Method, system, device, equipment and medium for identifying hot spot phenomenon of photovoltaic curtain wall

Abstract

The present application provides a method, system, device, equipment and medium for identifying hot spot phenomena in photovoltaic curtain walls. The system includes a BIPV module, including multiple battery cells connected in series and / or parallel; multiple sensor modules, each sensor module corresponds to a battery cell, and is used to measure parameter information of the battery cell; a control device, which is electrically connected to each sensor module, and is used to obtain parameter information measured by each sensor module and corresponding battery cell position information, calculate difference information between each battery cell and battery cells within a preset range based on the battery cell position information and parameter information, including temperature difference information and power difference information, obtain parameter change information of each battery cell within a preset time range based on the parameter information, including temperature change information and power change information, identify whether the battery cell has a hot spot based on the difference information and parameter change information corresponding to each battery cell, so as to complete the identification of hot spot phenomena in the photovoltaic curtain wall.

Description

Technical Field

[0001] The present application relates to the field of photovoltaic technology, and in particular to a method, system, device, equipment and medium for identifying hot spot phenomena of photovoltaic curtain walls. Background Art

[0002] Photovoltaic curtain walls, as a building integrated system that converts solar energy into electrical energy, have been widely used in recent years. However, photovoltaic modules may encounter hot spot phenomena in actual operation, which has a serious impact on the performance and life of the modules. Hot spot phenomena are usually caused by partial obstruction or damage of the cells, which causes these cells to generate local high temperatures at high power output, thus affecting the efficiency of the entire module. Traditional hot spot detection methods mainly rely on manual inspections and thermal imagers, which are not only costly and inefficient, but also difficult to monitor in real time.

[0003] Therefore, a method for identifying hot spot phenomenon of photovoltaic curtain walls is urgently needed to solve at least one of the above problems. Summary of the invention

[0004] The present application provides a method, system, device, equipment and medium for identifying hot spot phenomena in photovoltaic curtain walls, aiming to solve the hot spot phenomenon that may be encountered in the actual operation of current photovoltaic modules, which has a serious impact on the performance and life of the modules. The hot spot phenomenon is usually caused by part of the battery cell being blocked or damaged, causing these parts of the battery cell to generate local high temperature at high power output, thereby affecting the efficiency of the entire module. Traditional hot spot detection methods mainly rely on manual inspections and thermal imagers. These methods are not only costly and inefficient, but also difficult to monitor in real time.

[0005] In a first aspect, the present application provides a hot spot phenomenon identification system for a photovoltaic curtain wall, comprising:

[0006] A BIPV module, wherein the BIPV module comprises a plurality of solar cells, wherein the plurality of solar cells are connected in series and / or in parallel;

[0007] A plurality of sensor modules, each of which corresponds to one of the battery cells and is used to measure parameter information corresponding to each of the battery cells;

[0008] A control device, wherein the control device is electrically connected to each of the sensing modules, and is used to obtain parameter information measured by each sensing module and cell position information of the corresponding cell, and the control device calculates difference information between each of the cells and cells within a preset range based on the cell position information and parameter information; the difference information at least includes temperature difference information and power difference information, and the control device obtains parameter change information of each cell within a preset time range based on the parameter information; the parameter change information at least includes temperature change information and power change information, and the control device identifies whether the cell has a hot spot based on the difference information corresponding to each cell and the parameter change information, so as to complete the identification of the hot spot phenomenon of the photovoltaic curtain wall.

[0009] In a second aspect, the present application provides a method for identifying hot spot phenomena of photovoltaic curtain walls, which is applied to a control device of a hot spot phenomenon identification system of a photovoltaic curtain wall provided in any embodiment of the present application; the method comprises:

[0010] Obtaining parameter information measured by each sensor module and cell position information of the corresponding cell;

[0011] Calculate the difference information between each of the battery cells and the battery cells within a preset range according to the battery cell position information and parameter information; the difference information includes at least temperature difference information and power difference information;

[0012] Acquire parameter change information of each of the battery cells within a preset time range according to the parameter information; the parameter change information at least includes temperature change information and power change information;

[0013] According to the difference information corresponding to each of the cells and the parameter change information, it is identified whether the cell has a hot spot, thereby completing the identification of the hot spot phenomenon of the photovoltaic curtain wall.

[0014] In some embodiments, after completing the identification of the hot spot phenomenon of the photovoltaic curtain wall, it also includes: determining the cell with the hot spot as the target cell; obtaining the circuit connection information corresponding to the BIPV module; parsing the circuit connection information to obtain multiple power supply branches and at least one power supply bypass corresponding to the BIPV module; each of the power supply branches includes multiple cells; determining the target branch corresponding to the target cell among the multiple power supply branches according to the cell position information corresponding to the target cell; generating current control information according to the cell position information of each cell corresponding to the target branch, so as to divert the current corresponding to the target branch to the power supply bypass among the multiple power supply branches.

[0015] Exemplarily, the hot spot phenomenon identification system of the photovoltaic curtain wall also includes multiple switch modules, and the switch modules are arranged in the power supply branch and the power supply bypass; the current control information is generated according to the cell position information of each cell corresponding to the target branch, including: obtaining the switch position information corresponding to the switch modules in the target branch and the power supply bypass; generating current control information according to the switch position information and the cell position information of the target cell, so as to control the current of the target branch to flow into the bypass branch.

[0016] In some embodiments, there are multiple BIPV modules, and the control device stores multiple hot spot identification models and model feature information corresponding to each of the hot spot identification models; identifying whether the battery cell has a hot spot based on the difference information and the parameter change information corresponding to each of the battery cells includes: obtaining circuit structure information corresponding to each of the BIPV modules; performing feature extraction on the circuit structure information to obtain module feature information corresponding to each of the BIPV modules; matching the module feature information with multiple model feature information, and confirming the hot spot identification model corresponding to the successfully matched model feature information as the target hot spot model; inputting the difference information and the parameter change information into the target hot spot model, and the target hot spot model outputs the hot spot identification result corresponding to the battery cell, so as to determine whether the battery cell has a hot spot based on the hot spot identification result.

[0017] Exemplarily, before matching the module feature information with multiple model feature information, the method further includes: obtaining multiple hot spot recognition models to be trained; obtaining multiple historical hot spot recognition results and historical circuit structure information, historical difference information and historical parameter change information corresponding to the historical hot spot recognition results; wherein the historical hot spot recognition structure includes the presence of hot spots and the absence of hot spots, and the ratio of the number of historical hot spot recognition results with the presence of hot spots to the number of historical hot spot recognition results with the absence of hot spots is a preset ratio; generating training samples based on each of the historical hot spot recognition results and the corresponding historical difference information and historical parameter change information; completing the training of one of the hot spot recognition models based on each of the training samples, and generating the model feature information corresponding to the hot spot recognition model based on the historical circuit structure information corresponding to the training sample.

[0018] In some embodiments, identifying whether a hot spot exists on the cell based on the difference information corresponding to each of the cell and the parameter change information includes: acquiring the ambient temperature and ambient humidity corresponding to the hot spot phenomenon identification system of the photovoltaic curtain wall; generating a target hot spot index based on the ambient temperature and ambient humidity; calculating the hot spot index corresponding to the cell based on the temperature difference information, power difference information, temperature change information and power change information; if the hot spot index is greater than the target hot spot index, confirming that a hot spot exists on the cell.

[0019] Exemplarily, generating a target hot spot index according to the ambient temperature and ambient humidity includes: acquiring circuit structure information corresponding to the BIPV module; generating a basic hot spot index corresponding to the BIPV module according to the circuit structure information, wherein the basic hot spot index is a reference index of the BIPV module when it is not affected by the environment; generating a target hot spot index according to the basic hot spot index, ambient temperature and ambient humidity.

