Photovoltaic testing system and testing method

Abstract

The present invention relates to the field of photovoltaic testing technology, and discloses a photovoltaic testing system and testing method, the system comprising: an initial determination module configured to determine initial test parameters for a hot spot test based on analytical results; a first judgment module configured to obtain the hot spot area of ​​an abnormal hot spot region and determine whether to optimize the initial test parameters based on the hot spot area; an optimization module configured to obtain optimized test parameters; a second judgment module configured to determine whether to compensate for the optimized test parameters based on the analytical results; a compensation module configured to determine a compensation coefficient for the optimized test parameters based on an abnormal temperature offset value and obtain the compensated test parameters; and an execution module configured to perform a final hot spot test based on the compensated test parameters and generate a test report. The present invention achieves a comprehensive assessment of the hot spot phenomenon of photovoltaic modules through precise detection of hot spots and dynamic optimization of test parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic testing, and in particular to a testing system and a testing method for photovoltaics. Background Art

[0002] Photovoltaics, a technology that converts solar energy into electricity, plays an increasingly important role in the global energy mix due to its clean, renewable nature. However, the performance and efficiency of PV modules directly determine the power generation capacity and economic benefits of the entire PV system. Therefore, comprehensive and accurate testing of PV modules to ensure their quality and performance is crucial.

[0003] With the rapid development of photovoltaic technology, the demand for performance testing of photovoltaic modules is increasing. Traditional testing methods often suffer from problems such as low test efficiency and insufficient test accuracy, and cannot meet the modern photovoltaic industry's demand for efficient and accurate testing.

[0004] Therefore, it is necessary to design a photovoltaic testing system and testing method to solve the problems existing in the current technology. Summary of the Invention

[0005] In view of this, the present invention proposes a photovoltaic testing system and testing method, aiming to solve the problems of low photovoltaic testing efficiency and insufficient testing accuracy in current technologies.

[0006] In one aspect, the present invention provides a photovoltaic testing system, comprising:

[0007] an initial determination module configured to determine a photovoltaic device to be tested, collect type data of the photovoltaic device to be tested, analyze the type data, and determine initial test parameters for a hot spot test based on the analysis results;

[0008] A first judgment module is configured to perform a hot spot test on the photovoltaic device to be tested using the initial test parameters, and collect thermal response data of the photovoltaic device to be tested in real time, and determine whether there is an abnormal hot spot area based on the thermal response data; if so, obtain the hot spot area of ​​the abnormal hot spot area, and determine whether to optimize the initial test parameters based on the hot spot area;

[0009] an optimization module configured to, when determining to optimize the initial test parameters, collect the temperature change rate of the abnormal hot spot area, determine the optimization coefficient of the initial test parameters based on the hot spot area and the temperature change rate, and obtain optimized test parameters;

[0010] a second judgment module configured to perform a hot spot test on the photovoltaic device to be tested using the optimized test parameters, divide the photovoltaic device to be tested except the abnormal hot spot area into a plurality of monitoring areas, collect regional thermal response data of each monitoring area, analyze the regional thermal response data, and determine whether to compensate for the optimized test parameters based on the analysis results;

[0011] a compensation module configured to, when determining to compensate the optimized test parameters, obtain an abnormal temperature offset value of the abnormal hot spot region based on the regional thermal response data, determine a compensation coefficient of the optimized test parameters according to the abnormal temperature offset value, and obtain compensated test parameters;

[0012] The execution module is configured to perform a final hot spot test on the photovoltaic device to be tested according to the compensation test parameters and generate a test report.

[0013] Furthermore, the initial determination module analyzes the type data and determines the initial test parameters of the hot spot test based on the analysis result, including:

[0014] The type data includes monocrystalline silicon photovoltaics, polycrystalline silicon photovoltaics, thin film photovoltaics and concentrated photovoltaics;

[0015] When the photovoltaic device to be tested is the monocrystalline silicon photovoltaic device, determining the initial test parameter to be a first test parameter;

[0016] When the photovoltaic device to be tested is the polycrystalline silicon photovoltaic device, determining the initial test parameter to be a second test parameter;

[0017] When the photovoltaic device to be tested is the thin-film photovoltaic device, determining that the initial test parameter is a third test parameter;

[0018] When the photovoltaic system to be tested is the concentrated photovoltaic system, the initial test parameter is determined to be a fourth test parameter.

