Photovoltaic fault early warning system and method

Abstract

The invention discloses a photovoltaic fault early warning system and method, and relates to the field of photovoltaic information management. Comprising a detection module, a data transmission module, an unmanned aerial vehicle, a server and terminal equipment which are connected in sequence. Through the unmanned aerial vehicle, the position of the photovoltaic defect assembly is accurately positioned, and the calculated amount is small; the operation efficiency and safety of the photovoltaic power station are improved, the fault occurrence rate and the maintenance cost are reduced, and stable development of clean energy is promoted.

Description

Technical Field

[0001] The present invention relates to the field of photovoltaic information management, and in particular to a photovoltaic fault warning system and method. Background Art

[0002] In recent years, solar energy, as a promising renewable energy source, has been widely developed. Photovoltaic energy is a form of solar energy that plays an indispensable role in curbing the global warming problem, reducing the use and emissions of fossil fuels. According to the latest announcement of the World Energy Organization, the global photovoltaic installed capacity and power generation are increasing day by day. With the rapid development of the photovoltaic industry and the rapid growth of the photovoltaic installed capacity, the service life and safety of photovoltaic arrays have received more and more attention.

[0003] Photovoltaic power stations cover a large area and are mainly distributed in wild natural environments such as deserts, wastelands, and water surfaces. Photovoltaic modules are placed in harsh outdoor environments and are exposed to wind, sun, and rain all year round, resulting in serious problems of faults and defects. Real-time control and detection of the power generation system and daily maintenance often require high labor costs, and there are disadvantages such as strong subjectivity and single inspection means, which are difficult to meet the increasing inspection needs. To ensure the efficient operation of photovoltaic power stations, an unmanned intelligent inspection method is urgently needed. Intelligent defect detection and positioning technology can realize diversified inspection modes, and at the same time give full play to the advantages of high precision, flexible response, and all-weather of robots, meeting the requirements of high-frequency unmanned inspections, which is of great significance for improving the power generation efficiency of photovoltaic power stations and ensuring the safe and efficient operation of large-scale photovoltaic power stations.

[0004] Traditional methods for monitoring and fault detection of photovoltaic power stations mainly rely on manual inspections and conventional monitoring systems, and these methods have many deficiencies. First of all, manual inspections are inefficient and it is difficult to detect potential faults in a timely manner; secondly, conventional monitoring systems usually can only detect obvious fault signals, and it is difficult to effectively identify and warn of early fault signs or complex multi-factor faults. In addition, photovoltaic power stations are usually distributed in vast areas, with a large number of equipment and complex and changeable environmental conditions, which further increase the difficulty of fault detection and maintenance.

[0005] Therefore, proposing a photovoltaic fault warning system and method to solve the problems in the prior art such as poor accuracy of photovoltaic defect positioning, large amount of calculation; low efficiency of manual inspection and difficulty in timely detecting potential faults; secondly, conventional monitoring systems usually can only detect obvious fault signals, and it is difficult to effectively identify and warn of early fault signs or complex multi-factor faults is an urgent problem to be solved by those skilled in the art. Summary of the Invention

[0006] In view of this, the present invention provides a photovoltaic fault warning system and method to solve at least one of the above technical problems.

[0007] To achieve the above object, the present invention adopts the following technical solutions:

[0008] A photovoltaic fault warning system, comprising a detection module, a data transmission module, a drone, a server and a terminal device connected in sequence;

[0009] The detection module is used to detect the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array;

[0010] The data transmission module is used to send the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array collected by the detection module to the drone;

[0011] The drone is used to judge whether to give a fault warning after receiving the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array, and send the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array and the judgment result to the server; and judge whether the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array reach the threshold through a preset threshold;

[0012] It is also used to take infrared pictures of the photovoltaic modules, read the real-time position information and attitude data of the drone, and send them to the server;

[0013] The server is used to receive the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array, judgment result, real-time position information and attitude data of the drone sent by the drone and perform data processing, and judge the fault type of the photovoltaic module array and locate the fault position.