[0020] In some embodiments, generating a target hot spot index according to the basic hot spot index, ambient temperature and ambient humidity includes: determining a temperature type according to the ambient temperature, and obtaining a temperature influence coefficient according to the temperature type; the temperature type includes at least normal temperature, extremely high temperature and extremely low temperature; the temperature range corresponding to the extremely low temperature is smaller than the temperature range corresponding to the normal temperature, and the temperature range corresponding to the normal temperature is smaller than the temperature range corresponding to the extremely high temperature; determining a humidity type according to the ambient humidity, and obtaining a humidity influence coefficient according to the humidity type; the humidity type includes at least normal humidity, extremely high humidity and extremely low humidity; the humidity range corresponding to the extremely low humidity is smaller than the humidity range corresponding to the normal humidity, and the humidity range corresponding to the normal humidity is smaller than the humidity range corresponding to the extremely high humidity; generating a target hot spot index according to the basic hot spot index, ambient temperature, ambient humidity, temperature influence coefficient and humidity influence coefficient; the expression of the target hot spot index includes:

[0021] ;

[0022] in, is the target hot spot index, is the basic hot spot index, is the ambient temperature, is the ambient humidity, is the temperature influence coefficient corresponding to the ambient temperature, is the humidity influence coefficient corresponding to the ambient humidity.

[0023] Exemplarily, calculating the hot spot index corresponding to the battery cell based on the temperature difference information, power difference information, temperature change information and power change information includes: parsing the temperature difference information, power difference information, temperature change information and power change information, and obtaining the difference values ​​and standard deviations corresponding to the temperature difference information, power difference information, temperature change information and power change information; calculating the hot spot index based on the difference values ​​and standard deviations corresponding to the temperature difference information, power difference information, temperature change information and power change information.

[0024] It should be noted that, in some embodiments, the hot spot index is calculated according to the difference values ​​and standard deviations corresponding to the temperature difference information, power difference information, temperature change information, and power change information, including: respectively obtaining the temperature change information of the battery cell corresponding to the power change information of the battery cell within the preset range and the average temperature difference value and the average power difference value; calculating the hot spot index according to the average temperature difference value and the average power difference value and the difference values ​​and standard deviations corresponding to the temperature difference information, power difference information, temperature change information, and power change information; the expression of the hot spot index includes:

[0025] ;

[0026] in, For battery cells The corresponding hot spot index, is the difference value corresponding to the temperature difference information, is the standard deviation corresponding to the temperature difference information, is the difference value corresponding to the power difference information, is the standard deviation corresponding to the power difference information, is the difference value corresponding to the temperature change information, is the standard deviation corresponding to the temperature change information, is the difference value corresponding to the power change information, is the standard deviation corresponding to the power change information, is the average temperature difference value, is the average power difference value, , , and They are the weight coefficients corresponding to the temperature difference information, the power difference information, the temperature change information, and the power change information respectively.

[0027] In a third aspect, the present application provides a hot spot phenomenon identification device for a photovoltaic curtain wall, which is applied to a control device of a hot spot phenomenon identification system for a photovoltaic curtain wall as provided in any embodiment of the present application; the device comprises:

[0028] An information acquisition unit, used to acquire parameter information measured by each sensor module and cell position information of the corresponding cell;

[0029] A difference acquisition unit, configured to calculate difference information between each of the battery cells and battery cells within a preset range according to the battery cell position information and parameter information; the difference information at least includes temperature difference information and power difference information;

[0030] A change acquisition unit, used to acquire parameter change information of each of the battery cells within a preset time range according to the parameter information; the parameter change information at least includes temperature change information and power change information;

[0031] An identification completion unit is used to identify whether the cell has a hot spot based on the difference information and parameter change information corresponding to each of the cell, and complete the identification of the hot spot phenomenon of the photovoltaic curtain wall; determine the cell with the hot spot as the target cell; obtain the circuit connection information corresponding to the BIPV module; parse the circuit connection information to obtain multiple power supply branches and at least one power supply bypass corresponding to the BIPV module; each of the power supply branches includes multiple cell cells; determine the target branch corresponding to the target cell in the multiple power supply branches based on the cell position information corresponding to the target cell; generate current control information based on the cell position information of each cell corresponding to the target branch, so as to divert the current corresponding to the target branch to the power supply bypass among the multiple power supply branches.

[0032] In a fourth aspect, the present application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, enables the processor to implement the steps of the method for identifying hot spot phenomena of photovoltaic curtain walls according to the second aspect above.

[0033] The embodiment of the present application provides a method, system, device, equipment and medium for identifying the hot spot phenomenon of a photovoltaic curtain wall. The system can monitor the temperature and power and other parameter information of each cell in real time through a sensor module, and timely discover the hot spot phenomenon. Compared with the traditional method of regular manual inspection and the use of a thermal imager, it can identify the problem earlier and prevent the hot spot from causing irreversible damage to the photovoltaic module. The traditional hot spot detection method not only consumes a lot of manpower and material resources, but also has low efficiency and cannot achieve continuous monitoring. The system greatly improves the detection efficiency and reduces the time required for detection through automated monitoring means. The system can calculate the difference information based on the position information of each cell and the measured parameter information, and combine the parameter change information to identify whether there is a hot spot phenomenon. This method based on data analysis is more accurate than manual judgment and can effectively reduce the misjudgment rate. Although the installation of the recognition system may require a certain initial investment, in the long run, it can significantly reduce maintenance costs. Because the system can identify hot spot problems in a timely and accurate manner, maintenance personnel can repair or replace the components with problems in a targeted manner, avoiding the cost waste caused by comprehensive inspections. Hot spots not only cause physical damage to photovoltaic modules, but also affect their power generation efficiency. By timely and effectively identifying and dealing with hot spot phenomena, the normal operation of photovoltaic modules can be ensured and the power generation efficiency of the entire photovoltaic power generation system can be improved. The system is suitable for both newly built photovoltaic curtain wall projects and the renovation and upgrading of existing projects. This means that whether it is a new or old photovoltaic curtain wall, the current status of hot spot monitoring can be improved by installing this system, and the reliability and efficiency of the system can be improved.

[0034] In summary, this hot spot phenomenon identification system for photovoltaic curtain walls can not only effectively solve the current problems in hot spot monitoring, but also provide technical support for improving the safety, reliability and power generation efficiency of photovoltaic brackets.

[0035] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0037] Figure 1 This is a structural schematic diagram of a hot spot phenomenon identification system for a photovoltaic curtain wall provided in one embodiment of the present application;

[0038] Figure 2It is a structural schematic diagram of another hot spot phenomenon identification system for a photovoltaic curtain wall provided in an embodiment of the present application;

[0039] Figure 3 This is a schematic flow chart of the steps of a method for identifying hot spot phenomena of a photovoltaic curtain wall provided by an embodiment of the present application;

[0040] Figure 4 It is a structural schematic diagram of a hot spot phenomenon identification device for a photovoltaic curtain wall provided in one embodiment of the present application;

[0041] Figure 5 It is a schematic block diagram of the structure of a control device provided in one embodiment of the present application.

[0042] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0044] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0045] It should be understood that, in order to facilitate the clear description of the technical solutions of the embodiments of the present invention, in the embodiments of the present invention, the words "first", "second", etc. are used to distinguish the same items or similar items with substantially the same functions and effects. Those skilled in the art can understand that the words "first", "second", etc. do not limit the quantity and execution order, and the words "first", "second", etc. do not necessarily limit the difference.

[0046] It should be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0047] It should also be understood that the term “and / or” used in the specification and appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0048] In conjunction with the accompanying drawings, some embodiments of the present application are described in detail below. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0049] Photovoltaic curtain walls, as a building integrated system that converts solar energy into electrical energy, have been widely used in recent years. However, photovoltaic modules may encounter hot spot phenomena in actual operation, which has a serious impact on the performance and life of the modules. Hot spot phenomena are usually caused by partial obstruction or damage of the cells, which causes these cells to generate local high temperatures at high power output, thus affecting the efficiency of the entire module. Traditional hot spot detection methods mainly rely on manual inspections and thermal imagers, which are not only costly and inefficient, but also difficult to monitor in real time.

