (232c), a kick index calculation module (232d), and a kick index change analysis module (232e).

[0136] The above voltage application module (232a) is configured to apply voltage to a string to measure insulation resistance, and can apply voltage for a certain period of time, for example, 10 minutes.

[0137] The voltage regulation module (232b) is configured to regulate the voltage applied by the voltage application module (232a), and can measure changes in insulation resistance in various voltage situations by increasing the voltage in steps. For example, the voltage regulation module (232b) can increase the voltage in steps from 100 V to 500 V.

[0138] The above insulation resistance measurement module (232c) is configured to measure insulation resistance for a certain period of time while voltage is applied. For example, when voltage is applied for 10 minutes, insulation resistance can be measured every second. In addition, when insulation resistance is measured while increasing voltage in stages by the voltage adjustment module (232b), insulation resistance can be measured every time the voltage is increased.

[0139] The kick index calculation module (232d) above is configured to calculate a kick index indicating the degree of rapid change in insulation resistance, and if the insulation resistance measured in units of time or voltage by the insulation resistance measurement module (232c) does not change linearly but has a large change range or rapid change as shown in FIG. 15, it can be determined that the insulation resistance has decreased. Accordingly, the kick index calculation module (232d) can calculate the degree to which the insulation resistance changes on average as a kick index, and can calculate a time kick index regarding the degree of change per unit time when a constant voltage is applied for a certain period of time, and a voltage kick index regarding the degree of change each time the voltage is changed when the voltage is applied while being adjusted in steps for a certain period of time. At this time, the time kick index can be calculated by the following (Mathematical Formula 4), and the voltage kick index can be calculated by the following (Mathematical Formula 5).

[0140] (Equation 4)

[0141]

[0142] (Equation 5)

[0143]

[0144] The above kick index change analysis module (232e) is configured to analyze the change pattern of the kick index, and can analyze the change pattern of the time kick index or the voltage kick index.

[0145] The above pattern classification unit (3) is configured to classify strings according to the change pattern of an index that affects the failure of a string, and classifies strings according to the change pattern of the imbalance index, the area of ​​the Isc region (∆a) and the Voc region (∆b), the time kick index, and the voltage kick index analyzed by the imbalance pattern analysis unit (21), the power generation pattern analysis unit (22), and the insulation resistance pattern analysis unit (23). Accordingly, the pattern classification unit (3) classifies strings having similar patterns of each index within the string group primarily classified by the string classification unit (1) into a string group for each index, and analyzes the change pattern for each index within the same classification to detect abnormal strings. For example, the pattern classification unit (3) may use an algorithm that classifies according to a change pattern.

[0146] The above-described abnormal string detection unit (4) is configured to detect a string in which an abnormality has occurred through pattern analysis by the pattern analysis unit (2), and can detect a string in which an imbalance between modules, a decrease in power generation, or a decrease in insulation resistance has occurred. Accordingly, the above-described abnormal string detection unit (4) can compare the change pattern of the imbalance index analyzed by the imbalance pattern analysis unit (21) between strings, the change pattern of each area of ​​the Isc area (∆a) and the Voc area (∆b) analyzed by the power generation pattern analysis unit (22), and the change pattern of the change index of the insulation resistance or the kick index, and can detect strings in which the change pattern is different as a string in which an abnormality has occurred for each index, and can increase the accuracy of abnormal string detection by allowing a comparison between strings within the same string group classified by the pattern classification unit (3).

[0147] The above module imbalance diagnosis unit (5) is configured to diagnose the cause of module imbalance, and is configured to diagnose the cause of imbalance when an abnormal string is detected by comparing the change pattern of the imbalance index in the above abnormal string detection unit (4), and the cause can be diagnosed based on the value of the imbalance index. To this end, the module imbalance diagnosis unit (5) may include an imbalance index loading module (51) and an abnormal information diagnosis module (52).

[0148] The above-mentioned imbalance index loading module (51) is configured to retrieve the imbalance index information of a string, and retrieves the imbalance index information of a string in which an abnormality is detected to have occurred due to an imbalance between modules by the above-mentioned abnormal string detection unit (4).