[0014] For the above system, optionally, the detection module includes: an ambient temperature measuring instrument, an illuminance measuring instrument, a voltage sampling module and a current sampling module,

[0015] The ambient temperature measuring instrument and the illuminance measuring instrument are installed near the photovoltaic module field, and the output ends are connected to the input end of the data transmission module; the ambient temperature measuring instrument and the illuminance measuring instrument are used to measure the ambient temperature and solar irradiance of the current environment field;

[0016] The number of voltage sampling modules is the same as the number of photovoltaic modules, and the input ends of each voltage sampling module are respectively connected to the output ends of the corresponding photovoltaic modules;

[0017] The input end of the current sampling module is connected to the output end of any one photovoltaic module, and is used to collect the output voltage and output current of the photovoltaic module array in real time.

[0018] The output ends of the voltage sampling module and the current sampling module are simultaneously connected to the input end of the data transmission module.

[0019] In the above system, optionally, the drone includes a drone body and a control unit, an image acquisition unit, a data receiving / sending unit, and a data analysis unit disposed inside the drone body;

[0020] The control unit is communicatively connected to the image acquisition unit, the data receiving / sending unit, and the data analysis unit respectively;

[0021] The control unit is used to control the flight of the drone, perform fault warning judgment, and control the image acquisition unit to take pictures;

[0022] The image acquisition unit is used to acquire the current image of the photovoltaic module array;

[0023] The data receiving / sending unit is used to receive and send the illuminance value of the photovoltaic module array, the ambient temperature, the current and voltage values of the photovoltaic modules, the drone position information and attitude data, and send the fault warning judgment result of the data analysis unit.

[0024] In the above system, optionally, the server includes: a data receiving unit, a data processing unit, an output unit, and a communication unit;

[0025] The input end of the data receiving unit is connected to the output end of the data receiving / sending unit of the drone, and the output end of the data receiving unit is connected to the first input end of the data processing unit;

[0026] The data receiving unit is used to receive the illuminance value of the photovoltaic module array, the ambient temperature, the current and voltage values of the photovoltaic modules, the drone position information and attitude data, and the fault warning judgment result sent by the data receiving / sending unit, and send them to the data processing unit;

[0027] The data processing unit is connected to the input end of the output unit, and is used to call the fault warning program according to the fault warning judgment result, perform fault warning type detection, and then obtain the photovoltaic module fault type and fault location;

[0028] The output unit is connected to the input end of the communication unit, and is used to output the photovoltaic module fault type and fault location;

[0029] The communication unit is communicatively connected to the terminal device, and is used to send the photovoltaic module fault type and fault location to the terminal device.

[0030] In the above system, optionally, the server further includes a storage unit,

[0031] The storage unit is connected to the input / output end of the data receiving unit, and is used to store the illuminance value of the photovoltaic module array, the ambient temperature, the current and voltage values of the photovoltaic modules, the drone position information and attitude data, the fault warning judgment result, the photovoltaic module fault type and fault location.

[0032] In the above system, optionally, the server further includes a clustering unit. The input end of the clustering unit is connected to the output end of the storage unit, and the output end of the clustering unit is connected to the second input end of the data processing unit;

[0033] The clustering unit is used to sort out the fault data found by the UAV inspection, perform clustering analysis, form the fault frequency analysis results of each photovoltaic module, and send them to the data processing unit; the data processing unit also outputs the fault frequency of the current fault type.

[0034] A photovoltaic fault warning method, based on the photovoltaic fault warning system described in any one of the above, includes the following:

[0035] The detection module detects the illuminance value, ambient temperature, current and voltage values of the photovoltaic modules in the photovoltaic module array; and sends them to the UAV through the data transmission module. The UAV judges whether to give a fault warning, and sends the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array and the judgment result to the server; the UAV takes infrared pictures of the photovoltaic modules, reads the real-time position information and attitude data of the UAV, and sends them to the server; the server processes the received data to obtain the photovoltaic module fault type and fault location; and sends the photovoltaic module fault type and fault location to the terminal device.

