A Method for Calculating the Wind Resistance of Photovoltaic Power Plants Based on Large Eddy Simulation

Abstract

The invention discloses a method for calculating wind resistance of photovoltaic power station based on large eddy simulation, comprising the following steps: S1, extracting relevant parameters of photovoltaic panels of photovoltaic power station; S2, extracting ultrasonic observation historical data of wind tower near photovoltaic power station and large eddy simulation refined forecast data centered on photovoltaic power station; S3, obtaining the forecast amount of wind resistance parameters required for wind resistance calculation of photovoltaic panels and the characteristics of wind resistance parameters of wind resistance calculation of photovoltaic panels; S4, correcting the forecast amount of wind resistance parameters obtained by refined forecast data using the characteristics of wind resistance parameters obtained by ultrasonic observation data, and dynamically adjusting the forecast of wind resistance parameters; S5, calculating wind resistance of photovoltaic panels. The invention improves the accuracy and initiative of wind resistance calculation of photovoltaic power station.

Description

Technical Field

[0001] The invention relates to the technical field of electrical digital data processing, and in particular to a method for calculating wind resistance of a photovoltaic power station based on large eddy simulation. Background Art

[0002] Photovoltaic modules are composed of photovoltaic cells with similar performance and suitable size, which are arranged in series or in parallel and then assembled. However, the size of photovoltaic cells is relatively large. If subjected to large wind loads, the strength and rigidity of the solar photovoltaic panels themselves may not meet the use requirements, which may cause the solar photovoltaic panels to break or deform significantly, and may also cause the solar photovoltaic panels to fail to work normally or reduce the photoelectric conversion efficiency. With the annual increase in my country's photovoltaic industry, the threat of strong winds to the safety of the photovoltaic industry has become increasingly serious, and the number of cases of strong winds destroying photovoltaic modules has also increased.

[0003] The impact of strong winds on photovoltaic equipment is mainly manifested in two aspects: first, extreme strong winds will affect the safety of solar panels, causing photovoltaic modules to be overturned by strong winds; second, extreme strong winds will reduce the anti-corrosion performance of the bracket. It can be seen that strong winds have a great impact on the normal safe production and stable operation of photovoltaic power stations.

[0004] At present, the research on wind resistance of photovoltaic panels is mainly focused on the wind-induced response of photovoltaic components and the optimization of wind load design. The wind resistance calculation of photovoltaic power stations still relies on the continuous strengthening of meteorological monitoring and forecasting and the timely issuance of strong wind warnings. Therefore, an accurate and quantifiable method for calculating the wind resistance of photovoltaic panels is urgently needed. Summary of the invention

[0005] The purpose of the present invention is to provide a method for calculating the wind resistance of a photovoltaic power station based on large eddy simulation, which can obtain the predicted values ​​of key wind resistance parameters from the ultrasonic observation data of a wind tower near the photovoltaic power station and the refined forecast data of a large eddy simulation centered on the photovoltaic power station, and calculate the wind resistance performance of a photovoltaic panel through a comprehensive comparative analysis of influencing factors such as the stress of screws fixing the photovoltaic panel, the weight and material of the photovoltaic panel.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] The present invention provides a method for calculating wind resistance of a photovoltaic power station based on large eddy simulation, comprising the following steps:

[0008] S1. Extract the geometric parameters of the photovoltaic panels of the photovoltaic power station and the parameters of the screws fixing the photovoltaic panels, obtain the density of the photovoltaic panels and obtain the wind-resistant area of ​​the photovoltaic panels according to the installation angle, as well as the stress of the screws fixing the photovoltaic panels;

[0009] S2, extracting the ultrasonic observation historical data of the wind tower near the photovoltaic power station and the large eddy simulation refined forecast data centered on the photovoltaic power station;

[0010] S3. Analyze the refined forecast data of large eddy simulation to obtain the forecast of wind resistance parameters required for wind resistance calculation of photovoltaic panels, analyze the historical data of ultrasonic observation of wind measurement towers, and compare and analyze to obtain the characteristics of wind resistance parameters required for wind resistance calculation of photovoltaic panels;

[0011] S4. Correct the wind resistance parameter forecast obtained by the refined forecast data using the wind resistance parameter characteristics obtained by the ultrasonic observation data, and dynamically adjust the forecast of the wind resistance parameters;

[0012] S5. Calculate the wind resistance of photovoltaic panels using the corrected wind resistance parameter forecast, photovoltaic panel property parameters, and the stress of screws fixing photovoltaic panels.