[0149] The above abnormal information diagnosis module (52) is configured to diagnose the cause of imbalance according to the imbalance index. The imbalance index is a value obtained by multiplying the degree of voltage imbalance and the degree of abnormal fluctuation, and since the power fluctuation coefficient is calculated as a positive or negative number depending on the power fluctuation state, a positive imbalance index means a state in which the voltage change is large, and a negative imbalance index means a state in which the voltage change is small and the current change is large. Therefore, as shown in Fig. 17, if the imbalance index is positive, it means that it is operating on the left (ⓐ) of the normal maximum power point, which means that the series resistance is large, and damage, shade, contamination, etc. of the module can be suspected. In addition, if the imbalance index is negative, it means that it is operating on the right (ⓑ) of the normal maximum power point, which means that the parallel resistance is small, and leakage current, cell cracks, and reduced insulation resistance, etc. can be suspected. Accordingly, it is possible to accurately diagnose the imbalance state between modules while simultaneously identifying the cause, enabling a quick response.

[0150] The above power generation diagnosis unit (6) is configured to diagnose the cause of the decrease in power generation of a string, and if the abnormal string detection unit (4) detects a string in which power generation decreases due to a pattern of change in the area of ​​the Isc area (∆a) or the Voc area (∆b) being different from other strings, the cause is diagnosed. To this end, the power generation diagnosis unit (6) may include an area loading module (61), an area comparison module (62), and a decrease cause detection module (63).

[0151] The above area loading module (61) is configured to load area information for each area of ​​the Isc area (∆a) and the Voc area (∆b), and loads area information for each area of ​​the string in which an abnormality is detected.

[0152] The above area comparison module (62) is configured to compare the areas of the Isc area (∆a) and the Voc area (∆b), and depending on which area has a larger area, it can be determined whether the cause of the decrease in power generation is an increase in series resistance or a decrease in parallel resistance.

[0153] The above-described cause detection module (63) is configured to detect the cause of the decrease in power generation, and can detect the cause based on the comparison result by the area comparison module (62). If the area of ​​the Isc area (∆a) is larger than the area of ​​the Voc area (∆b), the decrease in power generation can be considered to have occurred due to an increase in series resistance, such as a cable connection condition, a line condition, or shading within the module. If the area of ​​the Isc area (∆a) is smaller than the area of ​​the Voc area (∆b), the decrease in power generation can be considered to have occurred due to a decrease in parallel resistance, such as a leakage current, cell cracks, or a decrease in insulation resistance. Therefore, rapid inspection and response to the decrease in power generation can be performed based on the result detected by the cause detection module (35).

[0154] In the above, the applicant has described various embodiments of the present invention, but such embodiments are only examples of implementing the technical idea of ​​the present invention, and any change or modification that implements the technical idea of ​​the present invention should be interpreted as falling within the scope of the present invention.

Claims

1. A string classification unit that classifies strings according to device information on the strings of a solar power generation facility, A pattern analysis unit that analyzes the change patterns of indicators that affect failure in each classification of strings, A pattern classification unit that classifies strings having similar change patterns of each indicator within strings of the same classification, A comprehensive diagnosis system for a solar power generation facility, characterized by including an abnormal string detection unit that compares change patterns of indicators between strings of the same classification and detects strings with different change patterns as abnormal.

2. In the first paragraph, the string classification unit A comprehensive diagnosis system for a solar power generation facility, characterized by including a module specification collection module that collects specification information of solar modules included in a string, a module quantity collection module that collects information on the number of solar modules included in a string, a capacity information collection module that collects capacity information of an inverter connected to a string, and a string selection module that selects and classifies similar strings within a set range according to module specifications, module quantity, and inverter capacity.

3. In the second paragraph, the string classification unit It includes an irradiance collection module that collects irradiance information for a string and a module temperature collection module that collects temperature information of a solar module. The above string selection module is, A comprehensive diagnosis system for solar power generation facilities characterized by classifying strings with similar irradiance and module temperature per unit period into the same string group.

