New energy one-stop management operation method and system based on GIS

Abstract

The invention provides a GIS-based new energy one-stop management operation method and system, and relates to the technical field of new energy power generation, and the method comprises the steps: obtaining a first fault score, generated by a GIS management platform, of a target photovoltaic panel after the operation parameters of the target photovoltaic panel in a photovoltaic array are transmitted to the GIS management platform; generating a correction coefficient according to the data of the environment where the target photovoltaic panel is located, and correcting the first fault score according to the correction coefficient to generate a second fault score; according to historical operation data of the target photovoltaic panel, correcting the second fault score to generate a target fault score; when the target fault score is lower than a preset score, determining that the target photovoltaic panel is a fault photovoltaic panel; and marking the position of the fault photovoltaic panel on an electronic map of the GIS management platform, and generating a maintenance task of the fault photovoltaic panel. The technical effect of the invention is that the accuracy of photovoltaic panel fault diagnosis is improved.

Description

Technical Field

[0001] The present application relates to the field of supply management technology, and in particular to a one-stop management and operation method and system for new energy based on GIS. Background Art

[0002] With the rapid development of the new energy industry, the scale of photovoltaic power stations continues to expand. Especially in complex operating environments, how to promptly detect faulty equipment and formulate effective maintenance plans has become a technical problem that needs to be urgently solved in the operation and maintenance management of photovoltaic power stations.

[0003] At present, some photovoltaic power stations use automated monitoring systems to monitor the operating status of photovoltaic panels, and identify whether there is a fault in the photovoltaic panel by collecting operating parameters and setting alarm thresholds. Although the above method can realize real-time monitoring of photovoltaic panel faults and improve the timeliness of fault detection, the above method fails to fully consider the impact of external factors such as the environment on the photovoltaic panel, and only relies on a single operating parameter to determine whether the photovoltaic panel has a fault, it is difficult to ensure the accuracy of the diagnosis result. Summary of the invention

[0004] The present application provides a one-stop management and operation method and system for new energy based on GIS, which is used to improve the accuracy of photovoltaic panel fault diagnosis.

[0005] In a first aspect, the present application provides a one-stop management and operation method for new energy based on GIS, the method comprising: after sending the operating parameters of the target photovoltaic panel in the photovoltaic array to the GIS management platform, obtaining the first fault score of the target photovoltaic panel generated by the GIS management platform according to the operating parameters; obtaining environmental data of the environment in which the target photovoltaic panel is located, generating a correction coefficient according to the environmental data, and correcting the first fault score according to the correction coefficient to generate a second fault score of the target photovoltaic panel; obtaining historical operating data of the target photovoltaic panel, correcting the second fault score according to the historical operating data, and generating a target fault score of the target photovoltaic panel; when the target fault score is lower than a preset score, determining that the target photovoltaic panel is a faulty photovoltaic panel; marking the location of the faulty photovoltaic panel on the electronic map of the GIS management platform, and generating a maintenance task for the faulty photovoltaic panel.

[0006] By adopting the above technical solution, a multi-dimensional correction of fault scores is achieved by combining the operating parameters, environmental data and historical operating data of photovoltaic panels. First, the first fault score is generated based on the operating parameters, and then the correction coefficient is generated by introducing environmental data to correct it to obtain the second fault score. Finally, the target fault score is corrected in combination with the historical operating data, thereby establishing a complete fault assessment system. When the target fault score is lower than the preset score, the system automatically marks the location of the faulty photovoltaic panel on the electronic map of the GIS management platform and generates a maintenance task, which realizes the precise positioning and rapid response of the faulty equipment and improves the accuracy of photovoltaic panel fault diagnosis.

[0007] Optionally, the operating parameters include current, voltage and temperature, and the obtaining of the GIS management platform to generate a first fault score for the target photovoltaic panel based on the operating parameters includes: calculating a first difference between the current and a preset current, a second difference between the voltage and a preset voltage, and a third difference between the temperature and a preset temperature; substituting the first difference, the second difference and the third difference into a fault scoring formula to generate a first fault score for the target photovoltaic panel; wherein the fault scoring formula is: S1=ω1|ΔI|+ω2|ΔV|+ω3|ΔT|; wherein S1 is the first fault score, ω1 is the first weight coefficient, ΔI is the first difference, ω2 is the second weight coefficient, ΔV is the second difference, ω3 is the third weight coefficient, and ΔT is the third difference.

[0008] By adopting the above technical solution, the three key operating parameters of the photovoltaic panel, namely the current, voltage and temperature, are collected, their differences from the preset values ​​are calculated, and different weight coefficients are introduced to construct the fault scoring formula, so that the first fault score can comprehensively reflect the degree of deviation of various operating parameters. This scoring method based on multi-parameter weighted calculation not only takes into account the influence of different operating parameters on the fault state, but also can quantitatively characterize the operating state of the photovoltaic panel, providing a reliable data basis for subsequent fault judgment.

[0009] Optionally, the environmental data includes light intensity and ambient temperature, and generating a correction coefficient based on the environmental data includes: obtaining a preset standard light intensity, calculating a ratio of the light intensity to the standard light intensity, and determining the current influence coefficient based on the ratio; obtaining a preset standard ambient temperature, calculating a temperature difference between the ambient temperature and the standard ambient temperature, and determining the temperature influence coefficient based on the temperature difference; and using the current influence coefficient and the temperature influence coefficient as correction coefficients.

[0010] By adopting the above technical solution, by collecting light intensity and ambient temperature data, the light intensity ratio and temperature difference are calculated respectively, the corresponding current influence coefficient and temperature influence coefficient are generated, and finally a comprehensive correction coefficient is formed. This dual correction mechanism based on environmental factors effectively eliminates the interference of external environmental changes on fault judgment, so that the fault score can more accurately reflect the actual operating status of the photovoltaic panel.

[0011] Optionally, the first fault score is corrected according to the correction coefficient to generate a second fault score for the target photovoltaic panel, including: substituting the current influence coefficient and the temperature influence coefficient into a correction formula to generate a second fault score for the target photovoltaic panel; wherein the correction formula is: S2=I1ω1|ΔI|+ω2|ΔV|+T1ω3|ΔT|; wherein S2 is the second fault score, I1 is the current influence coefficient, ω1 is the first weight coefficient, ΔI is the first difference, ω2 is the second weight coefficient, ΔV is the second difference, T1 is the temperature influence coefficient, ω3 is the third weight coefficient, and ΔT is the third difference.