[0036] In the above method, optionally, the storage unit stores the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array, UAV position information and attitude data, fault warning judgment results, photovoltaic module fault types and fault locations; the clustering unit calls the data in the storage unit, performs clustering analysis to obtain the fault frequency analysis results of each photovoltaic module, and sends them to the data processing unit; the data processing unit also outputs the fault frequency of the current fault type.

[0037] From the above technical solutions, compared with the prior art, the present invention provides a photovoltaic fault warning system and method, which has the following beneficial effects:

[0038] 1) The position of the photovoltaic defective module is accurately located, and the calculation amount is small;

[0039] 2) Improve the operation efficiency and safety of the photovoltaic power station, reduce the fault incidence rate and maintenance cost, and promote the stable development of clean energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the provided drawings.

[0041] Figure 1 Block diagram of a photovoltaic fault warning system disclosed by the present invention;

[0042] Figure 2 Block diagram of the detection module components disclosed by the present invention;

[0043] Figure 3 Block diagram of the drone components disclosed by the present invention;

[0044] Figure 4 Block diagram of the server components of the present invention. Specific embodiments

[0045] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0046] In this application, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. The term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, the element defined by the statement "including an..." does not exclude the existence of additional identical elements in the process, method, article or device including the said element.

[0047] Refer to Figure 1 As shown, the present invention discloses a photovoltaic fault warning system, including a detection module, a data transmission module, a drone, a server and a terminal device connected in sequence;

[0048] The photovoltaic module array is composed of multiple photovoltaic modules connected in series;

[0049] The detection module is used to detect the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array; divide the time period from 6 am to 6 pm into whole hours for data detection;

[0050] The data transmission module is used to send the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array collected by the detection module to the drone;

[0051] A drone is used to receive the illuminance value, ambient temperature, current and voltage values of a photovoltaic module array, determine whether to issue a fault warning, and send the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array and the judgment result to a server; and judge whether the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array reach the threshold through a preset threshold.

[0052] It is also used to take infrared pictures of the photovoltaic modules, read the real-time position information and attitude data of the drone, and send them to the server.

[0053] A server is used to receive the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array, judgment result, real-time position information and attitude data of the drone sent by the drone, perform data processing, and judge the fault type of the photovoltaic module array and locate the fault position.

[0054] The fault types include: photovoltaic hot spot, shadow occlusion, and abnormal aging.

[0055] Further, as shown in Figure 2 The detection module includes: an ambient temperature measuring instrument, an illuminance measuring instrument, a voltage sampling module, and a current sampling module.

[0056] The ambient temperature measuring instrument and the illuminance measuring instrument are installed near the photovoltaic module field, and the output ends are connected to the input end of the data transmission module; the ambient temperature measuring instrument and the illuminance measuring instrument are used to measure the ambient temperature and solar irradiance of the current environment field.

[0057] The number of voltage sampling modules is the same as the number of photovoltaic modules, and the input ends of each voltage sampling module are respectively connected to the output ends of the corresponding photovoltaic modules.

[0058] The input end of the current sampling module is connected to the output end of any one photovoltaic module, and is used to collect the output voltage and output current of the photovoltaic module array in real time.

[0059] The output ends of the voltage sampling module and the current sampling module are simultaneously connected to the input end of the data transmission module.

[0060] Further, as shown in Figure 3 The drone includes a drone body and a control unit, an image acquisition unit, a data receiving / sending unit, and a data analysis unit provided inside the drone body.

[0061] The control unit is respectively communicatively connected to the image acquisition unit, the data receiving / sending unit, and the data analysis unit.

[0062] The data analysis unit is used to determine whether the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array do not reach the preset threshold. If not, it is determined that a fault warning is required.

[0063] The control unit is used to control the flight of the drone, the fault warning judgment, and the image acquisition unit to take images.

[0064] The image acquisition unit is used to acquire the current photovoltaic module array image.

[0065] The data receiving / sending unit is used to receive and send the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array, the drone position information and attitude data, and send the fault warning judgment result of the data analysis unit.

[0066] Further, as shown in Figure 4 The server includes: a data receiving unit, a data processing unit, an output unit, and a communication unit.