4. In the first paragraph, the pattern analysis unit Includes an imbalance pattern analysis unit that analyzes the pattern of change in the degree of imbalance of solar modules within a string, The above imbalance pattern analysis unit is, A voltage imbalance calculation unit that calculates the degree of voltage imbalance between modules that make up the string, A fluctuation abnormality calculation unit that calculates the abnormality according to the voltage and current fluctuations of the string, An imbalance index calculation unit that calculates an imbalance index indicating the degree of imbalance between modules based on the degree of voltage imbalance and the degree of abnormal fluctuation, A comprehensive diagnosis system for a solar power generation facility, characterized by including an imbalance index analysis unit that analyzes the change pattern of the imbalance index.

5. In paragraph 4, the voltage imbalance calculation unit A comprehensive diagnosis system for a solar power generation facility, characterized by including a string voltage measurement module that measures the voltage of power output from a string, a module voltage measurement module that measures the voltage of a specific module within the string, and a voltage imbalance coefficient calculation module that calculates a voltage imbalance coefficient that indicates the degree of voltage imbalance between modules by subtracting a value obtained by multiplying the number of solar modules included in the string by the voltage of the specific module from the string voltage.

6. In paragraph 5, the voltage imbalance calculation unit A comprehensive diagnosis system for a solar power generation facility, characterized by including a coefficient correction module that corrects a voltage imbalance coefficient according to solar irradiance and module temperature.

7. In paragraph 5, the above fluctuation abnormality calculation unit A comprehensive diagnosis system for a solar power generation facility, characterized by including a voltage measurement module that measures the voltage output from a string for a certain period of time, a current measurement module that measures the current output from the string for a certain period of time, and a power fluctuation coefficient calculation module that calculates the value of the ratio of the voltage change amount to the current change amount for the ratio of the voltage to the current per unit time for a certain period of time and calculates a power fluctuation coefficient that indicates the degree of voltage and current fluctuation by the average value thereof.

8. In paragraph 7, the above fluctuation abnormality calculation unit A comprehensive diagnosis system for a solar power generation facility, characterized by including a coefficient adjustment module that increases the scale while changing the standard for the normal state of the power variation coefficient to 0.

9. In the 8th paragraph, the coefficient adjustment module A comprehensive diagnosis system for a solar power generation facility characterized in that it calculates an adjusted power variation coefficient by adjusting the power variation coefficient by mathematical expression 3. (Equation 3) Pf = (1-Pd)*10 (Here, Pf is the adjusted power variation coefficient, and Pd is the initial power variation coefficient) 10. In paragraph 8, the imbalance index calculation unit A comprehensive diagnosis system for a solar power generation facility, characterized by including a voltage imbalance coefficient loading module for loading a voltage imbalance coefficient, a power variation coefficient loading module for loading a power variation coefficient, and an imbalance index calculation module for calculating an imbalance index indicating the degree of output imbalance between modules by multiplying the voltage imbalance coefficient and the power variation coefficient.

11. In paragraph 10, the comprehensive diagnosis system for solar power generation facilities In the case where an imbalance of a string is detected by comparing the change pattern of the imbalance index through the above-mentioned abnormal string detection unit, a module imbalance diagnosis unit is included to diagnose the cause of the imbalance. The above module imbalance diagnosis unit is, It includes an imbalance index loading module that loads an imbalance index and an abnormal information diagnosis module that diagnoses the cause of imbalance based on the imbalance index. The above abnormal information diagnosis module is, A comprehensive diagnosis system for solar power generation facilities characterized by diagnosing module damage, shading, and contamination when the imbalance index is positive, and diagnosing PID, cell cracks, and insulation resistance degradation when the imbalance index is negative.

12. In the first paragraph, the pattern analysis unit Includes a power generation pattern analysis unit that analyzes the change pattern of the error between the predicted power generation and the measured power generation of the string. The above power generation pattern analysis unit is, It includes a power generation prediction unit that predicts the power generation amount for each string of a solar power generation device, a power generation measurement unit that measures the power generation amount of the current string in real time, and an error analysis unit that analyzes the change pattern regarding the error of the predicted and measured power generation amount. The above error analysis section, A comprehensive diagnosis system for solar power generation facilities characterized by analyzing the change pattern of area by region on the IV coordinate plane according to predicted and measured power generation.