[0050] Therefore, a method for identifying hot spot phenomenon of photovoltaic curtain walls is urgently needed to solve at least one of the above problems.

[0051] To solve the above problems, please refer to Figure 1 and Figure 2 , Figure 1 It is a hot spot phenomenon identification system 10 for photovoltaic curtain walls provided by an embodiment of the present application. It includes: a BIPV module 1, the BIPV module 1 includes a plurality of cells, and the plurality of cells are connected in series and / or in parallel; a plurality of sensor modules 3, each of the sensor modules 3 corresponds to a cell, and is used to measure the parameter information corresponding to each cell; a control device 2, the control device 2 is electrically connected to each of the sensor modules 3, the control device 2 is used to obtain the parameter information measured by each sensor module 3 and the cell position information of the cell corresponding to each sensor module 3, the control device 2 calculates the difference information between each cell and the cells within a preset range according to the cell position information and parameter information; the difference information includes at least temperature difference information and power difference information, the control device 2 obtains the parameter change information of each cell within a preset time range according to the parameter information; the parameter change information includes at least temperature change information and power change information, the control device 2 identifies whether the cell has a hot spot according to the difference information corresponding to each cell and the parameter change information, so as to complete the hot spot phenomenon identification of the photovoltaic curtain wall.

[0052] Specifically, the hot spot phenomenon is a common problem in photovoltaic power generation systems, especially in building integrated photovoltaic (BIPV) applications. When parts of a photovoltaic module are blocked or the cells are damaged, these areas cannot perform normal photoelectric conversion, but instead become loads, absorbing energy from other normally working cells, causing the temperature of the area to rise sharply, forming hot spots. Long-term hot spots will not only reduce the power generation efficiency of photovoltaic modules, but may also cause permanent damage to the modules.

[0053] The system provided in the present application is composed of a plurality of cells through a BIPV module 1, and these cells can be connected in series or in parallel to form a part of a photovoltaic curtain wall. One or more sensor modules 3 are provided for each cell, and these sensor modules 3 can measure the working parameters of the cell, such as temperature, voltage, current, etc. The selection and arrangement of sensors are crucial to the accuracy and reliability of the hot spot detection system. At least one control device 2 (such as an MCU) is connected to all sensor modules 3, and can collect the measurement data of each cell and their specific location information. The control device 2 then calculates the difference between each cell and its surrounding cells based on these data, such as temperature difference and power difference, to identify whether there is a hot spot phenomenon. In addition to real-time parameter information, the system also analyzes the parameter change trend of each cell within a specific time range to more accurately determine whether the cell is in a hot spot state. This can also help identify problems such as performance degradation of the cell. Finally, the control device 2 determines which cells in the photovoltaic curtain wall have hot spot phenomena based on the above difference information and parameter change information. Once a hot spot is identified, the system can take timely measures, such as adjusting obstructions, replacing damaged cells, etc., to prevent the hot spot from causing further damage to the photovoltaic module.

[0054] At the same time Figure 1 and 2 , multiple BIPV modules 1 can be connected to one control device 2 respectively, or multiple BIPV modules 1 can be managed simultaneously by one control device 2. The embodiment of the present application does not limit this.

[0055] The realization of this system is of great significance for improving the operating efficiency of photovoltaic curtain walls and extending their service life. It not only overcomes the shortcomings of traditional manual inspections and the use of thermal imagers to detect hot spots, which are high cost, low efficiency, and difficulty in real-time monitoring, but also realizes effective management of the health status of photovoltaic curtain walls through automated and intelligent methods. This will play a positive role in promoting the development and widespread application of BIPV technology.

[0056] See also Figure 3 , Figure 3FIG. 1 is a schematic flow chart of a method for identifying hot spot phenomena of a photovoltaic curtain wall provided in an embodiment of the present application. The method for identifying hot spot phenomena of a photovoltaic curtain wall can be performed as follows: Figure 1 to Figure 2 According to any one of the embodiments of the present invention, the control device may be a micro control unit (MCU).

[0057] Specifically, Figure 3 As shown, the provided method for identifying hot spot phenomenon of photovoltaic curtain wall includes steps S101 to S104. The details are as follows:

[0058] Step S101: Obtain parameter information measured by each sensor module and cell position information of the corresponding cell.

[0059] Specifically, the parameter information (such as temperature, current, voltage, etc.) measured by each sensor module and the location information of the cell corresponding to each sensor module are obtained. These sensor modules can be small micro sensors installed inside or on the surface of the photovoltaic curtain wall assembly, which can monitor the working status of each cell in real time. By collecting detailed parameter information and location information, this step provides basic data support for subsequent analysis and processing, ensuring the accuracy and comprehensiveness of the detection. Compared with manual inspections, automated data collection reduces labor costs, improves detection efficiency, and avoids errors caused by human negligence.

[0060] Step S102: Calculate difference information between each of the battery cells and battery cells within a preset range according to the battery cell position information and parameter information; the difference information at least includes temperature difference information and power difference information.

[0061] Specifically, based on the cell position information and parameter information obtained in step S101, the difference information between each cell and other cells within a preset range is calculated. The difference information here mainly includes temperature difference and power difference, which is used to determine whether the cell is in an abnormal state. This step can effectively identify those cells with hot spots caused by obstruction or damage by comparing the parameter differences between adjacent cells or cells within a certain range. The detection of local abnormal parameters improves the detection rate of hot spot problems, facilitates early diagnosis and timely maintenance, and avoids further expansion of losses caused by hot spots.

[0062] Step S103: Obtain parameter change information of each of the battery cells within a preset time range according to the parameter information; the parameter change information at least includes temperature change information and power change information.

[0063] Specifically, according to the parameter information obtained in step S101, the parameter change information of each battery cell within the preset time range is obtained, including the temperature change trend over time and the power change trend over time, so as to understand the change of the working state of the battery cell in different time periods. This step can not only help identify the hot spot phenomenon that occurs immediately, but also discover potential hot spot trends or early signs by analyzing the data changes over a long period of time, which is conducive to preventive maintenance and improves the reliability and stability of the system.

[0064] Step S104: Identify whether the cell has a hot spot based on the difference information corresponding to each cell and the parameter change information, and complete the identification of the hot spot phenomenon of the photovoltaic curtain wall.

[0065] Specifically, by combining the difference information calculated in step S102 and the parameter change information obtained in step S103, it is possible to identify whether the cell has a hot spot phenomenon. This step may involve certain algorithms or models, such as machine learning models, which are used to determine whether a hot spot occurs based on the differences and change patterns. Figure 2 Determine whether a BIPV module has a shadow (such as Figure 2 The BIPV modules with shaded parts on the left are controlled to work at 70% efficiency, and the BIPV modules without shaded parts on the right are controlled to work at 95% efficiency). This step improves the accuracy and reliability of identifying hot spots through comprehensive analysis. At the same time, because it is based on automatically collected data and algorithm processing, it can realize real-time monitoring of hot spot phenomena on photovoltaic curtain walls, greatly enhancing the monitoring capability of the system, reducing maintenance costs, extending the service life of photovoltaic modules, and ensuring the efficient operation of the system.

[0066] In summary, the method provided forms an efficient and accurate photovoltaic curtain wall hot spot phenomenon identification system through four steps: automated data collection, local difference calculation, time series analysis and comprehensive identification. This not only solves the problems of high cost and low efficiency of traditional methods, but also realizes real-time monitoring of hot spot phenomena, which is of great significance for improving the safety, reliability and economic benefits of photovoltaic curtain walls.

[0067] In some embodiments, after completing the identification of the hot spot phenomenon of the photovoltaic curtain wall, it also includes: determining the cell with the hot spot as the target cell; obtaining the circuit connection information corresponding to the BIPV module; parsing the circuit connection information to obtain multiple power supply branches and at least one power supply bypass corresponding to the BIPV module; each of the power supply branches includes multiple cells; determining the target branch corresponding to the target cell among the multiple power supply branches according to the cell position information corresponding to the target cell; generating current control information according to the cell position information of each cell corresponding to the target branch, so as to divert the current corresponding to the target branch to the power supply bypass among the multiple power supply branches.