[0013] Furthermore, the large eddy simulation refined forecast data centered on the photovoltaic power station described in step S2 includes forecast data during the historical strong wind process calculated back and real-time refined forecast simulation data, and the calculated and real-time refined large eddy simulation data include Hertz-level wind speed and temperature simulated after parameterized observation and terrain processing.

[0014] Furthermore, the analysis of the historical data of ultrasonic observations of the wind tower described in step S3 is specifically as follows: the Hertz-level data of the ultrasonic observations are averaged at different time scales including seconds, minutes, and 10 minutes, and characteristic quantity statistics including variance, extreme value, turbulence intensity, and gust coefficient are performed on the processed data at different time scales.

[0015] Furthermore, the refined forecast data of the large eddy simulation described in step S3 is analyzed, specifically: the refined simulation data calculated back during the historical strong wind process are averaged at different time scales including seconds, minutes, and 10 minutes, and the characteristic quantity statistics including variance, extreme value, turbulence intensity, and gust coefficient are performed on the processed data at different time scales.

[0016] Furthermore, in step S3, the characteristics of the wind resistance parameters of the photovoltaic panel wind resistance measurement are obtained, specifically: by comparing and analyzing various statistical characteristic quantities of different time scales of the processed ultrasonic observations and the corresponding back-calculated forecasts, the key wind resistance parameters reflecting the wind resistance performance are obtained, and the characteristics of the key wind resistance parameters are obtained.

[0017] Furthermore, in step S4, the forecast of the wind resistance parameters is dynamically adjusted, and the processing method is as follows: the Hertz-level forecast data of the large eddy real-time simulation is corrected according to the characteristics of the key wind resistance parameters, and different correction coefficients are used according to different wind speed ranges.

[0018] Furthermore, the method for calculating the wind resistance of photovoltaic panels in step S5 is as follows: the refined Hertz-level wind speed data of the real-time simulation of the large eddy centered on the photovoltaic power station is averaged at the second and minute levels, and key wind resistance parameters including the maximum wind speed and turbulence intensity at different time scales are obtained; after correction and processing, and in combination with the density of the photovoltaic panels and the wind resistance area, the wind-induced stress of the photovoltaic panels at each moment is obtained according to the wind resistance calculation model of the photovoltaic panels; the wind-induced stress at each moment is compared with the wind resistance stress threshold; if the wind-induced stress at this moment is greater than the wind resistance stress threshold, it is determined that the photovoltaic panel at this moment may be overturned by strong winds; the different levels of wind resistance performance of the photovoltaic panel are determined according to the difference between the wind-induced stress and the wind resistance stress threshold; the above processing and discrimination are performed moment by moment to obtain the wind resistance calculation results of the photovoltaic panels at each moment during the forecast period.

[0019] Furthermore, the photovoltaic panel wind resistance measurement result described in step S5 is the moment-by-moment wind-induced stress value of the photovoltaic panel and the moment-by-moment wind resistance performance of the photovoltaic panel during the forecast period.

[0020] Furthermore, the screw stress for fixing the photovoltaic panel in step S1 is specifically calculated as the sum of the screw stress for fixing the photovoltaic panel according to the screw specification, the screw stress cross-sectional area and the number of screws for fixing the photovoltaic panel.