[0019] Furthermore, when the first judgment module judges whether there is an abnormal hot spot area based on the thermal response data, it includes:

[0020] A two-dimensional rectangular coordinate system is established with the geometric center of the photovoltaic device to be tested as the origin, the length direction as the horizontal coordinate, and the width direction as the vertical coordinate;

[0021] Mapping the thermal response data to the two-dimensional rectangular coordinate system to obtain a thermal response distribution map;

[0022] In the thermal response distribution map, monitoring coordinates are preset based on a fixed-interval grid, and a real-time temperature value of the monitoring coordinate is randomly collected;

[0023] Comparing the real-time temperature value with a real-time temperature threshold to determine whether the monitoring coordinate is an abnormal monitoring coordinate;

[0024] If the monitoring coordinates are the abnormal monitoring coordinates, the abnormal monitoring area is determined with the abnormal monitoring coordinates as the origin and the radius as r;

[0025] Counting the number of monitoring coordinates corresponding to the real-time temperature value greater than the real-time temperature threshold in the abnormal monitoring area, and recording it as the monitoring number;

[0026] If the monitoring quantity is greater than the monitoring quantity threshold, the abnormal monitoring area is determined to be the abnormal hot spot area.

[0027] Furthermore, the first judgment module obtains the hot spot area of ​​the abnormal hot spot region, and judges whether to optimize the initial test parameters according to the hot spot area, including:

[0028] The hot spot area is the sum of the areas of all abnormal monitoring areas after removing the overlapping parts;

[0029] When the hot spot area is greater than the hot spot area threshold, determining to optimize the initial test parameters;

[0030] Otherwise, the initial test parameters are not optimized.

[0031] Furthermore, the optimization module determines the optimization coefficient of the initial test parameter based on the hot spot area and the temperature change rate, and obtains the optimized test parameter, including:

[0032] Determining an area factor based on a ratio of the hot spot area to the total photovoltaic area to be tested;

[0033] determining a rate factor based on a ratio of the temperature change rate to a standard temperature change rate;

[0034] Combining the area factor and the speed factor into an optimization feature group;

[0035] Comparing the optimized feature group with the historical optimized group, and determining the optimization coefficient of the initial test parameter according to the comparison result;

[0036] When there is a historical optimization feature group identical to the optimization feature group in the historical optimization group, the historical optimization coefficient corresponding to the historical optimization feature group is used as the optimization coefficient, and the product value of the historical optimization coefficient and the initial test parameter is used as the optimization test parameter;

[0037] When there is no historical optimization feature group identical to the optimization feature group in the historical optimization group, an optimization factor is determined according to the optimization feature group, an optimization coefficient of the initial test parameter is determined according to the optimization factor, and the product value of the optimization coefficient and the initial test parameter is used as the optimized test parameter.

[0038] Furthermore, when the optimization module determines the optimization coefficient of the initial test parameter according to the optimization factor, it includes:

[0039] The optimization factor is a weighted average of the area factor and the rate factor;

[0040] Comparing the optimization factor with a first optimization factor and a second optimization factor, and determining an optimization coefficient of the initial test parameter according to the comparison result; wherein the first optimization factor is smaller than the second optimization factor;

[0041] When the optimization factor is less than or equal to the first optimization factor, determining the optimization coefficient to be the first optimization coefficient;

[0042] When the optimization factor is greater than the first optimization factor and less than or equal to the second optimization factor, determining the optimization coefficient to be the second optimization coefficient, and the second optimization coefficient is greater than the first optimization coefficient;

[0043] When the optimization factor is greater than the second optimization factor, the optimization coefficient is determined to be a third optimization coefficient, and the third optimization coefficient is greater than the second optimization coefficient.

[0044] Furthermore, the second judgment module analyzes the regional thermal response data and determines whether to compensate the optimized test parameters based on the analysis result, including:

[0045] Extracting features from the regional thermal response data to obtain temperature characteristic values ​​corresponding to each of the monitoring areas;

[0046] Comparing the temperature characteristic value with a temperature characteristic threshold value to determine whether the monitoring area is a compensation monitoring area;

[0047] If the temperature characteristic value corresponding to the monitoring area is greater than the temperature characteristic threshold, the monitoring area is marked as the compensation monitoring area;

[0048] Otherwise, the monitoring area is marked as a normal monitoring area;

[0049] Counting the number of all the compensation monitoring areas and recording it as the compensation number;

[0050] The compensation amount is compared with a compensation amount threshold, and if the compensation amount is greater than the compensation amount threshold, it is determined that the optimized test parameter is compensated.

[0051] Furthermore, when the compensation module obtains the abnormal temperature offset value of the abnormal hot spot area based on the regional thermal response data, it includes:

[0052] Collecting abnormal temperature data of the abnormal hot spot area, and performing feature extraction on the abnormal temperature data to obtain abnormal temperature feature values;

[0053] Calculate the average temperature characteristic value of all the compensation monitoring areas, and record it as the compensation average characteristic value;

[0054] Calculate the average temperature characteristic value of all the common monitoring areas, and record it as the common average characteristic value;

[0055] The abnormal temperature offset value is calculated according to the abnormal temperature characteristic value, the compensated average characteristic value and the normal average characteristic value.