[0012] By adopting the above technical solution, the current influence coefficient and temperature influence coefficient generated by environmental factors are introduced into the correction formula, and the current deviation and temperature deviation items in the first fault score are corrected in a targeted manner, while the voltage deviation item remains unchanged. This differentiated correction method accurately reflects the degree of influence of environmental changes on different operating parameters, so that the second fault score more objectively represents the performance status of the photovoltaic panel.

[0013] Optionally, the second fault score is corrected according to the historical operation data to generate a target fault score for the target photovoltaic panel, including: obtaining the number of failures of the target photovoltaic panel within a preset time period from the historical operation data; when the number of failures is greater than the preset number, obtaining a preset first reduction coefficient, and arithmetically multiplying the second fault score by the first reduction coefficient to obtain the target fault score; when the number of failures is less than or equal to the preset number, obtaining a preset first improvement coefficient, and arithmetically multiplying the second fault score by the first improvement coefficient to obtain the target fault score.

[0014] By adopting the above technical solution, the number of failures of the target photovoltaic panel within the preset time is counted, and different coefficients are used to dynamically correct the second fault score: when the number of failures is large, the coefficient is reduced to reflect the trend of reduced equipment reliability; when the number of failures is small, the coefficient is increased to reflect the stability of the equipment operation status. This adaptive correction mechanism based on historical fault data enables the final target fault score to more accurately predict the potential failure risk of photovoltaic panels.

[0015] Optionally, marking the location of the faulty photovoltaic panel on the electronic map of the GIS management platform includes: when the target fault score is less than a first preset score, marking the target photovoltaic panel with a first color so that operating personnel can perform routine inspections; when the target fault score is not less than the first preset score and less than a second preset score, marking the target photovoltaic panel with a second color so that the operating personnel can perform regular maintenance; when the target fault score is not less than the second preset score, marking the target photovoltaic panel with a third color so that the operating personnel can perform emergency maintenance.

[0016] By adopting the above technical solution, by setting different fault scoring thresholds and using the corresponding color marking system, visual hierarchical management of fault levels is achieved. According to the target fault score, the system automatically marks the faulty photovoltaic panels with different colors, corresponding to the three maintenance strategies of routine inspection, regular maintenance and emergency maintenance. This scoring-based hierarchical marking method not only intuitively shows the severity of the fault, but also guides operators to reasonably arrange maintenance priorities, improving the pertinence and efficiency of operation and maintenance work.

[0017] Optionally, generating a maintenance task for the faulty photovoltaic panel includes: determining a maintenance priority based on the target fault score; generating a maintenance route based on the location information of the target photovoltaic panel; and generating a maintenance task including the maintenance priority, the target photovoltaic panel location information and the maintenance route.

[0018] By adopting the above technical solution, intelligent planning of maintenance work is achieved by integrating the target fault score, location information and maintenance route into the maintenance task. The system determines the maintenance priority based on the fault score, and automatically generates the optimal maintenance route based on the specific location of the photovoltaic panel to form a task package containing complete maintenance information. This systematic maintenance task generation mechanism not only improves the planning and organization of maintenance work, but also helps operators complete maintenance work more efficiently.

[0019] In the second aspect, the present application provides a one-stop management and operation system for new energy based on GIS, the system comprising: an acquisition module, a generation module, a correction module, a determination module and a generation module; wherein, The acquisition module is used to send the operating parameters of the target photovoltaic panel in the photovoltaic array to the GIS management platform, and then obtain the first fault score of the target photovoltaic panel generated by the GIS management platform according to the operating parameters; the generation module is used to obtain the environmental data of the environment in which the target photovoltaic panel is located, generate a correction coefficient according to the environmental data, and correct the first fault score according to the correction coefficient to generate a second fault score for the target photovoltaic panel; the correction module is used to obtain the historical operating data of the target photovoltaic panel, correct the second fault score according to the historical operating data, and generate a target fault score for the target photovoltaic panel; the determination module is used to determine that the target photovoltaic panel is a faulty photovoltaic panel when the target fault score is lower than a preset score; the generation module is used to mark the location of the faulty photovoltaic panel on the electronic map of the GIS management platform, and generate a maintenance task for the faulty photovoltaic panel.

[0020] In the third aspect, the present application provides an electronic device, adopting the following technical solution: including a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes a computer program such as any of the above-mentioned GIS-based one-stop new energy management and operation methods.

[0021] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: storing a computer program that can be loaded by a processor and execute any of the above-mentioned GIS-based one-stop management and operation methods for new energy.

[0022] In summary, the present application includes at least one of the following beneficial technical effects: 1. By combining the operating parameters, environmental data and historical operating data of photovoltaic panels, a multi-dimensional correction of fault scores is achieved. First, the first fault score is generated based on the operating parameters, and then the correction coefficient is generated by introducing environmental data to correct it to obtain the second fault score. Finally, the target fault score is corrected in combination with the historical operating data, thus establishing a complete fault assessment system. When the target fault score is lower than the preset score, the system automatically marks the location of the faulty photovoltaic panel on the electronic map of the GIS management platform and generates a maintenance task, achieving accurate positioning and rapid response of the faulty equipment, and improving the accuracy of photovoltaic panel fault diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flow chart of a one-stop management and operation method of new energy based on GIS provided in an embodiment of the present application; Figure 2It is a structural diagram of a one-stop management and operation system of new energy based on GIS provided in an embodiment of the present application; Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0024] Description of reference numerals: 1000, electronic device; 1001, processor; 1002, communication bus; 1003, user interface; 1004, network interface; 1005, memory. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0026] In the description of the embodiments of the present application, words such as "illustrative", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "illustrative", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "illustrative", "for example" or "for example" is intended to present related concepts in a concrete way.

[0027] Photovoltaic power generation is an important component of clean energy, and its installed capacity is constantly expanding. Large photovoltaic power stations are often composed of thousands of photovoltaic panels, with a wide distribution range, and difficult operation and maintenance management. At present, the operation and maintenance management of photovoltaic power stations mainly relies on single operating parameter monitoring, such as abnormal judgment of current, voltage and other data. This method cannot fully consider the impact of environmental factors and is prone to misjudgment. For example, low current output when the light intensity is weak may be misjudged as a fault state, resulting in unnecessary maintenance work.