[0021] Furthermore, the ultrasonic observation historical data of the wind tower near the photovoltaic power station described in step S2 includes taking the photovoltaic power station as the center, selecting a wind tower that is close to the photovoltaic power station and has similar terrain and topography as a reference point, and extracting the ultrasonic observation data of the strong wind process with a wind speed greater than level 6 observed by the wind tower in history

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] The photovoltaic panel wind resistance calculation method of the present invention compares and analyzes the ultrasonic observation data of the wind tower near the photovoltaic power station with the refined Hertz-level data of the large eddy simulation centered on the photovoltaic power station, finds the key wind resistance parameters reflecting the wind resistance performance, and analyzes its characteristics for the correction of the results of the large eddy simulation forecast. With the photovoltaic power station as the main body and a single photovoltaic panel as the research unit, the photovoltaic panel wind-induced stress values ​​at each moment and the photovoltaic panel wind resistance calculation results at each moment of the forecast period are comprehensively calculated for the different natural properties of photovoltaic panels in different photovoltaic power stations. The method of the present invention is the application of large eddy simulation technology in the field of photovoltaic panel wind resistance calculation, which improves the accuracy and initiative of photovoltaic power station wind resistance calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0025] Figure 1 A flow chart of a method for calculating wind resistance of a photovoltaic power station based on large eddy simulation provided by an embodiment of the present invention;

[0026] Figure 2 This is the time series diagram of minute-level strong winds after processing the ultrasonic observation (20HZ) of the wind tower (a total of 1080 minutes);

[0027] Figure 3 This is the time series diagram of minute-level wind speed turbulence intensity after processing the ultrasonic observation (20HZ) of the wind tower (a total of 360 minutes);

[0028] Figure 4 Comparison of the maximum wind time series between ultrasonic observations from a wind tower and simulation forecasts;

[0029] Figure 5 This is the time series diagram of the corrected maximum wind and the observed maximum wind;

[0030] Figure 6 A schematic diagram of a specific calculation process of the wind resistance performance of a photovoltaic panel provided by an embodiment of the present invention;

[0031] Figure 7 A first application case diagram provided for an embodiment of the present invention;

[0032] Figure 8 A second application case diagram provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0034] The present invention provides a method for calculating wind resistance of photovoltaic power station based on large eddy simulation, the process is as follows: Figure 1 As shown, the following steps are included:

[0035] S1. Extract the geometric parameters of the photovoltaic panels of the photovoltaic power station and the parameters of the screws fixing the photovoltaic panels, obtain the density of the photovoltaic panels and obtain the wind-resistant area of ​​the photovoltaic panels according to the installation angle, as well as the stress of the screws fixing the photovoltaic panels.

[0036] The geometric parameters of the photovoltaic panels of the photovoltaic power station described in step S1 include the length, width, height and weight of the photovoltaic panels used in the power station. The density of the photovoltaic panels is calculated based on the above geometric parameters, and the wind-resistant area of ​​the photovoltaic panels is calculated in combination with the installation angle of the photovoltaic panels.

[0037] The parameters of the screws used to fix the photovoltaic panels in the photovoltaic power station described in step S1 include screw specifications, screw stress cross-sectional area, and the number of screws fixing the photovoltaic panels. The total stress of the screws fixing the photovoltaic panels can be calculated based on the above screw parameters.

[0038] S2. Extract the historical data of ultrasonic observation of wind towers near photovoltaic power stations and the refined forecast data of large eddy simulation centered on photovoltaic power stations.

[0039] The ultrasonic observation historical data of the wind tower near the photovoltaic power station described in step S2 includes taking the photovoltaic power station as the center, selecting a wind tower that is close to the photovoltaic power station and has similar terrain and topography as a reference point, and extracting the ultrasonic observation data of the strong wind process with a wind speed greater than level 6 observed by the wind tower in history.

[0040] The large eddy simulation refined forecast data centered on the photovoltaic power station described in step S2 includes forecast data during the back-calculated historical strong wind process and real-time refined forecast simulation data. The back-calculated historical strong wind process is consistent with the time of the strong wind process screened according to the observation data of the wind tower. The back-calculated and real-time refined large eddy simulation data are Hertz-level wind speed, temperature, etc. simulated after parameterized observation and terrain processing.

[0041] S3. Analyze the refined forecast data of large eddy simulation to obtain the forecast of wind resistance parameters required for wind resistance measurement of photovoltaic panels, analyze the historical data of ultrasonic observation of wind measurement towers, and obtain the characteristics of wind resistance parameters for wind resistance measurement of photovoltaic panels.

[0042] The analysis of the historical data of ultrasonic observations of the wind tower described in step S3 is processed by averaging the observed Hertz-level data at different time scales such as seconds, minutes, and 10 minutes, and performing statistics on characteristic quantities such as variance, extreme value, turbulence intensity, and gust coefficient on the processed data at different time scales.