[0067] The input end of the data receiving unit is connected to the output end of the data receiving / sending unit of the drone, and the output end of the data receiving unit is connected to the first input end of the data processing unit.

[0068] The data receiving unit is used to receive the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array, the drone position information and attitude data, and the fault warning judgment result sent by the data receiving / sending unit, and send them to the data processing unit.

[0069] The data processing unit is connected to the input end of the output unit. It is used to call the fault warning program according to the fault warning judgment result, perform fault warning type detection, and then obtain the photovoltaic module fault type and fault location.

[0070] The output unit is connected to the input end of the communication unit and is used to output the photovoltaic module fault type and fault location.

[0071] The communication unit is communicatively connected to the terminal device and is used to send the photovoltaic module fault type and fault location to the terminal device.

[0072] Specifically, the flight altitude of the drone is H, the GPS coordinates are (x D , y D ), the camera field of view angle is γ, the pitch angle is θ ZD , and the heading angle is ψ ZD。The data processing unit uses CSPDarknet53 as the backbone network for feature extraction, and adopts the FPT structure based on the attention mechanism and FPN structure for information fusion. It takes the aerial photo as the input and the pixel coordinates of the faulty photovoltaic module as the output. It segments the original image to obtain the photovoltaic module mask, and then determines the faulty photovoltaic module according to the positioning result of the target detection network to obtain the corner pixel coordinates of the target module. It establishes a coordinate conversion model based on the real-time coordinates and attitude angles captured by the drone, and converts the pixel coordinates output by the neural network into position coordinates in the geodetic coordinate system to obtain the position information of the photovoltaic module where the defect is located.

[0073] The specific work content of the data processing unit also includes:

[0074] Extract the device operation characteristics and environmental operation characteristics from the illumination value, ambient temperature, current and voltage values of the photovoltaic module array, and obtain the device operation characteristic data and environmental operation characteristic data respectively;

[0075] Specifically, extract the characteristics of the power station operation data to obtain the preliminary device operation characteristic data, and extract the characteristics of the environmental operation data to obtain the preliminary environmental operation characteristic data;

[0076] Perform multi-scale feature transformation on the preliminary device operation characteristic data to obtain the device operation characteristic data;

[0077] Perform extreme value feature extraction on the preliminary environmental operation characteristic data to obtain the environmental operation characteristic data.

[0078] The multi-scale feature transformation includes:

[0079] Perform initial feature decomposition on the preliminary device operation characteristic data to obtain the decomposed feature data;

[0080] Perform multi-scale time series segmentation on the decomposed feature data to obtain the multi-scale time series segmentation data;

[0081] Perform multi-scale feature extraction on the multi-scale time series segmentation data to obtain the multi-scale feature data;

[0082] Perform frequency domain feature analysis on the multi-scale feature data to obtain the frequency domain feature data;

[0083] Perform feature combination according to the multi-scale feature data to obtain the combined feature data;

[0084] Perform multi-scale feature aggregation according to the frequency domain feature data and the combined feature data to obtain the device operation characteristic data.

[0085] Construct a recursive tree based on the device operation characteristic data and the environmental operation characteristic data to obtain the device operation decision tree data and the environmental operation decision tree data respectively;

[0086] Construct a decision forest based on the device operation decision tree data, the environmental operation decision tree data and the corresponding photovoltaic power station early warning data to obtain a photovoltaic analysis model of the photovoltaic power station for performing photovoltaic power station fault early warning operations.

[0087] Accurate feature extraction can better reflect the actual operation state of the device, help to detect abnormal situations or potential faults in a timely manner, and improve the sensitivity of fault detection. Extract features from the environmental operation data, such as temperature, humidity, wind speed, etc., to obtain preliminary environmental operation characteristic data. Analyzing these features can help understand the impact of the external environment on the operation of the photovoltaic power station. Perform multi-scale feature transformation on the preliminary device operation characteristic data, and capture multi-level information in the data by analyzing the feature changes on different time scales. Extract extreme value features from the preliminary environmental operation characteristic data to identify extreme events or abnormal situations in the environmental data.