[0028] Traditional photovoltaic power station operation and maintenance mainly adopts the method of regular inspection, which cannot detect and handle faults in time, resulting in waste of human resources, unreasonable maintenance route planning, and lack of targeted maintenance strategies. In addition, the current management methods of most photovoltaic power stations have problems such as low degree of informatization, low data utilization, lack of intelligent decision support, and fragmented operation and maintenance management. Existing management systems often ignore the value of historical operation data and fail to make full use of historical fault information to optimize current operation and maintenance decisions, which leads to poor fault prediction capabilities, unscientific maintenance priority division, and unsatisfactory maintenance cost control. Although some photovoltaic power stations have begun to use GIS systems, the application level is relatively shallow and is only used to display the location of equipment. It lacks deep integration with fault diagnosis and fails to give full play to the advantages of GIS in spatial analysis and path planning.

[0029] Therefore, there is an urgent need for a photovoltaic power station management method that can comprehensively consider multiple factors and has intelligent analysis capabilities to improve operation and maintenance efficiency and reduce management costs.

[0030] Figure 1 Schematic diagram of a one-stop management and operation method of new energy based on GIS provided in the embodiment of the present application. Figure 1 As shown, the method includes S101-S105: S101, after sending the operating parameters of the target photovoltaic panel in the photovoltaic array to the GIS management platform, obtain a first fault score of the target photovoltaic panel generated by the GIS management platform according to the operating parameters.

[0031] The GIS management platform includes a data collection layer, a data processing layer, and an application display layer. The data collection layer establishes a communication connection with the sensors on each photovoltaic panel in the photovoltaic array to receive real-time operating parameter data; the data processing layer is responsible for data storage, calculation, and analysis, and has built-in fault scoring models, environmental impact analysis models, and other functional modules; the application display layer provides an electronic map visualization interface to display the spatial distribution and operating status of photovoltaic panels. The core function of the platform is to deeply integrate the equipment management of photovoltaic power stations with geographic spatial information, realizing the spatial management of equipment location, operating status, and fault information.

[0032] For example, when the system receives the operating parameters of the target photovoltaic panel, it can not only calculate the fault score, but also accurately locate the specific location of the photovoltaic panel on the electronic map and intuitively display its operating status through different icons or colors. This management method based on spatial information enables operation and maintenance personnel to quickly locate faulty equipment, optimize maintenance routes, and improve work efficiency.

[0033] In addition, the GIS management platform also has data storage and historical query functions, which can record the operating parameters, fault records and maintenance records of each photovoltaic panel, providing data support for the full life cycle management of the equipment.

[0034] Each photovoltaic panel in the photovoltaic array is equipped with a sensor for collecting operating parameters. The sensor collects the current, voltage and temperature data of the photovoltaic panel in real time. When the target photovoltaic panel needs to be monitored for faults, the sensor sends the collected operating parameters to the GIS management platform through the wireless communication module.

[0035] After receiving the operating parameters, the GIS management platform first obtains the standard operating parameters preset by the system, including preset current, preset voltage and preset temperature. These preset parameters are reference values ​​under the optimal working conditions determined based on the specification parameters of the photovoltaic panel and historical operating experience. Subsequently, the GIS management platform calculates the first difference between the actual current and the preset current, the second difference between the actual voltage and the preset voltage, and the third difference between the actual temperature and the preset temperature. In order to accurately evaluate the operating status of the target photovoltaic panel, the system uses the fault scoring formula S1=ω1|ΔI|+ω2|ΔV|+ω3|ΔT| for calculation, where ω1, ω2, and ω3 are the first weight coefficient, the second weight coefficient, and the third weight coefficient, respectively. The values ​​of these weight coefficients are determined according to the degree of influence of each parameter on the performance of the photovoltaic panel.

[0036] First, the current deviation |ΔI|, voltage deviation |ΔV| and temperature deviation |ΔT| are selected as scoring indicators because these three parameters can most directly reflect the working status of the photovoltaic panel. The current reflects the power generation capacity of the photovoltaic panel. When the photovoltaic panel is partially blocked, aged or damaged, the output current will be significantly reduced; the voltage can indicate the internal circuit status of the photovoltaic panel. When there are faults such as cold welding and open circuit, the voltage value will be abnormal; the temperature is an important indicator for the safe operation of the photovoltaic panel. Abnormal temperature often indicates the occurrence of hot spot effect or other faults.

[0037] Secondly, using absolute values ​​to represent deviations is to unify the measurement standards. Because the actual operating parameters may be higher or lower than the preset values, but whether it is a positive deviation or a negative deviation, it means that the photovoltaic panel has deviated from the optimal working state. Using absolute values ​​can unify deviations in different directions into quantitative indicators of the degree of fault.

[0038] Again, the purpose of introducing weight coefficients ω1, ω2, and ω3 is to balance the contribution of different parameters to the fault score. This is because current, voltage, and temperature have different effects on the performance of photovoltaic panels, and their measured values ​​have different orders of magnitude and ranges of variation. By setting different weight coefficients, the proportion of each parameter in the score can be adjusted according to its importance and actual engineering experience. For example, current anomalies usually reflect power generation efficiency issues more directly, so a larger ω1 can be set; while temperature changes may be partly due to environmental factors, so a relatively small ω3 can be set.

[0039] Finally, the use of linear weighted summation makes the scoring results more interpretable and adjustable. The linear relationship makes the impact of each parameter on the final score clear and intuitive, making it easier for operation and maintenance personnel to understand and analyze the cause of the fault; at the same time, by adjusting the weight coefficient, it can flexibly adapt to the operation and maintenance needs of different types of photovoltaic power stations.

[0040] This scoring method integrates multiple monitoring parameters into a single fault indicator through a mathematical model, which not only retains the characteristic information of the original data, but also simplifies the complexity of fault judgment, providing a reliable quantitative basis for subsequent fault diagnosis and maintenance decisions. Through this fault scoring formula, the system performs a weighted summation of the deviation values ​​of each parameter and finally obtains the first fault score of the target photovoltaic panel.

[0041] S102, obtaining environmental data of the environment in which the target photovoltaic panel is located, generating a correction coefficient according to the environmental data, and correcting the first fault score according to the correction coefficient to generate a second fault score of the target photovoltaic panel.