[0056] Furthermore, the compensation module determines the compensation coefficient of the optimized test parameter according to the abnormal temperature offset value, and obtains the compensated test parameter, including:

[0057] determining an offset factor based on a ratio of the abnormal temperature offset value to an abnormal temperature offset value threshold;

[0058] Comparing the offset factor with a preset compensation coefficient table, and determining the compensation coefficient of the optimized test parameter according to the comparison result;

[0059] The product value of the compensation coefficient and the optimized test parameter is used as the compensation test parameter.

[0060] Compared with existing technologies, the present invention offers the following advantages: the photovoltaic testing system provided by the present invention achieves a comprehensive assessment of hot spot phenomena in photovoltaic modules through precise hot spot detection and dynamic optimization of test parameters. This testing system not only improves testing accuracy and efficiency but also facilitates the timely detection and resolution of potential hot spot issues, thereby ensuring the safe operation and long-term stability of photovoltaic modules. The testing system also features a high degree of automation, significantly reducing manual intervention, lowering testing costs, and improving the convenience and operability of testing.

[0061] In another aspect, the present invention further provides a photovoltaic testing method, comprising the following steps:

[0062] Determine a photovoltaic device to be tested, collect type data of the photovoltaic device to be tested, analyze the type data, and determine initial test parameters for a hot spot test based on the analysis results;

[0063] Performing a hot spot test on the photovoltaic device to be tested using the initial test parameters, and collecting thermal response data of the photovoltaic device to be tested in real time, and determining whether an abnormal hot spot region exists based on the thermal response data; if so, obtaining the hot spot area of ​​the abnormal hot spot region, and determining whether to optimize the initial test parameters based on the hot spot area;

[0064] When it is determined that the initial test parameters are to be optimized, the temperature change rate of the abnormal hot spot area is collected, and the optimization coefficient of the initial test parameters is determined based on the hot spot area and the temperature change rate, and the optimized test parameters are obtained;

[0065] Performing a hot spot test on the photovoltaic system to be tested using the optimized test parameters, dividing the photovoltaic system to be tested except the abnormal hot spot area into a plurality of monitoring areas, collecting regional thermal response data of each monitoring area, analyzing the regional thermal response data, and determining whether to compensate for the optimized test parameters based on the analysis results;

[0066] When it is determined that the optimized test parameter is to be compensated, an abnormal temperature offset value of the abnormal hot spot region is obtained based on the regional thermal response data, a compensation coefficient of the optimized test parameter is determined according to the abnormal temperature offset value, and a compensated test parameter is obtained;

[0067] Perform a final hot spot test on the photovoltaic device to be tested according to the compensation test parameters and generate a test report.

[0068] It is understandable that the above-mentioned photovoltaic testing system and testing method have the same beneficial effects, which will not be described in detail here. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0070] Figure 1 A structural block diagram of a photovoltaic test system provided by an embodiment of the present invention;

[0071] Figure 2 A flowchart of a photovoltaic testing method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0072] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, unless there is a conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0073] See Figure 1 As shown, in some embodiments of the present application, this embodiment provides a photovoltaic testing system, including:

[0074] an initial determination module configured to determine a photovoltaic device to be tested, collect type data of the photovoltaic device to be tested, analyze the type data, and determine initial test parameters for a hot spot test based on the analysis results;

[0075] A first judgment module is configured to perform a hot spot test on the photovoltaic device to be tested using the initial test parameters, and collect thermal response data of the photovoltaic device to be tested in real time, and determine whether there is an abnormal hot spot area based on the thermal response data; if so, obtain the hot spot area of ​​the abnormal hot spot area, and determine whether to optimize the initial test parameters based on the hot spot area;

[0076] an optimization module configured to, when determining to optimize the initial test parameters, collect the temperature change rate of the abnormal hot spot area, determine the optimization coefficient of the initial test parameters based on the hot spot area and the temperature change rate, and obtain optimized test parameters;

[0077] a second judgment module configured to perform a hot spot test on the photovoltaic device to be tested using the optimized test parameters, divide the photovoltaic device to be tested except the abnormal hot spot area into a plurality of monitoring areas, collect regional thermal response data of each monitoring area, analyze the regional thermal response data, and determine whether to compensate for the optimized test parameters based on the analysis results;

[0078] a compensation module configured to, when determining to compensate the optimized test parameters, obtain an abnormal temperature offset value of the abnormal hot spot region based on the regional thermal response data, determine a compensation coefficient of the optimized test parameters according to the abnormal temperature offset value, and obtain compensated test parameters;

[0079] The execution module is configured to perform a final hot spot test on the photovoltaic device to be tested according to the compensation test parameters and generate a test report.