[0068] By isolating the cells with hot spots from the main power supply branch and diverting the current through the bypass branch, the high temperature of the hot spot cells can be prevented from spreading further, reducing safety hazards such as fire. By isolating the hot spot cells and diverting the current, the workload of these cells is reduced, which helps to extend their service life, thereby improving the reliability of the entire photovoltaic curtain wall system. Isolating the hot spot cells can prevent them from having a negative impact on the performance of the entire power supply branch, improving the overall power generation efficiency and stability of the system. This embodiment realizes automatic processing of hot spot cells through automated current control and isolation, reduces the need for manual intervention, and improves the efficiency and response speed of maintenance.

[0069] Exemplarily, the hot spot phenomenon identification system of the photovoltaic curtain wall also includes multiple switch modules, and the switch modules are arranged in the power supply branch and the power supply bypass; the current control information is generated according to the cell position information of each cell corresponding to the target branch, including: obtaining the switch position information corresponding to the switch modules in the target branch and the power supply bypass; generating current control information according to the switch position information and the cell position information of the target cell, so as to control the current of the target branch to flow into the bypass branch.

[0070] By setting the switch module and obtaining the switch position information, the current can be precisely controlled to ensure that the current of the target branch can accurately flow to the bypass branch. The automatic control of the switch module can respond quickly after the hot spot phenomenon is detected, avoiding the delay of manual operation and improving the response speed of the system. By diverting the current of the bypass branch, the energy loss caused by the failure of the hot spot battery cell can be reduced, and the overall power generation efficiency of the system can be improved. The use of the switch module makes the system more flexible, and the current path can be dynamically adjusted according to the actual situation to adapt to different operating conditions and maintenance requirements.

[0071] In summary, the above embodiments and their corresponding examples further improve the functions and performance of the photovoltaic curtain wall hot spot phenomenon identification system by introducing switch modules and current control technology. They not only improve the safety, reliability and power generation efficiency of the system, but also realize automated maintenance and optimization, greatly reducing the operation and maintenance costs. These technical contents and beneficial effects make the system more suitable for large-scale photovoltaic curtain wall projects and have broad application prospects.

[0072] In some embodiments, there are multiple BIPV modules, and the control device stores multiple hot spot identification models and model feature information corresponding to each of the hot spot identification models; identifying whether the battery cell has a hot spot based on the difference information and the parameter change information corresponding to each of the battery cells includes: obtaining circuit structure information corresponding to each of the BIPV modules; performing feature extraction on the circuit structure information to obtain module feature information corresponding to each of the BIPV modules; matching the module feature information with multiple model feature information, and confirming the hot spot identification model corresponding to the successfully matched model feature information as the target hot spot model; inputting the difference information and the parameter change information into the target hot spot model, and the target hot spot model outputs the hot spot identification result corresponding to the battery cell, so as to determine whether the battery cell has a hot spot based on the hot spot identification result.

[0073] By making the number of BIPV modules in the photovoltaic curtain wall multiple. The control device stores multiple hot spot identification models, each model corresponds to specific model feature information. Obtain the circuit structure information of each BIPV module. Perform feature extraction on the circuit structure information to obtain the module feature information of each BIPV module. Match the module feature information with the stored multiple model feature information, and confirm the hot spot identification model corresponding to the successfully matched model feature information as the target hot spot model. Input the difference information and parameter change information of each battery cell into the target hot spot model, and the model outputs the hot spot identification result to determine whether there is a hot spot on the battery cell.

[0074] Furthermore, by using multiple hot spot identification models and matching the most appropriate model according to the circuit structure information of each BIPV module, the accuracy of hot spot identification can be significantly improved. Different BIPV modules may have different circuit structures and operating conditions. The multi-model matching method can adapt to these differences and improve the versatility and flexibility of the system. Since each model is optimized for a specific circuit structure, it can better identify hot spot phenomena and reduce false alarms and missed alarms. This method realizes real-time monitoring and hot spot identification of multiple BIPV modules, can promptly detect and deal with hot spot problems, and improve the safety of the system.

[0075] Exemplarily, before matching the module feature information with multiple model feature information, the method further includes: obtaining multiple hot spot recognition models to be trained; obtaining multiple historical hot spot recognition results and historical circuit structure information, historical difference information and historical parameter change information corresponding to the historical hot spot recognition results; wherein the historical hot spot recognition structure includes the presence of hot spots and the absence of hot spots, and the ratio of the number of historical hot spot recognition results with the presence of hot spots to the number of historical hot spot recognition results with the absence of hot spots is a preset ratio; generating training samples based on each of the historical hot spot recognition results and the corresponding historical difference information and historical parameter change information; completing the training of one of the hot spot recognition models based on each of the training samples, and generating the model feature information corresponding to the hot spot recognition model based on the historical circuit structure information corresponding to the training sample.

[0076] By training multiple hot spot recognition models, each model can better adapt to specific circuit structures and working conditions, thereby improving recognition accuracy. The preset ratio ensures that the data ratio of hot spots and non-hot spots in the training samples is balanced, avoiding recognition bias caused by data imbalance. The model training process can be adjusted according to actual historical data, so that the recognition model is more in line with the actual operating conditions and improves the adaptability of the system. As new data continues to accumulate, the model can continue to be trained and optimized, making the system more scalable and long-term effective. The automated model training and feature generation process reduces the reliance on manually labeled data, reduces maintenance costs, and improves the automation of the system.

[0077] The above embodiments and examples thereof not only improve the accuracy and reliability of hot spot recognition, but also enhance the adaptability and flexibility of the system through multi-model matching and model training. Specifically, the multi-model matching method can select the most appropriate recognition model according to different circuit structures to reduce false positives and false negatives; and the model training process further improves the adaptability and scalability of the model through the optimization of historical data. These technical contents and beneficial effects make the hot spot phenomenon recognition system of photovoltaic curtain walls more suitable for complex and changeable practical application scenarios, and improve the overall performance and reliability of the system.

[0078] In some embodiments, identifying whether a hot spot exists on the cell based on the difference information corresponding to each of the cell and the parameter change information includes: acquiring the ambient temperature and ambient humidity corresponding to the hot spot phenomenon identification system of the photovoltaic curtain wall; generating a target hot spot index based on the ambient temperature and ambient humidity; calculating the hot spot index corresponding to the cell based on the temperature difference information, power difference information, temperature change information and power change information; if the hot spot index is greater than the target hot spot index, confirming that a hot spot exists on the cell.

[0079] By introducing environmental parameters (temperature and humidity), the hot spot phenomenon of the cell can be judged more accurately. Changes in ambient temperature and humidity can affect the working state of the cell, so considering these parameters can reduce misjudgments. The generation of the target hot spot index takes environmental factors into account, so the method can adapt to different environmental conditions and improve the versatility and flexibility of the system. By calculating the hot spot index of the cell and comparing it with the target hot spot index in real time, early warning of the hot spot phenomenon can be achieved, which helps to take maintenance measures in time to prevent the hot spot problem from further deteriorating. Accurate hot spot identification can avoid unnecessary maintenance operations, thereby reducing maintenance costs.

[0080] Exemplarily, generating a target hot spot index according to the ambient temperature and ambient humidity includes: acquiring circuit structure information corresponding to the BIPV module; generating a basic hot spot index corresponding to the BIPV module according to the circuit structure information, wherein the basic hot spot index is a reference index of the BIPV module when it is not affected by the environment; generating a target hot spot index according to the basic hot spot index, ambient temperature and ambient humidity.