[0042] The GIS management platform first obtains the environmental data of the target photovoltaic panel's environment through environmental monitoring equipment. Then, the GIS management platform generates the corresponding correction coefficient based on the obtained environmental data. Subsequently, the GIS management platform calculates and processes the first fault score and the correction coefficient to obtain the second fault score after environmental correction. The second fault score more accurately reflects the actual working condition of the photovoltaic panel by considering the influence of environmental factors, avoids misjudgment caused by interference from environmental factors, and improves the accuracy of fault diagnosis.

[0043] Specifically, the light intensity and ambient temperature in the environmental data are two key factors that affect the power generation performance of photovoltaic panels. Therefore, the present invention elaborates on the generation process of the correction coefficient. The GIS management platform first obtains the light intensity data collected by the environmental monitoring equipment, and compares it with the standard light intensity preset by the system. The current influence coefficient is determined by calculating the ratio of the actual light intensity to the standard light intensity. This is because the output current of the photovoltaic panel is positively correlated with the light intensity. When the actual light intensity is lower than the standard value, even if the photovoltaic panel is in normal working condition, its output current will be reduced accordingly.

[0044] At the same time, the GIS management platform obtains the ambient temperature data collected by the environmental monitoring equipment, subtracts it from the preset standard ambient temperature to obtain the temperature difference, and determines the temperature influence coefficient based on the temperature difference. This is because changes in ambient temperature will affect the photoelectric conversion efficiency of the photovoltaic panels, and excessively high temperatures will lead to a decrease in power generation efficiency.

[0045] Finally, the GIS management platform uses the calculated current influence coefficient and temperature influence coefficient as correction coefficients for subsequent fault score correction. This correction method based on the dual factors of light intensity and ambient temperature can more comprehensively reflect the impact of environmental conditions on the performance of photovoltaic panels, making the correction of fault scores more accurate, thereby improving the reliability of fault diagnosis.

[0046] Based on the above embodiment, as an optional implementation, in S102, the environmental data includes light intensity and ambient temperature, and generating the correction coefficient according to the environmental data specifically includes S201-S203: S201, obtaining a preset standard light intensity, calculating a ratio of the light intensity to the standard light intensity, and determining a current influence coefficient according to the ratio.

[0047] During the operation of photovoltaic panels, light intensity is a key factor affecting the output current. In order to accurately evaluate the operating status of photovoltaic panels, it is necessary to standardize the output current under actual lighting conditions. This process calculates the ratio of actual light intensity to standard light intensity and determines the current influence coefficient based on it, thereby converting the current data under different lighting conditions into comparable standard values.

[0048] In specific implementation, the GIS management platform first obtains the preset standard light intensity from the system database. This standard value is usually set to 1000W / m 2 , which is the light intensity under the standard test conditions (STC) commonly used in the photovoltaic industry. The system calculates the ratio of the real-time collected light intensity to this standard value to obtain a value that reflects the degree of deviation between the current light conditions and the standard conditions. This ratio is calculated using a simple division operation, that is, the actual light intensity is divided by the standard light intensity.

[0049] Based on the physical characteristics of photovoltaic cells, the output current of photovoltaic panels is approximately linearly related to light intensity. Therefore, the system directly uses the calculated light intensity ratio as the current influence coefficient. For example, when the actual light intensity is 800W / m 2 When the calculated ratio is 0.8, this value is used as the current influence coefficient under the current conditions. This processing method reflects the basic principle of photovoltaic power generation, that is, the output current changes proportionally with the change of light intensity.

[0050] This method of calculating the current influence coefficient based on the light intensity ratio provides an important correction basis for subsequent fault diagnosis. Through this coefficient, the system can convert the current values ​​measured under different light conditions into equivalent values ​​under standard conditions, making the current data under different times and weather conditions comparable. This standardization process eliminates the interference of light intensity changes on fault judgment and improves the accuracy of fault diagnosis.

[0051] S202, obtaining a preset standard ambient temperature, calculating a temperature difference between the ambient temperature and the standard ambient temperature, and determining a temperature influence coefficient according to the temperature difference.

[0052] In photovoltaic power generation systems, ambient temperature has a significant impact on the output characteristics of photovoltaic panels, especially the output voltage. In order to accurately evaluate the operating status of photovoltaic panels, it is necessary to consider the impact of temperature factors on output parameters. By calculating the difference between the actual ambient temperature and the standard ambient temperature and determining the temperature influence coefficient based on this, the electrical parameters under different temperature conditions can be converted to equivalent values ​​under standard conditions.

[0053] In specific implementation, the GIS management platform first obtains the preset standard ambient temperature from the system database. This standard temperature is usually set to 25°C, which is also the specified temperature under the standard test conditions (STC) of the photovoltaic industry. The system calculates the difference between the real-time collected ambient temperature and this standard temperature to obtain a value reflecting the deviation between the current temperature condition and the standard temperature. The temperature difference is calculated by subtracting the standard ambient temperature from the actual ambient temperature. For example, when the actual ambient temperature is 35°C, the calculated temperature difference is 10°C.

[0054] Based on the temperature characteristics of photovoltaic cells, the output voltage of the photovoltaic panel will decrease as the temperature increases, and this change is linearly related to the temperature difference. The system determines the temperature influence coefficient based on the temperature coefficient of the photovoltaic panel (usually between -0.3% / ℃ and -0.4% / ℃) and the calculated temperature difference. The specific calculation method is: the temperature influence coefficient is equal to 1 minus the product of the temperature coefficient and the temperature difference. For example, when the temperature coefficient is -0.35% / ℃ and the temperature difference is 10℃, the calculated temperature influence coefficient is 0.965, which means that under the current temperature conditions, the output voltage will decrease by 3.5%.

[0055] This temperature difference-based influence coefficient calculation method provides an important correction basis for the performance evaluation of photovoltaic panels. Through this coefficient, the system can convert the voltage values ​​measured under different temperature conditions into equivalent values ​​under standard temperature conditions, making the data collected at different times and seasons comparable. This standardization process eliminates the interference of ambient temperature changes on fault judgment and improves the accuracy of fault diagnosis.

[0056] S203, using the current influence coefficient and the temperature influence coefficient as correction coefficients.