13. In the 12th paragraph, the error analysis unit A comprehensive diagnosis system for a solar power generation facility, characterized by including an Isc area calculation module that calculates the area of ​​an Isc area formed by a line connecting points on an IV coordinate plane according to voltage and current values ​​of predicted and measured power generation and a line connecting points indicating short-circuit current, a Voc area calculation module that calculates the area of ​​a Voc area formed by a line connecting points on an IV coordinate plane according to voltage and current values ​​of predicted and measured power generation and a line connecting points indicating open-circuit voltage, and a change pattern analysis module that analyzes a change pattern of the area of ​​the Isc area or the area of ​​the Voc area.

14. In paragraph 13, the comprehensive diagnosis system for solar power generation facilities Including a power generation diagnosis unit that diagnoses the cause of the abnormality in the power generation reduction when the change pattern of the area of ​​the Isc area or the area of ​​the Voc area is different and is detected as an abnormal string, The above power generation diagnostic unit is, A comprehensive diagnosis system for a solar power generation facility, characterized by including an area loading module that retrieves information on the area of ​​an Isc area and a Voc area, an area comparison module that compares the areas of the retrieved Isc area and Voc area, and a decrease cause detection module that detects the cause of decrease in power generation based on the result of the area comparison.

15. In the 14th paragraph, the cause of the decline detection module A comprehensive diagnosis system for solar power generation facilities characterized in that when the area of ​​the Isc region is larger than the area of ​​the Voc region, it is judged as an abnormality due to an increase in series resistance, and when the area of ​​the Voc region is larger than the area of ​​the Isc region, it is judged as an abnormality due to a decrease in the module parallel resistance.

16. In the first paragraph, the pattern analysis unit Includes an insulation resistance pattern analysis unit that analyzes the change pattern of an indicator of the insulation resistance of a string, The above insulation resistance pattern analysis unit includes a change pattern analysis unit that analyzes the change pattern of the degree of insulation resistance change over a set period of time. The above change pattern analysis unit, A comprehensive diagnosis system for a solar power generation facility, characterized by including a first insulation resistance measurement module that measures insulation resistance after an initial set period of time has elapsed, a second insulation resistance measurement module that measures insulation resistance after a set period of time has elapsed from the initial set period of time, a change index calculation module that calculates a change index indicating the degree of change in insulation resistance according to the ratio of the second insulation resistance to the first insulation resistance, and an index pattern analysis module that analyzes a change pattern of the calculated change index.

17. In the first paragraph, the pattern analysis unit Includes an insulation resistance pattern analysis unit that analyzes the change pattern of an indicator of the insulation resistance of a string, The above insulation resistance pattern analysis unit, It includes a kick index analysis unit that analyzes the change pattern of the kick index, which indicates the degree of rapid change in insulation resistance per unit time during a set period of time. The above kick index analysis section, A comprehensive diagnosis system for a solar power generation facility, characterized by including a voltage application module that applies voltage to a string for a certain period of time, an insulation resistance measurement module that measures insulation resistance at unit time intervals according to the voltage application, a kick index calculation module that calculates a kick index indicating the degree of change in insulation resistance per unit time for a certain period of time, and a kick index change analysis module that analyzes the change pattern of the calculated kick index.

18. In the 17th paragraph, the kick index calculation module A comprehensive diagnosis system for solar power generation facilities characterized by calculating a time kick index using the mathematical formula 4 below. (Equation 4) 19. In paragraph 17, the kick index analysis unit A comprehensive diagnosis system for a solar power generation facility, characterized by including a voltage regulation module that allows measurement of insulation resistance while changing the voltage in steps.

20. In paragraph 19, the kick index calculation module A comprehensive diagnosis system for solar power generation facilities characterized by calculating a voltage kick index using the mathematical formula 5 below. (Equation 5)

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