[0081] The generation of the basic hot spot index takes into account the circuit structure of each BIPV module, so each module has a personalized reference value, which improves the accuracy and reliability of recognition. The generation of the target hot spot index takes into account the real-time ambient temperature and humidity, and can dynamically adjust the threshold according to environmental changes to avoid misjudgments caused by environmental factors. The combination of the basic hot spot index and environmental parameters provides comprehensive data support, which helps to more comprehensively evaluate the working status of the battery cells. By dynamically adjusting the target hot spot index, a high level of recognition accuracy can be maintained under different environmental conditions, reducing false alarms and missed alarms. The automated index generation process improves the intelligence level of the system, reduces the need for manual intervention, and improves the system's degree of automation and operating efficiency.

[0082] The above-mentioned embodiments and their corresponding examples further optimize the identification method of the hot spot phenomenon of photovoltaic curtain walls by introducing environmental parameters and dynamically generating a target hot spot index. Specifically: the introduction of environmental parameters makes hot spot identification more accurate and reliable, and can adapt to different environmental conditions. A reference hot spot index for each BIPV module is generated based on circuit structure information, providing a personalized and accurate reference value. By combining the basic hot spot index and real-time environmental parameters to generate a target hot spot index, dynamic adjustment of the identification threshold is achieved, further improving the adaptability and accuracy of the system. Not only does it improve the accuracy of hot spot identification, it also makes the operation and maintenance of photovoltaic curtain walls more efficient and intelligent, helping to ensure the safety and economy of the system.

[0083] In some embodiments, generating a target hot spot index according to the basic hot spot index, ambient temperature and ambient humidity includes: determining a temperature type according to the ambient temperature, and obtaining a temperature influence coefficient according to the temperature type; the temperature type includes at least normal temperature, extremely high temperature and extremely low temperature; the temperature range corresponding to the extremely low temperature is smaller than the temperature range corresponding to the normal temperature, and the temperature range corresponding to the normal temperature is smaller than the temperature range corresponding to the extremely high temperature; determining a humidity type according to the ambient humidity, and obtaining a humidity influence coefficient according to the humidity type; the humidity type includes at least normal humidity, extremely high humidity and extremely low humidity; the humidity range corresponding to the extremely low humidity is smaller than the humidity range corresponding to the normal humidity, and the humidity range corresponding to the normal humidity is smaller than the humidity range corresponding to the extremely high humidity; generating a target hot spot index according to the basic hot spot index, ambient temperature, ambient humidity, temperature influence coefficient and humidity influence coefficient; the expression of the target hot spot index includes:

[0084] ;

[0085] in, is the target hot spot index, is the basic hot spot index, is the ambient temperature, is the ambient humidity, is the temperature influence coefficient corresponding to the ambient temperature, is the humidity influence coefficient corresponding to the ambient humidity.

[0086] By classifying the ambient temperature and humidity, the influence coefficients under different environmental conditions are obtained, so that the target hot spot index can better adapt to different environmental conditions. High temperature or high humidity environment will cause changes in the working state of the battery cell. The introduction of temperature and humidity influence coefficients can more accurately evaluate the impact of these changes on the hot spot phenomenon. For example, [-20,0℃] is the temperature range corresponding to extremely low temperature, (0,50℃) is the temperature range corresponding to normal temperature, and [50,200℃) is the temperature range corresponding to extremely high temperature. The ranges corresponding to extremely low humidity, normal humidity and extremely high humidity can be set according to actual needs and the size relationship corresponding to the above temperature ranges. The embodiment of the present application does not limit the numerical value of the specific range. The dynamically generated target hot spot index can more accurately reflect the threshold standard in the current environment, thereby reducing false alarms and missed alarms caused by environmental changes. For example, in an extremely high temperature environment, the target hot spot index will be appropriately adjusted to avoid the normal temperature rise caused by high temperature from being misjudged as a hot spot. The hot spot index generation method that takes environmental factors into account enables the system to reliably identify hot spot phenomena under various environmental conditions, thereby improving the overall reliability of the system. It helps to find and deal with hot spot problems in time, preventing system failures and potential safety hazards. The dynamically adjusted threshold standard can be flexibly adjusted according to actual conditions, optimizing system performance and improving power generation efficiency and stability.

[0087] Exemplarily, calculating the hot spot index corresponding to the battery cell based on the temperature difference information, power difference information, temperature change information and power change information includes: parsing the temperature difference information, power difference information, temperature change information and power change information, and obtaining the difference values ​​and standard deviations corresponding to the temperature difference information, power difference information, temperature change information and power change information; calculating the hot spot index based on the difference values ​​and standard deviations corresponding to the temperature difference information, power difference information, temperature change information and power change information.

[0088] By comprehensively considering various information such as temperature difference, power difference, temperature change and power change, the hot spot phenomenon of the battery cell can be evaluated more comprehensively and the accuracy of identification can be improved. Different types of information have different impacts. By introducing difference values ​​and standard deviations, the contribution of these information can be better balanced. The introduction of the use of standard deviation makes the calculation results more stable, which can reflect the discreteness of the data and further improve the reliability of identification. By parsing a variety of difference information, the impact of local abnormal data on the hot spot index can be reduced to avoid misjudgment. This method realizes real-time monitoring of battery cells and dynamic calculation of hot spot index, which helps to timely discover and deal with hot spot problems and improve the response speed of the system. The dynamically calculated hot spot index can reflect the current status of the battery cell in real time and realize more precise monitoring.

[0089] It should be noted that, in some embodiments, the hot spot index is calculated according to the difference values ​​and standard deviations corresponding to the temperature difference information, power difference information, temperature change information, and power change information, including: respectively obtaining the temperature change information of the battery cell corresponding to the power change information of the battery cell within the preset range and the average temperature difference value and the average power difference value; calculating the hot spot index according to the average temperature difference value and the average power difference value and the difference values ​​and standard deviations corresponding to the temperature difference information, power difference information, temperature change information, and power change information; the expression of the hot spot index includes:

[0090] ;

[0091] in, For battery cells The corresponding hot spot index, is the difference value corresponding to the temperature difference information, is the standard deviation corresponding to the temperature difference information, is the difference value corresponding to the power difference information, is the standard deviation corresponding to the power difference information, is the difference value corresponding to the temperature change information, is the standard deviation corresponding to the temperature change information, is the difference value corresponding to the power change information, is the standard deviation corresponding to the power change information, is the average temperature difference value, is the average power difference value, , , and They are the weight coefficients corresponding to the temperature difference information, the power difference information, the temperature change information, and the power change information respectively.

[0092] By comprehensively considering various information such as temperature difference, power difference, temperature change and power change, as well as their average difference value and standard deviation, the hot spot phenomenon of the battery cell can be more comprehensively evaluated and the accuracy of recognition can be improved. The introduction of the average difference value can reduce the impact of local abnormal data on the overall evaluation, making the results more stable and reliable. The introduction of the use of the standard deviation makes the calculation results more stable, which can reflect the discreteness of the data and further improve the reliability of recognition. By analyzing multiple difference information and average difference values, the possibility of misjudgment and false alarm can be reduced.

[0093] This method realizes real-time monitoring of the battery cell and dynamic calculation of the hot spot index, which helps to timely discover and deal with hot spot problems and improve the response speed of the system. The dynamically calculated hot spot index can reflect the current status of the battery cell in real time and realize more precise monitoring. Through automatic analysis and calculation of the hot spot index, the intelligence level of the system is improved and the need for manual intervention is reduced. The optimized calculation method enables the system to better adapt to different environments and working conditions, and improves the overall automated operation and maintenance capabilities.

[0094] The above-mentioned embodiments and their corresponding examples of extensions further improve the identification system of the hot spot phenomenon of the photovoltaic curtain wall by introducing the influence coefficient of ambient temperature and humidity, as well as the multi-dimensional calculation method of the hot spot index of the battery cell. Specifically: the generation method of the target hot spot index takes into account the influence of ambient temperature and humidity, so that the system can better adapt to different environmental conditions. The calculation method of the hot spot index of the battery cell comprehensively considers various information such as temperature difference, power difference, temperature change and power change, as well as their difference value, standard deviation and average difference value, which improves the comprehensiveness and accuracy of the evaluation. Through the dynamically generated target hot spot index and the multi-dimensional calculation of the hot spot index of the battery cell, the possibility of misjudgment and false alarm is reduced, and the reliability of the system is improved. The automated method realizes real-time monitoring and dynamic calculation of the hot spot phenomenon, improves the response speed and intelligence level of the system, and makes the operation and maintenance of the photovoltaic curtain wall more efficient and intelligent. These technical contents and beneficial effects make the hot spot identification system of the photovoltaic curtain wall more suitable for complex and changeable practical application scenarios, and improve the overall performance and reliability of the system.