[0057] Based on the above embodiment, as an optional implementation, in S102, correcting the first fault score according to the correction coefficient to generate the second fault score of the target photovoltaic panel specifically includes: Substitute the current influence coefficient and the temperature influence coefficient into the correction formula to generate the second fault score of the target photovoltaic panel; wherein the correction formula is: S2=I1ω1|ΔI|+ω2|ΔV|+T1ω3|ΔT| Wherein, S2 is the second fault score, I1 is the current influence coefficient, ω1 is the first weight coefficient, ΔI is the first difference, ω2 is the second weight coefficient, ΔV is the second difference, T1 is the temperature influence coefficient, ω3 is the third weight coefficient, and ΔT is the third difference.

[0058] In specific implementation, the GIS management platform uses the correction formula S2 = I1ω1|ΔI|+ω2|ΔV|+T1ω3|ΔT| to generate the second fault score. In this formula, the current influence coefficient I1 acts on the current deviation term |ΔI|, reflecting the influence of light intensity on the output current; the temperature influence coefficient T1 acts on the temperature deviation term |ΔT|, reflecting the influence of ambient temperature on the performance of photovoltaic panels; and the voltage deviation term |ΔV| is directly involved in the calculation because the voltage is affected by multiple factors.

[0059] The three weight coefficients ω1, ω2 and ω3 in the formula correspond to the weights of current deviation, voltage deviation and temperature deviation respectively. These weight coefficients are set based on the working characteristics of the photovoltaic panel and actual operation and maintenance experience. Usually, since current and voltage are the direct determinants of the output power of the photovoltaic panel, their corresponding weight coefficients ω1 and ω2 will be set to larger values, while the weight coefficient ω3 of temperature deviation is relatively small to reflect the different importance of various parameters to fault judgment.

[0060] The purpose of using the absolute value sign in the correction formula is to ensure that whether the parameter deviation is positive or negative, it will have a corresponding impact on the fault score. This treatment method meets the actual needs of photovoltaic panel fault diagnosis, because any abnormal deviation of the parameter may indicate a potential fault.

[0061] When calculating the second fault score, the system first substitutes the acquired current influence coefficient I1 and temperature influence coefficient T1 into the formula, and then combines the deviation values ​​of various parameters obtained by real-time monitoring to obtain the final second fault score S2 through weighted calculation. This score more accurately reflects the operating status of the photovoltaic panel under the current environmental conditions, and provides a reliable basis for subsequent fault judgment.

[0062] S103, acquiring historical operation data of the target photovoltaic panel, and correcting the second fault score according to the historical operation data to generate a target fault score of the target photovoltaic panel.

[0063] During specific implementation, the GIS management platform first extracts the fault records of the target photovoltaic panel within a preset time period (for example, the past 3 months) from the historical operation data stored in the data processing layer. The system counts the number of failures of the target photovoltaic panel within this time period and compares it with the preset fault frequency threshold (preset number of times). When the number of failures obtained by statistics is greater than the preset number of times, it means that the photovoltaic panel has frequent failures. The system will obtain a preset first reduction coefficient (for example, 0.8) less than 1, and multiply the second fault score by this coefficient to obtain a lower target fault score. This processing method reflects the system's conservative evaluation strategy for equipment with frequent failures. The reduced score will prompt operation and maintenance personnel to inspect the equipment more frequently.

[0064] On the contrary, when the number of failures is less than or equal to the preset number, it indicates that the photovoltaic panel is running relatively stably, and the system will obtain a preset first improvement coefficient greater than 1 (for example, 1.2), multiply the second fault score by the coefficient, and obtain a relatively high target fault score. This score improvement reflects the system's trust in the equipment with good historical performance, and can also reduce unnecessary maintenance work.

[0065] Based on the above embodiment, as an optional implementation, in S103, the second fault score is corrected according to the historical operation data to generate the target fault score of the target photovoltaic panel, which specifically includes S401-S403: S401, obtaining the number of failures of a target photovoltaic panel within a preset time period from historical operation data.

[0066] S402, when the number of faults is greater than a preset number, obtaining a preset first reduction coefficient, and arithmetically multiplying the second fault score by the first reduction coefficient to obtain a target fault score.

[0067] Potential systemic problems. In order to more accurately reflect the impact of such historical failure records on equipment reliability, it is necessary to introduce the failure frequency factor into the failure score and adjust the score by reducing the coefficient to provide a more realistic failure assessment result.

[0068] In specific implementation, the GIS management platform first reads the historical fault records of the target photovoltaic panel from the database, counts the number of faults, and compares it with the fault number threshold preset by the system. When the number of faults obtained by statistics exceeds the preset number, the system will automatically trigger the score adjustment mechanism. The preset number is usually set based on the design life of the photovoltaic panel and the industry operation and maintenance experience. For example, the preset number can be set to the upper limit of the number of allowable faults within a year.

[0069] The system then obtains the preset first reduction coefficient from the configuration library. This coefficient is usually set to a positive number less than 1, such as 0.8 or 0.9. The selection of the specific value needs to take into account the characteristics of the equipment and the operation and maintenance requirements. The second fault score is arithmetically multiplied by the first reduction coefficient to obtain the final target fault score. This simple multiplication operation can effectively reduce the score of frequently faulty equipment, making it easier to be judged as an object that needs special attention or replacement.

[0070] For example, if the second fault score of a photovoltaic panel is 85 points and the number of historical faults has exceeded the preset number, the system uses the first reduction coefficient of 0.85 to adjust the final target fault score to 72.25 points. This reduced score better reflects the actual condition of the equipment and provides a more accurate reference for subsequent maintenance decisions.

[0071] This scoring adjustment mechanism based on the frequency of failures enables a dynamic assessment of equipment reliability. By introducing a reduction factor, the system can promptly identify problematic equipment that requires special attention, helping operation and maintenance personnel to develop more targeted maintenance strategies. At the same time, this scoring mechanism also provides an objective basis for equipment upgrade and transformation decisions, helping to optimize equipment management and resource allocation.

[0072] S403, when the number of faults is less than or equal to the preset number, obtain a preset first improvement coefficient, and arithmetically multiply the second fault score by the first improvement coefficient to obtain a target fault score.

[0073] In specific implementation, the GIS management platform first queries the historical fault records of the target photovoltaic panel in the database, counts the number of faults, and compares it with the fault number threshold preset by the system. When the number of faults obtained is less than or equal to the preset number, it indicates that the photovoltaic panel has a good operating record, and the system will start the score improvement mechanism. The preset number is usually determined based on the normal operating parameters and industry standards of the photovoltaic panel. For example, it can be set as the allowable number of faults within half a year.