[0043] The processing method of analyzing the refined forecast data of the large eddy simulation described in step S3 is as follows: the refined simulation data calculated back during the historical strong wind process are averaged at different time scales such as seconds, minutes, and 10 minutes, and the variance, extreme value, turbulence intensity, gust coefficient and other characteristic quantity statistics of the processed data at different time scales are performed.

[0044] In step S3, in order to obtain the characteristics of the wind resistance parameters of the photovoltaic panel wind resistance measurement, it is necessary to compare and analyze the statistical results of the characteristic quantities after ultrasonic observation processing of the above-mentioned wind measurement tower and the various statistical characteristic quantities of the corresponding time scale predicted by the large eddy simulation back calculation, so as to obtain the key wind resistance parameters (wind speed extreme value, turbulence intensity, etc.) that can reflect the wind resistance performance, and obtain the characteristics of the key wind resistance parameters (correction method and correction coefficient, etc.).

[0045] The key wind resistance parameters reflecting wind resistance performance obtained in step S3 include the extreme value of strong wind speed and turbulence intensity. The extreme value of strong wind speed is generally greater than 10.8m / s (level 6 wind). Figure 2 This is a minute-level strong wind time series diagram after ultrasonic observation (20HZ) processing at a certain period of time in 2011 at a wind tower in Inner Mongolia. The wind speed exceeded 20m / s continuously during the strongest period, and the strongest was close to 30m / s (level 11 wind). Turbulence intensity describes the degree to which wind speed changes with time and space, and is a dimensionless quantity. Figure 3 This is a time series diagram of minute-level wind speed turbulence intensity after processing of ultrasonic observations (20HZ) from a wind tower. The intensity reaches 0.2~0.3, with the strongest reaching 0.6.

[0046] The characteristics of the key wind resistance parameters obtained in step S3 are as follows: Figure 4 As shown in the figure, there is a certain difference in the minute-level strong wind after processing the ultrasonic observation of the wind tower (20HZ) and the refined forecast data of large eddy simulation (20HZ). It is necessary to correct the deviation of the wind speed forecast of large eddy simulation, and different systematic deviations can be obtained for different wind speed sections. Different photovoltaic power stations have different wind speed correction coefficients. Figure 5 This is the time series diagram of the corrected wind speed extreme value.

[0047] S4. The wind resistance parameter characteristics obtained by ultrasonic observation data are used to correct the wind resistance parameter forecast obtained by refined forecast data, and the forecast of wind resistance parameters is dynamically adjusted.

[0048] Step S4 dynamically adjusts the forecast of the wind resistance parameters of the large eddy simulation. The processing method is: according to the characteristics of the key wind resistance parameters obtained above, the Hertz-level forecast data of the large eddy real-time simulation is corrected. Generally, different correction coefficients are used according to different wind speed sections, so as to achieve the effect of dynamically adjusting the forecast.

[0049] S5. Calculate the wind resistance of photovoltaic panels using the corrected wind resistance parameter forecast, photovoltaic panel property parameters, and the stress of screws fixing photovoltaic panels.

[0050] Step S5: The method for calculating the wind resistance of photovoltaic panels is:

[0051] The refined Hertzian wind speed data of the real-time simulation of the large eddy centered on the photovoltaic power station is averaged at the second and minute levels, and the key wind resistance parameters such as the maximum wind speed and turbulence intensity at different time scales are obtained. After correction and processing, combined with the density of photovoltaic panels and the wind resistance area, the wind-induced stress F of the photovoltaic panel at each moment is obtained according to the photovoltaic panel wind resistance calculation model. The specific formula is: F=C*I*A*ρ*U*2, where C is the coefficient, I is the turbulence intensity, A is the density of photovoltaic panels, U is the maximum wind, and the coefficient C is obtained through CFD (computational fluid dynamics) experiments and is a fixed value. The wind-induced stress at each moment is calculated by the above formula and compared with the wind resistance stress threshold. If the wind-induced stress at this moment is greater than the wind resistance stress threshold, it is determined that the photovoltaic panel at this moment may be overturned by strong wind. The wind resistance performance level of the photovoltaic panel can be judged according to the difference between the wind-induced stress and the wind resistance stress threshold. The above processing and judgment are performed moment by moment, and the wind resistance calculation results of the photovoltaic panel at each moment during the forecast period can be obtained.