[0095] See also Figure 4 As shown, Figure 4 : is a schematic diagram of the structure of the hot spot phenomenon identification device 200 for photovoltaic curtain walls provided in an embodiment of the present application. The hot spot phenomenon identification device 200 for photovoltaic curtain walls is used to execute the steps of the hot spot phenomenon identification method for photovoltaic curtain walls shown in the above embodiments. The hot spot phenomenon identification device 200 for photovoltaic curtain walls can be a single server or a server cluster, or the hot spot phenomenon identification device 200 for photovoltaic curtain walls can be a terminal, which can be a handheld terminal, a laptop computer, a wearable device or a robot, etc.

[0096] like Figure 4 As shown, the hot spot phenomenon identification device 200 for photovoltaic curtain walls includes:

[0097] The information acquisition unit 201 is used to acquire the parameter information measured by each sensor module and the cell position information of the corresponding cell;

[0098] A difference acquisition unit 202 is used to calculate difference information between each of the battery cells and the battery cells within a preset range according to the battery cell position information and parameter information; the difference information at least includes temperature difference information and power difference information;

[0099] A change acquisition unit 203 is used to acquire parameter change information of each of the battery cells within a preset time range according to the parameter information; the parameter change information at least includes temperature change information and power change information;

[0100] The identification completion unit 204 is used to identify whether the cell has a hot spot based on the difference information and the parameter change information corresponding to each of the cell, and complete the identification of the hot spot phenomenon of the photovoltaic curtain wall; determine the cell with the hot spot as the target cell; obtain the circuit connection information corresponding to the BIPV module; parse the circuit connection information to obtain multiple power supply branches and at least one power supply bypass corresponding to the BIPV module; each of the power supply branches includes multiple cell cells; determine the target branch corresponding to the target cell in the multiple power supply branches based on the cell position information corresponding to the target cell; generate current control information based on the cell position information of each cell corresponding to the target branch, so as to divert the current corresponding to the target branch to the power supply bypass among the multiple power supply branches.

[0101] It should be noted that technical personnel in the relevant field can clearly understand that, for the convenience and conciseness of description, the specific working processes of the hot spot phenomenon identification device and each module of the photovoltaic curtain wall described above can refer to the corresponding processes in the hot spot phenomenon identification method embodiments of the photovoltaic curtain wall described in the above embodiments, and will not be repeated here.

[0102] The above-mentioned method for identifying hot spot phenomenon of photovoltaic curtain wall can be implemented in the form of a computer program. The computer program can be used in Figure 4 Run on the device shown.

[0103] See also Figure 5 , Figure 5 : is a schematic block diagram of the structure of a control device provided in an embodiment of the present application. The control device includes a processor, a memory and a network interface connected via a device bus, wherein the memory may include a storage medium and an internal memory.

[0104] The storage medium can store an operating device and a computer program. The computer program includes program instructions, and when the program instructions are executed, the processor can execute any method for identifying hot spot phenomena of photovoltaic curtain walls.

[0105] The processor is used to provide computing and control capabilities to support the operation of the entire control device.

[0106] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor, the processor can execute any method for identifying hot spot phenomena of photovoltaic curtain walls.

[0107] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the terminal to which the scheme of the present application is applied. The specific control device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0108] It should be understood that the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0109] In one embodiment, the processor is used to run a computer program stored in the memory to implement the following steps:

[0110] Obtaining parameter information measured by each sensor module and cell position information of the corresponding cell;

[0111] Calculate the difference information between each of the battery cells and the battery cells within a preset range according to the battery cell position information and parameter information; the difference information includes at least temperature difference information and power difference information;

[0112] Acquire parameter change information of each of the battery cells within a preset time range according to the parameter information; the parameter change information at least includes temperature change information and power change information;

[0113] According to the difference information corresponding to each of the cells and the parameter change information, it is identified whether the cell has a hot spot, thereby completing the identification of the hot spot phenomenon of the photovoltaic curtain wall.

[0114] In some embodiments, after completing the identification of the hot spot phenomenon of the photovoltaic curtain wall, it also includes: determining the cell with the hot spot as the target cell; obtaining the circuit connection information corresponding to the BIPV module; parsing the circuit connection information to obtain multiple power supply branches and at least one power supply bypass corresponding to the BIPV module; each of the power supply branches includes multiple cells; determining the target branch corresponding to the target cell among the multiple power supply branches according to the cell position information corresponding to the target cell; generating current control information according to the cell position information of each cell corresponding to the target branch, so as to divert the current corresponding to the target branch to the power supply bypass among the multiple power supply branches.

[0115] Exemplarily, the hot spot phenomenon identification system of the photovoltaic curtain wall also includes multiple switch modules, and the switch modules are arranged in the power supply branch and the power supply bypass; the current control information is generated according to the cell position information of each cell corresponding to the target branch, including: obtaining the switch position information corresponding to the switch modules in the target branch and the power supply bypass; generating current control information according to the switch position information and the cell position information of the target cell, so as to control the current of the target branch to flow into the bypass branch.

[0116] In some embodiments, there are multiple BIPV modules, and the control device stores multiple hot spot identification models and model feature information corresponding to each of the hot spot identification models; identifying whether the battery cell has a hot spot based on the difference information and the parameter change information corresponding to each of the battery cells includes: obtaining circuit structure information corresponding to each of the BIPV modules; performing feature extraction on the circuit structure information to obtain module feature information corresponding to each of the BIPV modules; matching the module feature information with multiple model feature information, and confirming the hot spot identification model corresponding to the successfully matched model feature information as the target hot spot model; inputting the difference information and the parameter change information into the target hot spot model, and the target hot spot model outputs the hot spot identification result corresponding to the battery cell, so as to determine whether the battery cell has a hot spot based on the hot spot identification result.

[0117] Exemplarily, before matching the module feature information with multiple model feature information, the method further includes: obtaining multiple hot spot recognition models to be trained; obtaining multiple historical hot spot recognition results and historical circuit structure information, historical difference information and historical parameter change information corresponding to the historical hot spot recognition results; wherein the historical hot spot recognition structure includes the presence of hot spots and the absence of hot spots, and the ratio of the number of historical hot spot recognition results with the presence of hot spots to the number of historical hot spot recognition results with the absence of hot spots is a preset ratio; generating training samples based on each of the historical hot spot recognition results and the corresponding historical difference information and historical parameter change information; completing the training of one of the hot spot recognition models based on each of the training samples, and generating the model feature information corresponding to the hot spot recognition model based on the historical circuit structure information corresponding to the training sample.

[0118] In some embodiments, identifying whether a hot spot exists on the cell based on the difference information corresponding to each of the cell and the parameter change information includes: acquiring the ambient temperature and ambient humidity corresponding to the hot spot phenomenon identification system of the photovoltaic curtain wall; generating a target hot spot index based on the ambient temperature and ambient humidity; calculating the hot spot index corresponding to the cell based on the temperature difference information, power difference information, temperature change information and power change information; if the hot spot index is greater than the target hot spot index, confirming that a hot spot exists on the cell.

[0119] Exemplarily, generating a target hot spot index according to the ambient temperature and ambient humidity includes: acquiring circuit structure information corresponding to the BIPV module; generating a basic hot spot index corresponding to the BIPV module according to the circuit structure information, wherein the basic hot spot index is a reference index of the BIPV module when it is not affected by the environment; generating a target hot spot index according to the basic hot spot index, ambient temperature and ambient humidity.