[0074] The system then obtains the preset first improvement coefficient from the configuration library. This coefficient is usually set to a positive number slightly greater than 1, such as 1.1 or 1.15. The selection of the specific value needs to balance the incentive effect and the rationality of the score. The second fault score is multiplied by the first improvement coefficient to obtain the final target fault score. This calculation method can moderately improve the score of equipment in good operating condition, reflecting the system's positive evaluation of stable operating equipment.

[0075] For example, if the second fault score of a photovoltaic panel is 92 points and its historical fault count is lower than the preset number, the system uses the first improvement factor of 1.08 to adjust and finally obtain the target fault score of 99.36 points. This improved score better reflects the excellent operating status of the equipment and helps to identify and protect equipment with stable performance.

[0076] Specifically, the setting of the first reduction coefficient is mainly based on the following factors: first, the aging characteristics of the equipment. According to the design life and performance attenuation curve of the photovoltaic panels, frequent failures usually indicate that the equipment has entered the accelerated attenuation stage, and the attenuation rate may reach 1.2-1.5 times the normal level. Therefore, the reduction coefficient is usually set between 0.7-0.85; secondly, maintenance cost considerations. The maintenance cost of equipment with frequent failures is significantly higher than that of normal equipment, which may reach 1.5-2 times. This also supports setting the reduction coefficient within this range; finally, the chain reaction of failures must also be considered. Frequently failed equipment may affect the operating efficiency of adjacent components. The setting of the reduction coefficient needs to reflect this potential risk.

[0077] The setting of the first improvement coefficient takes the following factors into consideration: first, the stability premium of the equipment. A low failure rate indicates that the equipment has good reliability and its actual value is higher than the nominal value. This premium is usually between 5% and 15%, so the improvement coefficient is generally set between 1.05 and 1.15; second, maintenance cost savings. Stable equipment can significantly reduce maintenance investment. This savings effect supports a certain score improvement; finally, the demonstration effect must also be considered. Well-functioning equipment can serve as a management benchmark and its experience has promotion value.

[0078] In practice, the specific values ​​of these two coefficients need to be dynamically adjusted in combination with the actual operating data of the power station. For example, if it is found that the equipment in a certain area generally performs well, the coefficient can be appropriately reduced to maintain the discrimination of the scoring system; on the contrary, if the failure rate of a certain type of equipment is generally high, the coefficient can be appropriately adjusted to highlight the identification of problematic equipment. Through this dynamic adjustment mechanism, it is ensured that the scoring system can accurately reflect the differences in the operating status of the equipment and provide a reliable basis for maintenance decisions.

[0079] S104: When the target fault score is lower than a preset score, determining that the target photovoltaic panel is a faulty photovoltaic panel.

[0080] After obtaining the target fault score of the target photovoltaic panel, a scientific fault judgment standard needs to be established to accurately identify the faulty equipment. The GIS management platform compares the target fault score with the preset score pre-set by the system. When the target fault score is lower than the preset score, the target photovoltaic panel can be judged as a faulty photovoltaic panel. This fault judgment method based on scoring thresholds converts complex multi-parameter evaluation results into clear fault judgment results, which facilitates operation and maintenance personnel to make maintenance decisions quickly.

[0081] The preset score setting is based on the statistical analysis results of a large amount of historical operating data, taking into account factors such as the model specifications, service life, and operating environment of the photovoltaic panels. The system adopts a hierarchical preset scoring mechanism, setting differentiated preset scoring standards for photovoltaic panels of different types or different working environments.

[0082] For example, for newly installed photovoltaic panels, a higher preset score can be set to ensure a higher operating standard; while for photovoltaic panels with a longer service life, the preset score standard can be appropriately lowered to avoid excessive maintenance.

[0083] When the system determines that a photovoltaic panel is a faulty panel, the application display layer of the GIS management platform will immediately mark the icon of the photovoltaic panel as a faulty state on the electronic map, usually using a striking red or flashing effect to mark it. At the same time, the system will automatically generate fault alarm information, including key information such as the location information of the faulty photovoltaic panel, fault score data, historical operation records, etc. This information is integrated through the data processing layer of the GIS management platform to form a complete fault report.

[0084] Based on the spatial management advantages of the GIS management platform, the system will automatically plan the optimal maintenance route and visualize it on the electronic map. This combination of fault location and spatial information greatly improves the work efficiency of operation and maintenance personnel and shortens the fault response time. At the same time, the system will store the fault record in the database for subsequent statistical analysis and equipment management decisions.

[0085] S105, marking the location of the faulty photovoltaic panel on the electronic map of the GIS management platform, and generating a maintenance task for the faulty photovoltaic panel.

[0086] In specific implementation, the GIS management platform first updates the icon of the faulty photovoltaic panel to the preset fault status style on the electronic map interface of the application display layer, usually using red flashing special effects to highlight it. The system also marks the key information of the faulty photovoltaic panel at the location, including equipment number, fault score, fault type, etc. This intuitive visual display method enables operation and maintenance personnel to understand the spatial distribution and fault severity of the faulty equipment at a glance.

[0087] While marking the location, the GIS management platform will automatically generate a standardized maintenance task. The task contains detailed information about the faulty photovoltaic panel, such as the specific installation location coordinates of the faulty photovoltaic panel, the photovoltaic array number to which it belongs, abnormal operating parameters, historical maintenance records, etc. The system will also determine the urgency of the fault based on the value of the target fault score and set the priority of the maintenance task accordingly. For example, when the target fault score is significantly lower than the preset score, the system will mark the maintenance task as high priority and require the operation and maintenance personnel to handle it first.

[0088] In order to improve maintenance efficiency, the GIS management platform will automatically plan the optimal maintenance route based on the spatial analysis function of the electronic map, combined with the road network data and the current location information of the maintenance personnel. The system considers multiple factors to optimize the route, including the priority of the maintenance task, the distance between maintenance points, and road conditions. The optimized maintenance route is directly displayed on the electronic map with eye-catching path lines, and detailed navigation information is provided.