[0080] In this embodiment, the initial test parameters include test time and thermal actuation temperature.

[0081] In this embodiment, the test report includes the test results, the location, area and temperature distribution information of the abnormal hot spot area.

[0082] It is understood that the photovoltaic testing system provided in this embodiment achieves a comprehensive assessment of hot spot phenomena in photovoltaic modules through precise hot spot detection and dynamic optimization of test parameters. This testing system not only improves testing accuracy and efficiency but also facilitates the timely detection and resolution of potential hot spot issues, thereby ensuring the safe operation and long-term stability of photovoltaic modules. This testing system also features a high degree of automation, significantly reducing manual intervention, lowering testing costs, and improving the convenience and operability of testing.

[0083] Specifically, the initial determination module analyzes the type data and determines the initial test parameters of the hot spot test based on the analysis results, including:

[0084] The type data includes monocrystalline silicon photovoltaics, polycrystalline silicon photovoltaics, thin film photovoltaics and concentrated photovoltaics;

[0085] When the photovoltaic device to be tested is the monocrystalline silicon photovoltaic device, determining the initial test parameter to be a first test parameter;

[0086] When the photovoltaic device to be tested is the polycrystalline silicon photovoltaic device, determining the initial test parameter to be a second test parameter;

[0087] When the photovoltaic device to be tested is the thin-film photovoltaic device, determining that the initial test parameter is a third test parameter;

[0088] When the photovoltaic system to be tested is the concentrated photovoltaic system, the initial test parameter is determined to be a fourth test parameter.

[0089] Understandably, different types of PV modules will respond differently to hot spot testing due to differences in their materials, structures, and manufacturing processes. Therefore, by setting targeted initial test parameters, we can more effectively simulate the hot spot phenomenon under actual operating conditions, thereby improving the accuracy and pertinence of the test.

[0090] Specifically, when the first judgment module judges whether there is an abnormal hot spot area based on the thermal response data, it includes:

[0091] A two-dimensional rectangular coordinate system is established with the geometric center of the photovoltaic device to be tested as the origin, the length direction as the horizontal coordinate, and the width direction as the vertical coordinate;

[0092] Mapping the thermal response data to the two-dimensional rectangular coordinate system to obtain a thermal response distribution map;

[0093] In the thermal response distribution map, monitoring coordinates are preset based on a fixed-interval grid, and a real-time temperature value of the monitoring coordinate is randomly collected;

[0094] Comparing the real-time temperature value with a real-time temperature threshold to determine whether the monitoring coordinate is an abnormal monitoring coordinate;

[0095] If the monitoring coordinates are the abnormal monitoring coordinates, the abnormal monitoring area is determined with the abnormal monitoring coordinates as the origin and the radius as r;

[0096] Counting the number of monitoring coordinates corresponding to the real-time temperature value greater than the real-time temperature threshold in the abnormal monitoring area, and recording it as the monitoring number;

[0097] If the monitoring quantity is greater than the monitoring quantity threshold, the abnormal monitoring area is determined to be the abnormal hot spot area.

[0098] In this embodiment, the preferred value of the radius r is 3 cm.

[0099] It can be understood that by setting a fixed grid of preset monitoring coordinates and randomly collecting temperature values, the thermal response of the photovoltaic system under test can be more comprehensively and randomly monitored, avoiding misjudgments due to local anomalies. At the same time, by counting the number of monitoring coordinates within the abnormal monitoring area, the presence of abnormal hot spots can be more accurately determined, improving the accuracy of the test. In addition, the optimal value setting of radius r can ensure that the determination of abnormal hot spot areas is neither too sensitive nor too slow, further improving the reliability and stability of the test.

[0100] Specifically, the first judgment module obtains the hot spot area of ​​the abnormal hot spot region, and judges whether to optimize the initial test parameters according to the hot spot area, including:

[0101] The hot spot area is the sum of the areas of all abnormal monitoring areas after removing the overlapping parts;

[0102] When the hot spot area is greater than the hot spot area threshold, determining to optimize the initial test parameters;

[0103] Otherwise, the initial test parameters are not optimized.

[0104] In this embodiment, if there are two abnormal monitoring areas, their areas are both 9, and the area of ​​the overlapping part is 3, then the area of ​​the hot spot is 15.