[0120] In some embodiments, generating a target hot spot index according to the basic hot spot index, ambient temperature and ambient humidity includes: determining a temperature type according to the ambient temperature, and obtaining a temperature influence coefficient according to the temperature type; the temperature type includes at least normal temperature, extremely high temperature and extremely low temperature; the temperature range corresponding to the extremely low temperature is smaller than the temperature range corresponding to the normal temperature, and the temperature range corresponding to the normal temperature is smaller than the temperature range corresponding to the extremely high temperature; determining a humidity type according to the ambient humidity, and obtaining a humidity influence coefficient according to the humidity type; the humidity type includes at least normal humidity, extremely high humidity and extremely low humidity; the humidity range corresponding to the extremely low humidity is smaller than the humidity range corresponding to the normal humidity, and the humidity range corresponding to the normal humidity is smaller than the humidity range corresponding to the extremely high humidity; generating a target hot spot index according to the basic hot spot index, ambient temperature, ambient humidity, temperature influence coefficient and humidity influence coefficient; the expression of the target hot spot index includes:

[0121] ;

[0122] in, is the target hot spot index, is the basic hot spot index, is the ambient temperature, is the ambient humidity, is the temperature influence coefficient corresponding to the ambient temperature, is the humidity influence coefficient corresponding to the ambient humidity.

[0123] Exemplarily, calculating the hot spot index corresponding to the battery cell based on the temperature difference information, power difference information, temperature change information and power change information includes: parsing the temperature difference information, power difference information, temperature change information and power change information, and obtaining the difference values ​​and standard deviations corresponding to the temperature difference information, power difference information, temperature change information and power change information; calculating the hot spot index based on the difference values ​​and standard deviations corresponding to the temperature difference information, power difference information, temperature change information and power change information.

[0124] It should be noted that, in some embodiments, the hot spot index is calculated according to the difference values ​​and standard deviations corresponding to the temperature difference information, power difference information, temperature change information, and power change information, including: respectively obtaining the temperature change information of the battery cell corresponding to the power change information of the battery cell within the preset range and the average temperature difference value and the average power difference value; calculating the hot spot index according to the average temperature difference value and the average power difference value and the difference values ​​and standard deviations corresponding to the temperature difference information, power difference information, temperature change information, and power change information; the expression of the hot spot index includes:

[0125] ;

[0126] in, For battery cells The corresponding hot spot index, is the difference value corresponding to the temperature difference information, is the standard deviation corresponding to the temperature difference information, is the difference value corresponding to the power difference information, is the standard deviation corresponding to the power difference information, is the difference value corresponding to the temperature change information, is the standard deviation corresponding to the temperature change information, is the difference value corresponding to the power change information, is the standard deviation corresponding to the power change information, is the average temperature difference value, is the average power difference value, , , and They are the weight coefficients corresponding to the temperature difference information, the power difference information, the temperature change information, and the power change information respectively.

[0127] The present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the processor implements the steps of the method for identifying hot spot phenomena of photovoltaic curtain walls as described in the first aspect above.

[0128] The computer-readable storage medium may be an internal storage unit of the control device described in the foregoing embodiment, such as a hard disk or memory of the control device. The computer-readable storage medium may also be an external storage device of the control device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc., equipped on the control device.

[0129] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A hot spot phenomenon recognition system for photovoltaic curtain walls, characterized in that: include: A BIPV module, wherein the BIPV module comprises a plurality of solar cells, wherein the plurality of solar cells are connected in series and / or in parallel; A plurality of sensor modules, each of which corresponds to one of the battery cells and is used to measure parameter information corresponding to each of the battery cells; A control device, the control device is electrically connected to each of the sensing modules, the control device is used to obtain parameter information measured by each sensing module and cell position information of the corresponding cell, the control device calculates difference information between each of the cells and cells within a preset range based on the cell position information and parameter information; the difference information at least includes temperature difference information and power difference information, the control device obtains parameter change information of each cell within a preset time range based on the parameter information; the parameter change information at least includes temperature change information and power change information, the control device identifies whether there is a hot spot on the cell based on the difference information and parameter change information corresponding to each cell, including: obtaining the ambient temperature and ambient humidity corresponding to the hot spot phenomenon identification system of the photovoltaic curtain wall; generating a target hot spot index based on the ambient temperature and ambient humidity; and The method comprises: calculating the hot spot index corresponding to the battery cell according to the temperature difference information, power difference information, temperature change information and power change information, including: parsing the temperature difference information, power difference information, temperature change information and power change information, and obtaining the difference value and standard deviation corresponding to the temperature difference information, power difference information, temperature change information and power change information; calculating the hot spot index according to the difference value and standard deviation corresponding to the temperature difference information, power difference information, temperature change information and power change information, including: respectively obtaining the temperature average difference value and power average difference value corresponding to the temperature change information and power change information of the battery cell within the preset range; calculating the hot spot index according to the temperature average difference value and power average difference value and the difference value and standard deviation corresponding to the temperature difference information, power difference information, temperature change information and power change information; the expression of the hot spot index comprises: ; in, For battery cells The corresponding hot spot index, is the difference value corresponding to the temperature difference information, is the standard deviation corresponding to the temperature difference information, is the difference value corresponding to the power difference information, is the standard deviation corresponding to the power difference information, is the difference value corresponding to the temperature change information, is the standard deviation corresponding to the temperature change information, is the difference value corresponding to the power change information, is the standard deviation corresponding to the power change information, is the average temperature difference value, is the average power difference value, , , and They are respectively the weight coefficients corresponding to the temperature difference information, the power difference information, the temperature change information, and the power change information; if the hot spot index is greater than the target hot spot index, it is confirmed that the cell has a hot spot; so as to complete the identification of the hot spot phenomenon of the photovoltaic curtain wall; the cell with the hot spot is determined as the target cell; the circuit connection information corresponding to the BIPV module is obtained; the circuit connection information is parsed to obtain multiple power supply branches and at least one power supply bypass corresponding to the BIPV module; each of the power supply branches includes multiple cells; according to the cell position information corresponding to the target cell, the target branch corresponding to the target cell is determined in the multiple power supply branches; according to the cell position information of each cell corresponding to the target branch, the current control information is generated to divert the current corresponding to the target branch to the power supply bypass in the multiple power supply branches.

2. A method for identifying hot spot phenomenon of photovoltaic curtain wall, characterized in that: A control device for a hot spot phenomenon identification system for a photovoltaic curtain wall as claimed in claim 1; the method comprising: Obtaining parameter information measured by each sensor module and cell position information of the corresponding cell; Calculate the difference information between each of the battery cells and the battery cells within a preset range according to the battery cell position information and parameter information; the difference information includes at least temperature difference information and power difference information; Acquire parameter change information of each of the battery cells within a preset time range according to the parameter information; the parameter change information at least includes temperature change information and power change information; Identify whether the cell has a hot spot according to the difference information and the parameter change information corresponding to each cell, including: obtaining the ambient temperature and ambient humidity corresponding to the hot spot phenomenon identification system of the photovoltaic curtain wall; generating a target hot spot index according to the ambient temperature and ambient humidity; calculating the hot spot index corresponding to the cell according to the temperature difference information, power difference information, temperature change information and power change information, including: parsing the temperature difference information, power difference information, temperature change information and power change information, and obtaining the difference value and standard deviation corresponding to the temperature difference information, power difference information, temperature change information and power change information; calculating the hot spot index according to the difference value and standard deviation corresponding to the temperature difference information, power difference information, temperature change information and power change information, including: respectively obtaining the temperature change information and power change information corresponding to the cell within the preset range of the cell The average temperature difference value and the average power difference value; calculating the hot spot index according to the temperature average difference value and the power average difference value and the difference value and standard deviation corresponding to the temperature difference information, power difference information, temperature change information, and power change information; the expression of the hot spot index includes: ; in, For battery cells The corresponding hot spot index, is the difference value corresponding to the temperature difference information, is the standard deviation corresponding to the temperature difference information, is the difference value corresponding to the power difference information, is the standard deviation corresponding to the power difference information, is the difference value corresponding to the temperature change information, is the standard deviation corresponding to the temperature change information, is the difference value corresponding to the power change information, is the standard deviation corresponding to the power change information, is the average temperature difference value, is the average power difference value, , , and They are weight coefficients corresponding to temperature difference information, power difference information, temperature change information, and power change information respectively; if the hot spot index is greater than the target hot spot index, it is confirmed that a hot spot exists in the cell; the hot spot phenomenon of the photovoltaic curtain wall is identified; the cell with a hot spot is determined as the target cell; the circuit connection information corresponding to the BIPV module is obtained; the circuit connection information is parsed to obtain multiple power supply branches and at least one power supply bypass corresponding to the BIPV module; each of the power supply branches includes multiple cells; the target branch corresponding to the target cell is determined in the multiple power supply branches according to the cell position information corresponding to the target cell; current control information is generated according to the cell position information of each cell corresponding to the target branch, so as to divert the current corresponding to the target branch to the power supply bypass in the multiple power supply branches.