[0052] The photovoltaic panel wind resistance measurement result described in step S5 is the moment-by-moment wind-induced stress value of the photovoltaic panel and the quantitative wind resistance performance of the photovoltaic panel at each moment during the forecast period.

[0053] The present invention comprehensively considers the geometric properties (including the length, width, height and weight of the photovoltaic panels of the photovoltaic power station) and the properties of the screws fixing the photovoltaic panels (screw specifications, screw stress cross-sectional area, screw weight, etc.), and combines the ultrasonic observation of the wind measurement tower near the photovoltaic power station to dynamically adjust the refined-level forecast data of the large eddy simulation centered on the photovoltaic power station. The wind-induced stress is comprehensively calculated according to the above factors, and compared and analyzed with the wind stress threshold to obtain the wind resistance measurement result of the photovoltaic power station.

[0054] The method for calculating wind resistance of a photovoltaic power station based on large eddy simulation provided by an embodiment of the present invention comprises the following specific steps:

[0055] (1) Geometric parameters of photovoltaic panels: basic information such as the length, width, height, weight, and installation angle of photovoltaic panels in photovoltaic power stations.

[0056] (2) Processing of PV panel geometric parameters: The density of the PV panels is calculated using the sorted PV panel geometric parameters as one of the fixed parameters that must be considered in the measurement model. The area of ​​the PV panels is also calculated, and the wind-resistant area is calculated in combination with the installation angle.

[0057] (3) Sorting out the properties of screws used to fix photovoltaic panels: Sorting out screw specifications, corresponding screw stress cross-sectional areas, and the number of screws used to fix a single photovoltaic panel.

[0058] (4) Calculation of screw stress processing: Calculate the total screw stress of the photovoltaic panel based on the screw specifications, screw stress cross-sectional area, and the number of screws fixing a single photovoltaic panel.

[0059] (5) Compilation of ultrasonic observation data from the wind tower: Compilation of ultrasonic observation data from the wind tower during strong winds with wind speeds greater than level 6.

[0060] (6) Processing of ultrasonic observation data from wind towers: The observed Hertz-level data are averaged at different time scales, such as seconds, minutes, and 10 minutes. The variance, extreme value, turbulence intensity, gust coefficient and other characteristic quantities of the processed data at different time scales are statistically analyzed.

[0061] (7) Large eddy simulation refined forecast data compilation: Large eddy simulation refined forecast data includes the forecast data during the back-calculated historical strong wind process and the real-time refined simulation forecast data. The back-calculated historical strong wind process is consistent with the time of the strong wind process selected in (5).

[0062] (8) Large eddy simulation forecast data processing: The refined simulation data calculated back during the historical strong wind process are averaged at different time scales such as seconds, minutes, and 10 minutes. The variance, extreme value, turbulence intensity, gust coefficient and other characteristic quantities of the processed data at different time scales are statistically analyzed.

[0063] (9) Obtaining the characteristics of key wind resistance parameters for wind resistance measurement: Based on the comparative analysis of various statistical characteristic quantities of wind tower observation data and large eddy simulation data of the same period at different time scales, the key wind resistance parameters that can reflect the wind resistance performance are obtained, and the characteristics of the key wind resistance parameters, such as correction methods and correction coefficients, are obtained.

[0064] (10) Real-time correction of large eddy simulation (LES) refined data: The real-time LES refined forecast data is corrected according to the characteristics of the key wind resistance parameters of the photovoltaic panels.

[0065] (11) Determination of the wind resistance calculation results of photovoltaic panels.

[0066] Among them, Figure 6 As shown, the process of calculating the wind resistance of photovoltaic panels in each photovoltaic power station is as follows:

[0067] The first step is data extraction and organization, including the extraction of wind resistance parameter correction coefficients, the extraction of photovoltaic panel geometric parameters and screw property parameters, the extraction and processing of large eddy simulation data, and the correction of key wind resistance parameters.