[0105] It can be understood that by setting the hot spot area threshold, hot spot conditions that require optimization of test parameters can be distinguished, avoiding unnecessary optimization of minor hot spot phenomena, thereby improving the efficiency and specificity of the test.

[0106] Specifically, the optimization module determines the optimization coefficient of the initial test parameter based on the hot spot area and the temperature change rate, and obtains the optimized test parameter, including:

[0107] Determining an area factor based on a ratio of the hot spot area to the total photovoltaic area to be tested;

[0108] determining a rate factor based on a ratio of the temperature change rate to a standard temperature change rate;

[0109] Combining the area factor and the speed factor into an optimization feature group;

[0110] Comparing the optimized feature group with the historical optimized group, and determining the optimization coefficient of the initial test parameter according to the comparison result;

[0111] When there is a historical optimization feature group identical to the optimization feature group in the historical optimization group, the historical optimization coefficient corresponding to the historical optimization feature group is used as the optimization coefficient, and the product value of the historical optimization coefficient and the initial test parameter is used as the optimization test parameter;

[0112] When there is no historical optimization feature group identical to the optimization feature group in the historical optimization group, an optimization factor is determined according to the optimization feature group, an optimization coefficient of the initial test parameter is determined according to the optimization factor, and the product value of the optimization coefficient and the initial test parameter is used as the optimized test parameter.

[0113] In this embodiment, the optimization feature group is (area factor, rate factor), which is represented by letters (a, b); the historical optimization group is (historical area factor, historical rate factor; historical optimization coefficient), which is represented by letters (ai, bi; ci).

[0114] It's understandable that by comparing the current hot spot area and temperature change rate with historical data, the optimization coefficient can be quickly and accurately determined, resulting in more reasonable optimized test parameters. This historical data-based optimization method not only improves test accuracy and efficiency, but also avoids improper optimization caused by human factors, further ensuring the safe operation and long-term stability of photovoltaic modules.

[0115] Specifically, when the optimization module determines the optimization coefficient of the initial test parameter according to the optimization factor, it includes:

[0116] The optimization factor is a weighted average of the area factor and the rate factor;

[0117] Comparing the optimization factor with a first optimization factor and a second optimization factor, and determining an optimization coefficient of the initial test parameter according to the comparison result; wherein the first optimization factor is smaller than the second optimization factor;

[0118] When the optimization factor is less than or equal to the first optimization factor, determining the optimization coefficient as the first optimization coefficient;

[0119] When the optimization factor is greater than the first optimization factor and less than or equal to the second optimization factor, determining the optimization coefficient to be the second optimization coefficient, and the second optimization coefficient is greater than the first optimization coefficient;

[0120] When the optimization factor is greater than the second optimization factor, the optimization coefficient is determined to be a third optimization coefficient, and the third optimization coefficient is greater than the second optimization coefficient.

[0121] In this embodiment, the first optimization factor and the second optimization factor are obtained through training of a machine learning algorithm based on a large amount of historical test data.

[0122] It can be understood that by setting the first and second optimization factors, the value range of the optimization coefficient can be more finely divided, thereby achieving more refined adjustments to the initial test parameters. This method of determining optimization factors based on machine learning algorithms not only improves test accuracy and efficiency, but also adapts to the testing needs of different types and situations of photovoltaic modules, further enhancing the flexibility and applicability of the test system.

[0123] Specifically, when the second judgment module analyzes the regional thermal response data and determines whether to compensate the optimized test parameters based on the analysis result, it includes:

[0124] Extracting features from the regional thermal response data to obtain temperature characteristic values ​​corresponding to each of the monitoring areas;

[0125] Comparing the temperature characteristic value with a temperature characteristic threshold value to determine whether the monitoring area is a compensation monitoring area;

[0126] If the temperature characteristic value corresponding to the monitoring area is greater than the temperature characteristic threshold, the monitoring area is marked as the compensation monitoring area;

[0127] Otherwise, the monitoring area is marked as a normal monitoring area;

[0128] Counting the number of all the compensation monitoring areas and recording it as the compensation number;

[0129] The compensation amount is compared with a compensation amount threshold, and if the compensation amount is greater than the compensation amount threshold, it is determined that the optimized test parameter is compensated.

[0130] In this embodiment, the temperature characteristic value refers to the average value of the real-time temperature values ​​of all monitoring coordinates in the monitoring area.

[0131] It's understandable that by extracting features from regional thermal response data and setting temperature feature thresholds, we can more accurately identify monitoring areas requiring compensation, thus avoiding misjudgments due to localized excessive temperatures. Furthermore, by counting the number of compensated monitoring areas, we can more comprehensively assess the applicability of optimized test parameters, further improving test accuracy and efficiency.