[0088] Furthermore, the server also includes a storage unit,

[0089] The storage unit is connected to the input / output end of the data receiving unit and is used to store the illuminance value of the photovoltaic module array, the environmental temperature, the current and voltage values of the photovoltaic module, the drone position information and attitude data, the fault early warning judgment result, the photovoltaic module fault type and the fault location.

[0090] Still further, the server also includes a clustering unit. The input end of the clustering unit is connected to the output end of the storage unit, and the output end of the clustering unit is connected to the second input end of the data processing unit;

[0091] The clustering unit is used to sort out the fault data found by the drone inspection and perform clustering analysis to form the fault frequency analysis results of each photovoltaic module and send them to the data processing unit; the data processing unit also outputs the fault frequency of the current fault type.

[0092] Specifically, use the k-means clustering algorithm to divide the fault data into k groups, and divide the fault frequency of the photovoltaic module into four situations: frequent faults, occasional faults, possible faults, and no faults; clustering belongs to unsupervised learning, and k-means clustering is the most basic and commonly used clustering algorithm. Its basic idea is to find a division scheme of K clusters through iteration, so that the loss function corresponding to the clustering result is the smallest.

[0093] And Figure 1 Corresponding to the above system, the present invention also discloses a photovoltaic fault early warning method, based on any one of the above-mentioned photovoltaic fault early warning systems, including the following contents:

[0094] The detection module detects the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array; and sends them to the drone through the data transmission module. The drone determines whether to issue a fault warning, and sends the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array and the judgment result to the server; the drone takes infrared pictures of the photovoltaic modules, reads the real-time position information and attitude data of the drone, and sends them to the server; the server processes the received data to obtain the fault type and fault location of the photovoltaic modules; and sends the fault type and fault location of the photovoltaic modules to the terminal device.

[0095] Further, the storage unit stores the illuminance value, ambient temperature, current and voltage values of the photovoltaic module array, the drone position information and attitude data, the fault warning judgment result, the fault type and fault location of the photovoltaic modules; the clustering unit calls the data in the storage unit, conducts clustering analysis to obtain the fault frequency analysis results of each photovoltaic module, and sends them to the data processing unit; the data processing unit also outputs the fault frequency of the current fault type.

[0096] Each embodiment in this specification is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and the key point of each embodiment is to illustrate the differences from other embodiments. In particular, for the system or system embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiments. The systems and system embodiments described above are only illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative work.

[0097] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A photovoltaic fault early warning system, characterized in that: It includes a detection module, a data transmission module, a drone, a server and a terminal device connected in sequence; A detection module is used to detect the illumination value of the photovoltaic module array, the ambient temperature, and the current and voltage values ​​of the photovoltaic modules; The data transmission module is used to send the illumination value, ambient temperature, current and voltage value of the photovoltaic module array collected by the detection module to the drone; The drone is used to receive the illumination value, ambient temperature, current and voltage value of the photovoltaic module array, determine whether to issue a fault warning, and send the illumination value, ambient temperature, current and voltage value of the photovoltaic module array and the judgment result to the server; and determine whether the illumination value, ambient temperature, current and voltage value of the photovoltaic module array reach the threshold value through a preset threshold value; It is also used to take infrared pictures of photovoltaic modules, read the real-time location information and attitude data of drones, and send them to the server; The server is used to receive the illumination value of the photovoltaic module array, the ambient temperature, the current and voltage values ​​of the photovoltaic module, the judgment result, the real-time position information and the attitude data of the drone and process the data to judge the fault type of the photovoltaic module array and locate the fault location.

2. A photovoltaic fault early warning system according to claim 1, characterized in that: The detection module includes: ambient temperature measuring instrument, illumination measuring instrument, voltage sampling module and current sampling module. The ambient temperature measuring instrument and the illuminance measuring instrument are installed near the photovoltaic module field, and the output end is connected to the input end of the data transmission module; the ambient temperature measuring instrument and the illuminance measuring instrument are used to measure the ambient temperature and solar radiation of the current environment field; The number of voltage sampling modules is the same as the number of photovoltaic modules, and the input end of each voltage sampling module is respectively connected to the output end of the corresponding photovoltaic module; The input end of the current sampling module is connected to the output end of any photovoltaic module to collect the output voltage and output current of the photovoltaic module array in real time; The output ends of the voltage sampling module and the current sampling module are simultaneously connected to the input end of the data transmission module.