3. The method according to claim 2, characterized in that The hot spot phenomenon identification system of the photovoltaic curtain wall further includes a plurality of switch modules, and the switch modules are arranged in the power supply branch and the power supply bypass; The generating current control information according to the battery cell position information of each battery cell corresponding to the target branch includes: Obtaining switch position information corresponding to the switch modules in the target branch and the power supply bypass; Current control information is generated according to the switch position information and the cell position information of the target cell, so as to control the current of the target branch to flow into the power supply bypass.

4. The method according to claim 2, characterized in that: The number of the BIPV modules is multiple, and the control device stores multiple hot spot recognition models and model feature information corresponding to each hot spot recognition model; The step of identifying whether a hot spot exists in the battery cell according to the difference information corresponding to each battery cell and the parameter change information includes: Obtaining circuit structure information corresponding to each of the BIPV modules; Performing feature extraction on the circuit structure information to obtain module feature information corresponding to each of the BIPV modules; Matching is performed according to the module feature information and a plurality of model feature information, and the hot spot recognition model corresponding to the successfully matched model feature information is confirmed as a target hot spot model; The difference information and the parameter change information are input into the target hot spot model, and the target hot spot model outputs a hot spot identification result corresponding to the battery cell, so as to determine whether the battery cell has a hot spot according to the hot spot identification result.

5. The method according to claim 4, characterized in that Before matching according to the module feature information and the plurality of model feature information, the method further includes: Obtain multiple hot spot recognition models to be trained; Acquire multiple historical hot spot identification results and historical circuit structure information, historical difference information, and historical parameter change information corresponding to the historical hot spot identification results; wherein the historical hot spot identification results include hot spots with presence and hot spots without presence, and the ratio of the number of historical hot spot identification results with hot spots with presence to the number of historical hot spot identification results with no hot spots with presence is a preset ratio; Generate a training sample according to each of the historical hot spot identification results and the corresponding historical difference information and historical parameter change information; The training of a hot spot recognition model is completed according to each of the training samples, and the model feature information corresponding to the hot spot recognition model is generated according to the historical circuit structure information corresponding to the training samples.

6. The method according to claim 2, characterized in that The generating a target hot spot index according to the ambient temperature and ambient humidity comprises: Obtaining circuit structure information corresponding to the BIPV module; Generate a basic hot spot index corresponding to the BIPV module according to the circuit structure information, wherein the basic hot spot index is a reference index of the BIPV module that is not affected by the environment; A target hot spot index is generated according to the basic hot spot index, ambient temperature and ambient humidity.

7. The method according to claim 6, characterized in that Generating a target hot spot index according to the basic hot spot index, ambient temperature and ambient humidity includes: Determine the temperature type according to the ambient temperature, and obtain the temperature influence coefficient according to the temperature type; the temperature type includes at least normal temperature, extremely high temperature and extremely low temperature; the temperature range corresponding to the extremely low temperature is smaller than the temperature range corresponding to the normal temperature, and the temperature range corresponding to the normal temperature is smaller than the temperature range corresponding to the extremely high temperature; Determine the humidity type according to the ambient humidity, and obtain the humidity influence coefficient according to the humidity type; the humidity type includes at least normal humidity, extremely high humidity and extremely low humidity; the humidity range corresponding to the extremely low humidity is smaller than the humidity range corresponding to the normal humidity, and the humidity range corresponding to the normal humidity is smaller than the humidity range corresponding to the extremely high humidity; A target hot spot index is generated according to the basic hot spot index, ambient temperature, ambient humidity, temperature influence coefficient and humidity influence coefficient; the expression of the target hot spot index includes: ； in, is the target hot spot index, is the basic hot spot index, is the ambient temperature, is the ambient humidity, is the temperature influence coefficient corresponding to the ambient temperature, is the humidity influence coefficient corresponding to the ambient humidity.

8. A hot spot phenomenon identification device for photovoltaic curtain walls, characterized in that: A control device for a hot spot phenomenon identification system for a photovoltaic curtain wall as claimed in claim 1; the device comprises: An information acquisition unit, used to acquire parameter information measured by each sensor module and cell position information of the corresponding cell; A difference acquisition unit, configured to calculate difference information between each of the battery cells and battery cells within a preset range according to the battery cell position information and parameter information; the difference information at least includes temperature difference information and power difference information; A change acquisition unit, used to acquire parameter change information of each of the battery cells within a preset time range according to the parameter information; the parameter change information at least includes temperature change information and power change information; An identification completion unit is used to identify whether the cell has a hot spot according to the difference information corresponding to each cell and the parameter change information, including: obtaining the ambient temperature and ambient humidity corresponding to the hot spot phenomenon identification system of the photovoltaic curtain wall; generating a target hot spot index according to the ambient temperature and ambient humidity; calculating the hot spot index corresponding to the cell according to the temperature difference information, power difference information, temperature change information and power change information, including: parsing the temperature difference information, power difference information, temperature change information and power change information, and obtaining the difference value and standard deviation corresponding to the temperature difference information, power difference information, temperature change information and power change information; calculating the hot spot index according to the difference value and standard deviation corresponding to the temperature difference information, power difference information, temperature change information and power change information, including: respectively obtaining the temperature change information and power change information corresponding to the cell within the preset range of the cell The average temperature difference value and the average power difference value; calculating the hot spot index according to the temperature average difference value and the power average difference value and the difference value and standard deviation corresponding to the temperature difference information, power difference information, temperature change information, and power change information; the expression of the hot spot index includes: ; in, For battery cells The corresponding hot spot index, is the difference value corresponding to the temperature difference information, is the standard deviation corresponding to the temperature difference information, is the difference value corresponding to the power difference information, is the standard deviation corresponding to the power difference information, is the difference value corresponding to the temperature change information, is the standard deviation corresponding to the temperature change information, is the difference value corresponding to the power change information, is the standard deviation corresponding to the power change information, is the average temperature difference value, is the average power difference value, , , and They are weight coefficients corresponding to temperature difference information, power difference information, temperature change information, and power change information respectively; if the hot spot index is greater than the target hot spot index, it is confirmed that a hot spot exists in the cell; the hot spot phenomenon of the photovoltaic curtain wall is identified; the cell with a hot spot is determined as the target cell; the circuit connection information corresponding to the BIPV module is obtained; the circuit connection information is parsed to obtain multiple power supply branches and at least one power supply bypass corresponding to the BIPV module; each of the power supply branches includes multiple cells; the target branch corresponding to the target cell is determined in the multiple power supply branches according to the cell position information corresponding to the target cell; current control information is generated according to the cell position information of each cell corresponding to the target branch, so as to divert the current corresponding to the target branch to the power supply bypass in the multiple power supply branches.

9. A control device, characterized in that: The control device comprises a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to execute the computer program and implement the method according to any one of claims 2 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed by a processor, causes the processor to implement the method according to any one of claims 2 to 7.

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