[0132] Specifically, when the compensation module obtains the abnormal temperature offset value of the abnormal hot spot area based on the regional thermal response data, it includes:

[0133] Collecting abnormal temperature data of the abnormal hot spot area, and performing feature extraction on the abnormal temperature data to obtain abnormal temperature feature values;

[0134] Calculate the average temperature characteristic value of all the compensation monitoring areas, and record it as the compensation average characteristic value;

[0135] Calculate the average temperature characteristic value of all the common monitoring areas, and record it as the common average characteristic value;

[0136] The abnormal temperature offset value is calculated according to the abnormal temperature characteristic value, the compensated average characteristic value and the normal average characteristic value.

[0137] In this embodiment, the abnormal temperature characteristic value refers to the difference between the maximum and minimum real-time temperature values ​​of all monitoring coordinates within the abnormal hot spot area.

[0138] It can be understood that the abnormal temperature offset value is obtained by the following formula:

[0139] ΔT=T a -2Tc+Tn;

[0140] Where ΔT represents the abnormal temperature offset value; T a represents the abnormal temperature characteristic value; Tc represents the average temperature characteristic value of the compensation monitoring area; Tn represents the average temperature characteristic value of the normal monitoring area.

[0141] Specifically, when the compensation module determines the compensation coefficient of the optimized test parameter according to the abnormal temperature offset value and obtains the compensated test parameter, it includes:

[0142] determining an offset factor based on a ratio of the abnormal temperature offset value to an abnormal temperature offset value threshold;

[0143] Comparing the offset factor with a preset compensation coefficient table, and determining the compensation coefficient of the optimized test parameter according to the comparison result;

[0144] The product value of the compensation coefficient and the optimized test parameter is used as the compensation test parameter.

[0145] In this embodiment, the preset compensation coefficient table includes multiple offset factors and their corresponding compensation coefficients, and the corresponding compensation coefficient can be quickly found according to the actual offset factor, thereby achieving rapid compensation of the optimized test parameters.

[0146] In this embodiment, when the abnormal temperature offset value is 3, the compensation coefficient is preferably 1.2; when the abnormal temperature offset value is 6, the compensation coefficient is preferably 1.5; when the abnormal temperature offset value is greater than 6, the compensation coefficient is preferably 2.0.

[0147] It's understandable that by setting an abnormal temperature offset threshold and determining a compensation factor based on the offset factor, test parameters can be adjusted more precisely, further improving test accuracy and efficiency. Furthermore, the preset compensation factor table allows for quick and accurate retrieval of the corresponding compensation factor, avoiding issues with improper compensation caused by human error.

[0148] See Figure 2 As shown, in some embodiments of the present application, this embodiment provides a photovoltaic testing method, comprising the following steps:

[0149] S100: Determine a photovoltaic device to be tested, collect type data of the photovoltaic device to be tested, analyze the type data, and determine initial test parameters for a hot spot test based on the analysis results;

[0150] S200: performing a hot spot test on the photovoltaic device to be tested using the initial test parameters, and collecting thermal response data of the photovoltaic device to be tested in real time, and determining whether an abnormal hot spot region exists based on the thermal response data; if so, obtaining the hot spot area of ​​the abnormal hot spot region, and determining whether to optimize the initial test parameters based on the hot spot area;

[0151] S300: When it is determined that the initial test parameters are to be optimized, collecting the temperature change rate of the abnormal hot spot area, and determining the optimization coefficient of the initial test parameters based on the hot spot area and the temperature change rate, and obtaining the optimized test parameters;

[0152] S400: performing a hot spot test on the photovoltaic device to be tested using the optimized test parameters, dividing the photovoltaic device to be tested except the abnormal hot spot area into a plurality of monitoring areas, collecting regional thermal response data of each monitoring area, analyzing the regional thermal response data, and determining whether to compensate for the optimized test parameters based on the analysis results;

[0153] S500: When it is determined that the optimized test parameter is to be compensated, an abnormal temperature offset value of the abnormal hot spot region is obtained based on the regional thermal response data, a compensation coefficient of the optimized test parameter is determined according to the abnormal temperature offset value, and a compensated test parameter is obtained;

[0154] S600: Perform a final hot spot test on the photovoltaic device to be tested according to the compensation test parameters, and generate a test report.