3. A photovoltaic fault early warning system according to claim 2, characterized in that: The drone includes a drone body and a control unit, an image acquisition unit, a data receiving / transmitting unit, and a data analysis unit arranged inside the drone body; The control unit is communicatively connected with the image acquisition unit, the data receiving / sending unit, and the data analysis unit respectively; A control unit is used to control the flight of the UAV, fault warning judgment and image acquisition unit to take images; An image acquisition unit, used to acquire the current photovoltaic module array image; The data receiving / transmitting unit is used to receive and transmit the illumination value of the photovoltaic module array, the ambient temperature, the current and voltage values ​​of the photovoltaic modules, the position information and attitude data of the drone, and the fault warning judgment results of the sending data analysis unit.

4. A photovoltaic fault early warning system according to claim 3, characterized in that: The server includes: a data receiving unit, a data processing unit, an output unit, and a communication unit; The input end of the data receiving unit is connected to the output end of the data receiving / transmitting unit of the drone, and the output end of the data receiving unit is connected to the first input end of the data processing unit; A data receiving unit is used to receive the illumination value of the photovoltaic module array, the ambient temperature, the current and voltage values ​​of the photovoltaic modules, the position information and attitude data of the drone, and the fault warning judgment result sent by the data receiving / sending unit, and send them to the data processing unit; The data processing unit is connected to the input end of the output unit and is used to call the fault warning program according to the fault warning judgment result, perform fault warning type detection, and then obtain the fault type and fault location of the photovoltaic module; An output unit, connected to the input terminal of the communication unit, for outputting the fault type and fault location of the photovoltaic module; The communication unit is connected to the terminal device for communication and is used to send the fault type and fault location of the photovoltaic module to the terminal device.

5. A photovoltaic fault early warning system according to claim 4, characterized in that: The server also includes a storage unit, The storage unit is connected to the input / output terminal of the data receiving unit and is used to store the illumination value of the photovoltaic module array, the ambient temperature, the current and voltage values ​​of the photovoltaic module, the position information and attitude data of the drone, the fault warning judgment result, the photovoltaic module fault type and the fault location.

6. A photovoltaic fault early warning system according to claim 5, characterized in that: The server further includes a clustering unit, an input end of the clustering unit is connected to an output end of the storage unit, and an output end of the clustering unit is connected to a second input end of the data processing unit; The clustering unit is used to sort out the fault data found by the drone inspection and perform cluster analysis to form the fault frequency analysis results of each photovoltaic module and send them to the data processing unit; The data processing unit also outputs the fault frequency of the current fault type.

7. A photovoltaic fault early warning method, characterized in that: A photovoltaic fault early warning system according to any one of claims 1 to 6, comprising the following contents: The detection module detects the illumination value of the photovoltaic module array, the ambient temperature, and the current and voltage values ​​of the photovoltaic modules; And send it to the drone through the data transmission module. The drone determines whether to issue a fault warning, and sends the illumination value of the PV module array, ambient temperature, current and voltage values ​​of the PV module and the judgment results to the server; the drone takes infrared pictures of the PV module, reads the real-time location information and attitude data of the drone, and sends them to the server; the server processes the received data to obtain the fault type and fault location of the PV module; and sends the fault type and fault location of the PV module to the terminal device.

8. A photovoltaic fault early warning method according to claim 7, characterized in that: The storage unit saves the illumination value of the photovoltaic module array, the ambient temperature, the current and voltage values ​​of the photovoltaic modules, the position information and attitude data of the drone, the fault warning judgment results, the photovoltaic module fault type and the fault location; the clustering unit calls the storage unit data, performs clustering analysis to obtain the fault frequency analysis results of each photovoltaic module, and sends them to the data processing unit; the data processing unit also outputs the fault frequency of the current fault type.

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