[0089] In addition, the GIS management platform will automatically match the maintenance tools and spare parts list required for the fault type, and provide spare parts information based on inventory conditions. The system integrates all relevant information of the maintenance task into a complete work order and pushes it to the relevant operation and maintenance personnel through the mobile terminal. This intelligent work order push mechanism ensures the timely delivery of maintenance information and the effective execution of tasks.

[0090] Based on the above embodiment, as an optional implementation, in S105, marking the location of the faulty photovoltaic panel on the electronic map of the GIS management platform specifically includes S501-S503: S501, when the target fault score is less than a first preset score, marking the target photovoltaic panel with a first color so that an operator can perform a routine inspection.

[0091] S502: When the target fault score is not less than the first preset score and less than the second preset score, the target photovoltaic panel is marked with a second color so that the operator can perform regular maintenance.

[0092] S503, when the target fault score is not less than the second preset score, the target photovoltaic panel is marked with a third color so that the operator can perform emergency maintenance.

[0093] In specific implementation, the GIS management platform first needs to set two key preset scores as the criteria for the scoring level. The first preset score is usually set in the range of 60-70 points, representing the critical point where the equipment changes from a normal operating state to a state that requires attention; the second preset score is usually set in the range of 80-85 points, indicating that the equipment has entered a state that requires emergency treatment. The determination of these preset scores requires comprehensive consideration of factors such as the equipment's operating characteristics, maintenance costs, and failure risks.

[0094] When the system calculates the fault score of the target photovoltaic panel, it will automatically compare it with the two preset scores and take corresponding marking measures based on the comparison results. Specifically, when the fault score is less than the first preset score, the system marks the photovoltaic panel as green (first color), indicating that the equipment is in normal operation and only needs to be inspected and maintained according to the regular plan. Equipment in this state usually focuses on preventive maintenance, and the inspection cycle can be relatively long, such as once a month.

[0095] When the fault score is not less than the first preset score but less than the second preset score, the system marks the photovoltaic panel in yellow (second color), indicating that the equipment has shown certain abnormal signs and needs to be monitored and maintained. Equipment in this state needs to be regularly inspected and maintained, and the inspection cycle may need to be shortened to once a week, and special attention needs to be paid to the specific parameter changes that lead to the increase in the score.

[0096] When the fault score is not less than the second preset score, the system marks the photovoltaic panel in red (third color), indicating that the equipment may have a serious fault risk and immediate measures need to be taken. The equipment in this state needs to start the emergency maintenance procedure, which may require the first inspection to be completed within 24 hours, and a detailed maintenance plan to be formulated based on the inspection results.

[0097] Generate a maintenance task for a faulty photovoltaic panel, including: determining a maintenance priority according to a target fault score; generating a maintenance route according to location information of a target photovoltaic panel; and generating a maintenance task including a maintenance priority, target photovoltaic panel location information and a maintenance route.

[0098] In specific implementation, the system first determines the maintenance priority based on the target fault score. For red-marked equipment with a fault score not less than the second preset score, the system sets it to the highest priority and requires that the maintenance must be completed within 24 hours; for yellow-marked equipment with a fault score between the first preset score and the second preset score, it is set to a medium priority and requires that the maintenance be completed within a week; for green-marked equipment with a fault score less than the first preset score, it is set to a regular priority and is executed according to the monthly maintenance plan.

[0099] After determining the priority, the system will read the location information of the target photovoltaic panel, including its specific coordinates in the photovoltaic array, the area number to which it belongs, and the characteristics of the surrounding environment. This location information is crucial for developing an efficient maintenance route. The system uses an intelligent path planning algorithm to comprehensively consider multiple factors to generate the optimal maintenance route: first, consider the priority of the equipment to ensure that high-priority equipment can be processed first; second, consider the proximity of geographical locations, merge the maintenance tasks of adjacent areas, and reduce the round-trip time of maintenance personnel; finally, consider site conditions and weather factors to select the appropriate maintenance time and route.

[0100] The system integrates this information to generate a complete maintenance task, which includes: maintenance priority identification to guide the urgency of task execution; detailed location information of the target photovoltaic panel, including area number, arrangement number and specific coordinates; optimized maintenance route map, showing the optimal path from the maintenance base to each maintenance point; necessary maintenance tools and safety protection requirements; estimated maintenance time and a specific list of maintenance items. This information is pushed to maintenance personnel through mobile terminals to ensure that they can clearly understand the task requirements and execution path.

[0101] Based on the above method, the present application also discloses a one-stop management and operation system of new energy based on GIS, such as Figure 2 As shown, Figure 2 : is a structural diagram of a one-stop management and operation system of new energy based on GIS provided in an embodiment of the present application. The system includes: an acquisition module, a generation module, a correction module, a determination module and a generation module; wherein: An acquisition module is used to send the operating parameters of the target photovoltaic panel in the photovoltaic array to the GIS management platform, and then obtain a first fault score of the target photovoltaic panel generated by the GIS management platform according to the operating parameters; a generation module is used to obtain environmental data of the environment in which the target photovoltaic panel is located, generate a correction coefficient according to the environmental data, and correct the first fault score according to the correction coefficient to generate a second fault score of the target photovoltaic panel; a correction module is used to obtain historical operating data of the target photovoltaic panel, correct the second fault score according to the historical operating data, and generate a target fault score of the target photovoltaic panel; a determination module is used to determine that the target photovoltaic panel is a faulty photovoltaic panel when the target fault score is lower than a preset score; a generation module is used to mark the location of the faulty photovoltaic panel on the electronic map of the GIS management platform, and generate a maintenance task for the faulty photovoltaic panel.

[0102] It should be noted that: when the system provided in the above embodiment realizes its functions, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0103] See also Figure 3 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 3 As shown, the electronic device 1000 may include: at least one processor 1001 , at least one network interface 1004 , a user interface 1003 , a memory 1005 , and at least one communication bus 1002 .

[0104] The communication bus 1002 is used to realize the connection and communication between these components.

[0105] The user interface 1003 may include a display screen (Display) and a camera (Camera), and the optional user interface 1003 may also include a standard wired interface and a wireless interface.

[0106] The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0107] Among them, the processor 1001 may include one or more processing cores. The processor 1001 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 1005, and calling data stored in the memory 1005. Optionally, the processor 1001 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 1001 can integrate one or more combinations of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 1001, and it can be implemented separately through a chip.