[0155] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or a combination of software and hardware embodiments. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0156] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0157] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0158] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0159] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A photovoltaic testing system, characterized in that: include: an initial determination module configured to determine a photovoltaic device to be tested, collect type data of the photovoltaic device to be tested, analyze the type data, and determine initial test parameters for a hot spot test based on the analysis results; A first judgment module is configured to perform a hot spot test on the photovoltaic device to be tested using the initial test parameters, collect thermal response data of the photovoltaic device to be tested in real time, and judge whether an abnormal hot spot area exists based on the thermal response data; If yes, obtaining the hot spot area of ​​the abnormal hot spot region, and determining whether to optimize the initial test parameters according to the hot spot area; an optimization module configured to, when determining to optimize the initial test parameters, collect the temperature change rate of the abnormal hot spot area, determine the optimization coefficient of the initial test parameters based on the hot spot area and the temperature change rate, and obtain optimized test parameters; a second judgment module configured to perform a hot spot test on the photovoltaic device to be tested using the optimized test parameters, divide the photovoltaic device to be tested except the abnormal hot spot area into a plurality of monitoring areas, collect regional thermal response data of each monitoring area, analyze the regional thermal response data, and determine whether to compensate for the optimized test parameters based on the analysis results; a compensation module configured to, when determining to compensate the optimized test parameters, obtain an abnormal temperature offset value of the abnormal hot spot region based on the regional thermal response data, determine a compensation coefficient of the optimized test parameters according to the abnormal temperature offset value, and obtain compensated test parameters; The execution module is configured to perform a final hot spot test on the photovoltaic device to be tested according to the compensation test parameters and generate a test report.

2. The photovoltaic testing system according to claim 1, characterized in that: The initial determination module analyzes the type data and determines the initial test parameters of the hot spot test based on the analysis result, including: The type data includes monocrystalline silicon photovoltaics, polycrystalline silicon photovoltaics, thin film photovoltaics and concentrated photovoltaics; When the photovoltaic device to be tested is the monocrystalline silicon photovoltaic device, determining the initial test parameter to be a first test parameter; When the photovoltaic device to be tested is the polycrystalline silicon photovoltaic device, determining the initial test parameter to be a second test parameter; When the photovoltaic device to be tested is the thin-film photovoltaic device, determining that the initial test parameter is a third test parameter; When the photovoltaic system to be tested is the concentrated photovoltaic system, the initial test parameter is determined to be a fourth test parameter.

3. The photovoltaic testing system according to claim 2, characterized in that: When the first judgment module judges whether there is an abnormal hot spot area based on the thermal response data, it includes: A two-dimensional rectangular coordinate system is established with the geometric center of the photovoltaic device to be tested as the origin, the length direction as the horizontal coordinate, and the width direction as the vertical coordinate; Mapping the thermal response data to the two-dimensional rectangular coordinate system to obtain a thermal response distribution map; In the thermal response distribution map, monitoring coordinates are preset based on a fixed-interval grid, and a real-time temperature value of the monitoring coordinate is randomly collected; Comparing the real-time temperature value with a real-time temperature threshold to determine whether the monitoring coordinate is an abnormal monitoring coordinate; If the monitoring coordinates are the abnormal monitoring coordinates, the abnormal monitoring area is determined with the abnormal monitoring coordinates as the origin and the radius as r; Counting the number of monitoring coordinates corresponding to the real-time temperature value greater than the real-time temperature threshold in the abnormal monitoring area, and recording it as the monitoring number; If the monitoring quantity is greater than the monitoring quantity threshold, the abnormal monitoring area is determined to be the abnormal hot spot area.

4. The photovoltaic testing system according to claim 3, characterized in that: The first judgment module obtains the hot spot area of ​​the abnormal hot spot region and judges whether to optimize the initial test parameters according to the hot spot area, including: The hot spot area is the sum of the areas of all abnormal monitoring areas after removing the overlapping parts; When the hot spot area is greater than the hot spot area threshold, determining to optimize the initial test parameters; Otherwise, the initial test parameters are not optimized.

5. The photovoltaic testing system according to claim 4, characterized in that: The optimization module determines the optimization coefficient of the initial test parameter based on the hot spot area and the temperature change rate, and obtains the optimized test parameter, including: Determining an area factor based on a ratio of the hot spot area to the total photovoltaic area to be tested; determining a rate factor based on a ratio of the temperature change rate to a standard temperature change rate; Combining the area factor and the speed factor into an optimization feature group; Comparing the optimized feature group with the historical optimized group, and determining the optimization coefficient of the initial test parameter according to the comparison result; When there is a historical optimization feature group identical to the optimization feature group in the historical optimization group, the historical optimization coefficient corresponding to the historical optimization feature group is used as the optimization coefficient, and the product value of the historical optimization coefficient and the initial test parameter is used as the optimization test parameter; When there is no historical optimization feature group identical to the optimization feature group in the historical optimization group, an optimization factor is determined according to the optimization feature group, an optimization coefficient of the initial test parameter is determined according to the optimization factor, and the product value of the optimization coefficient and the initial test parameter is used as the optimized test parameter.

6. The photovoltaic testing system according to claim 5, characterized in that: When the optimization module determines the optimization coefficient of the initial test parameter according to the optimization factor, it includes: The optimization factor is a weighted average of the area factor and the rate factor; Comparing the optimization factor with a first optimization factor and a second optimization factor, and determining an optimization coefficient of the initial test parameter according to the comparison result; wherein the first optimization factor is smaller than the second optimization factor; When the optimization factor is less than or equal to the first optimization factor, determining the optimization coefficient to be the first optimization coefficient; When the optimization factor is greater than the first optimization factor and less than or equal to the second optimization factor, determining the optimization coefficient to be the second optimization coefficient, and the second optimization coefficient is greater than the first optimization coefficient; When the optimization factor is greater than the second optimization factor, the optimization coefficient is determined to be a third optimization coefficient, and the third optimization coefficient is greater than the second optimization coefficient.

7. The photovoltaic testing system according to claim 6, characterized in that: The second judgment module analyzes the regional thermal response data and determines whether to compensate the optimized test parameters based on the analysis result, including: Extracting features from the regional thermal response data to obtain temperature characteristic values ​​corresponding to each of the monitoring areas; Comparing the temperature characteristic value with a temperature characteristic threshold value to determine whether the monitoring area is a compensation monitoring area; If the temperature characteristic value corresponding to the monitoring area is greater than the temperature characteristic threshold, the monitoring area is marked as the compensation monitoring area; Otherwise, the monitoring area is marked as a normal monitoring area; Counting the number of all the compensation monitoring areas and recording it as the compensation number; The compensation amount is compared with a compensation amount threshold, and if the compensation amount is greater than the compensation amount threshold, it is determined that the optimized test parameter is compensated.

8. The photovoltaic testing system according to claim 7, characterized in that: When the compensation module obtains the abnormal temperature offset value of the abnormal hot spot area based on the regional thermal response data, it includes: Collecting abnormal temperature data of the abnormal hot spot area, and performing feature extraction on the abnormal temperature data to obtain abnormal temperature feature values; Calculate the average temperature characteristic value of all the compensation monitoring areas, and record it as the compensation average characteristic value; Calculate the average temperature characteristic value of all the common monitoring areas, and record it as the common average characteristic value; The abnormal temperature offset value is calculated according to the abnormal temperature characteristic value, the compensated average characteristic value and the normal average characteristic value.

9. The photovoltaic testing system according to claim 8, characterized in that: The compensation module determines the compensation coefficient of the optimized test parameter according to the abnormal temperature offset value and obtains the compensated test parameter, including: determining an offset factor based on a ratio of the abnormal temperature offset value to an abnormal temperature offset value threshold; Comparing the offset factor with a preset compensation coefficient table, and determining the compensation coefficient of the optimized test parameter according to the comparison result; The product value of the compensation coefficient and the optimized test parameter is used as the compensation test parameter.

10. A photovoltaic testing method, applied to the photovoltaic testing system according to any one of claims 1 to 9, characterized in that: include: Determine a photovoltaic device to be tested, collect type data of the photovoltaic device to be tested, analyze the type data, and determine initial test parameters for a hot spot test based on the analysis results; Performing a hot spot test on the photovoltaic device to be tested using the initial test parameters, collecting thermal response data of the photovoltaic device to be tested in real time, and determining whether an abnormal hot spot area exists based on the thermal response data; If yes, obtaining the hot spot area of ​​the abnormal hot spot region, and determining whether to optimize the initial test parameters according to the hot spot area; When it is determined that the initial test parameters are to be optimized, the temperature change rate of the abnormal hot spot area is collected, and the optimization coefficient of the initial test parameters is determined based on the hot spot area and the temperature change rate, and the optimized test parameters are obtained; Performing a hot spot test on the photovoltaic system to be tested using the optimized test parameters, dividing the photovoltaic system to be tested except the abnormal hot spot area into a plurality of monitoring areas, collecting regional thermal response data of each monitoring area, analyzing the regional thermal response data, and determining whether to compensate for the optimized test parameters based on the analysis results; When it is determined that the optimized test parameter is to be compensated, an abnormal temperature offset value of the abnormal hot spot region is obtained based on the regional thermal response data, a compensation coefficient of the optimized test parameter is determined according to the abnormal temperature offset value, and a compensated test parameter is obtained; Perform a final hot spot test on the photovoltaic device to be tested according to the compensation test parameters and generate a test report.

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