[0108] Among them, the memory 1005 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 1005 includes a non-transitory computer-readable storage medium. The memory 1005 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 1005 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 1005 may optionally be at least one storage device located away from the aforementioned processor 1001. As Figure 3 As shown, the memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program of a one-stop management and operation method of new energy based on GIS.

[0109] exist Figure 3 In the electronic device 1000 shown, the user interface 1003 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 1001 can be used to call an application stored in the memory 1005 for a one-stop management and operation method of new energy based on GIS. When executed by one or more processors, the electronic device executes one or more methods described in the above embodiments.

[0110] An electronic device readable storage medium stores instructions, which, when executed by one or more processors, enable the electronic device to execute one or more of the methods described in the above embodiments.

[0111] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0112] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0113] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0114] 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 distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0115] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0116] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0117] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the specification and practicing the disclosure here, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field not recorded in the present disclosure. The description and examples are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A one-stop management and operation method for new energy based on GIS, characterized in that: The method comprises: After the operating parameters of the target photovoltaic panel in the photovoltaic array are sent to the GIS management platform, a first fault score of the target photovoltaic panel generated by the GIS management platform according to the operating parameters is obtained; Acquiring environmental data of an environment in which the target photovoltaic panel is located, generating a correction coefficient according to the environmental data, and correcting the first fault score according to the correction coefficient to generate a second fault score for the target photovoltaic panel; Acquire historical operation data of the target photovoltaic panel, and modify the second fault score according to the historical operation data to generate a target fault score of the target photovoltaic panel; When the target fault score is lower than a preset score, determining that the target photovoltaic panel is a faulty photovoltaic panel; The location of the faulty photovoltaic panel is marked on the electronic map of the GIS management platform, and a maintenance task for the faulty photovoltaic panel is generated.

2. The one-stop management and operation method of new energy based on GIS according to claim 1 is characterized in that: The operating parameters include current, voltage and temperature, and the obtaining the first fault score of the target photovoltaic panel generated by the GIS management platform according to the operating parameters includes: Calculating a first difference between the current and a preset current, a second difference between the voltage and a preset voltage, and a third difference between the temperature and a preset temperature; Substituting the first difference, the second difference and the third difference into the fault scoring formula to generate a first fault score for the target photovoltaic panel; wherein, The fault scoring formula is: S1=ω1|ΔI|+ω2|ΔV|+ω3|ΔT|; Wherein, S1 is the first fault score, ω1 is the first weight coefficient, ΔI is the first difference, ω2 is the second weight coefficient, ΔV is the second difference, ω3 is the third weight coefficient, and ΔT is the third difference.

3. The one-stop management and operation method of new energy based on GIS according to claim 2 is characterized in that: The environmental data includes light intensity and ambient temperature, and generating a correction coefficient according to the environmental data includes: Obtaining a preset standard light intensity, calculating a ratio of the light intensity to the standard light intensity, and determining the current influence coefficient according to the ratio; Obtaining a preset standard ambient temperature, calculating a temperature difference between the ambient temperature and the standard ambient temperature, and determining the temperature influence coefficient according to the temperature difference; The current influence coefficient and the temperature influence coefficient are used as correction coefficients.

4. The one-stop management and operation method of new energy based on GIS according to claim 3 is characterized in that: The correcting the first fault score according to the correction coefficient to generate a second fault score for the target photovoltaic panel includes: Substituting the current influence coefficient and the temperature influence coefficient into the correction formula to generate a second fault score of the target photovoltaic panel; wherein, The correction formula is: S2=I1ω1|ΔI|+ω2|ΔV|+T1ω3|ΔT|; Wherein, S2 is the second fault score, I1 is the current influence coefficient, ω1 is the first weight coefficient, ΔI is the first difference, ω2 is the second weight coefficient, ΔV is the second difference, T1 is the temperature influence coefficient, ω3 is the third weight coefficient, and ΔT is the third difference.

5. The one-stop management and operation method of new energy based on GIS according to claim 1 is characterized in that: The step of correcting the second fault score according to the historical operation data to generate a target fault score for the target photovoltaic panel includes: Obtaining the number of failures of the target photovoltaic panel within a preset time period from the historical operation data; When the number of failures is greater than a preset number, obtaining a preset first reduction coefficient, and arithmetically multiplying the second failure score by the first reduction coefficient to obtain the target failure score; When the number of faults is less than or equal to the preset number, a preset first improvement coefficient is obtained, and the second fault score is arithmetically multiplied by the first improvement coefficient to obtain the target fault score.

6. The one-stop management and operation method of new energy based on GIS according to claim 1 is characterized in that: The step of marking the location of the faulty photovoltaic panel on the electronic map of the GIS management platform includes: When the target fault score is less than a first preset score, the target photovoltaic panel is marked with a first color so that an operator can perform a routine inspection; When the target fault score is not less than the first preset score and less than a second preset score, marking the target photovoltaic panel with a second color so that the operator can perform regular maintenance; When the target fault score is not less than the second preset score, the target photovoltaic panel is marked with a third color so that the operator can perform emergency maintenance.

7. The one-stop management and operation method of new energy based on GIS according to claim 1 is characterized in that: The generating of the maintenance task of the faulty photovoltaic panel comprises: Determining maintenance priorities according to the target fault scores; Generate a maintenance route according to the location information of the target photovoltaic panel; A maintenance task including the maintenance priority, the target photovoltaic panel location information and the maintenance route is generated.

8. The one-stop management and operation system of new energy based on GIS is characterized by: The system includes: an acquisition module, a generation module, a correction module, a determination module and a generation module; wherein, The acquisition module is used to send the operating parameters of the target photovoltaic panel in the photovoltaic array to the GIS management platform, and then acquire the first fault score of the target photovoltaic panel generated by the GIS management platform according to the operating parameters; The generating module is used to obtain environmental data of the environment in which the target photovoltaic panel is located, generate a correction coefficient according to the environmental data, and correct the first fault score according to the correction coefficient to generate a second fault score of the target photovoltaic panel; The correction module is used to obtain the historical operation data of the target photovoltaic panel, and correct the second fault score according to the historical operation data to generate a target fault score of the target photovoltaic panel; The determination module is configured to determine that the target photovoltaic panel is a faulty photovoltaic panel when the target fault score is lower than a preset score; The generation module is used to mark the location of the faulty photovoltaic panel on the electronic map of the GIS management platform, and to generate a maintenance task for the faulty photovoltaic panel.

9. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 7.

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