[0068] In the second step, the wind-induced stress is calculated using the photovoltaic panel wind-resistant measurement model through the corrected wind-resistant parameters, the density of the photovoltaic panel, the wind-resistant area and other influencing factors, and compared with the photovoltaic panel wind-resistant stress threshold (the photovoltaic panel wind-resistant stress threshold is proportional to the sum of the screw stress of the photovoltaic panel + the weight of the screw and the photovoltaic panel). If the wind-induced stress is less than the wind-resistant stress threshold, it can be determined that the wind-resistant performance at this moment is the best. If the wind-induced stress is greater than the wind-resistant stress threshold, different wind-resistant performance may be produced, and the wind-resistant performance level can be determined based on the difference between the two. Alternatively, since the weight of the screws and photovoltaic panels is relatively small compared to the sum of the screw stress, the wind-resistant stress threshold can be the sum of the screw stress.

[0069] Based on the above calculation logic, corresponding analysis and judgment are carried out at each moment, especially for the period when strong wind may occur, and finally the moment-by-moment wind-induced stress value of the photovoltaic panel and the moment-by-moment wind resistance measurement results of the photovoltaic panel during the forecast period are obtained.

[0070] like Figure 7 , 8 As shown, the photovoltaic power station wind resistance calculation method based on large eddy simulation of the present invention has been verified on individual cases of a 20MW photovoltaic array in Inner Mongolia being blown over by strong winds on September 22, 2022, and a case in which photovoltaic power stations in many places in Jiangxi suffered severe impacts from strong convective weather on March 31, 2024. It can be found that during strong wind periods, according to the photovoltaic panel wind resistance calculation method of the present invention, the wind-induced stress values ​​at multiple times are greater than the wind resistance stress threshold. According to the above-mentioned corresponding wind resistance calculation results, reasonable plans for construction and operation and maintenance of various links in the generation operation of photovoltaic power stations can be made.

[0071] In summary, the present invention can be used for different photovoltaic power station environments. According to the geometric properties of the photovoltaic panels and the specifications of the screws for fixing the photovoltaic panels, combined with the observation data of the wind tower near the photovoltaic power station, the large eddy simulation forecast results centered on the photovoltaic power station can be dynamically adjusted, and more accurate wind resistance measurement results can be given after comprehensive calculation, thereby providing technical support for the operation and maintenance of the power station.

[0072] The above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the aforementioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the aforementioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical specialties therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application. They should all be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for calculating wind resistance of photovoltaic power stations based on large eddy simulation, characterized in that: The following steps are involved: S1. Extract the geometric parameters of the photovoltaic panels of the photovoltaic power station and the parameters of the screws fixing the photovoltaic panels, obtain the density of the photovoltaic panels and obtain the wind-resistant area of ​​the photovoltaic panels according to the installation angle, as well as the stress of the screws fixing the photovoltaic panels; S2, extracting the ultrasonic observation historical data of the wind tower near the photovoltaic power station and the large eddy simulation refined forecast data centered on the photovoltaic power station; S3. Analyze the refined forecast data of large eddy simulation to obtain the forecast of wind resistance parameters required for wind resistance measurement of photovoltaic panels, analyze the historical data of ultrasonic observation of wind towers, and compare and analyze to obtain the characteristics of wind resistance parameters for wind resistance measurement of photovoltaic panels; S4. Correct the wind resistance parameter forecast obtained by the refined forecast data using the wind resistance parameter characteristics obtained by the ultrasonic observation data, and dynamically adjust the forecast of the wind resistance parameters; S5, using the revised multiple parameters including wind resistance parameter forecast, photovoltaic panel property parameters, and stress of screws fixing the photovoltaic panel to calculate the wind resistance of the photovoltaic panel; The analysis of the historical data of ultrasonic observation of the wind tower described in step S3 is specifically: averaging the Hertz-level data of ultrasonic observation at different time scales including second level, minute level and 10-minute level, and performing characteristic quantity statistics including variance, extreme value, turbulence intensity and gust coefficient on the processed data at different time scales; The step S3 of analyzing the refined forecast data of the large eddy simulation is specifically as follows: the refined simulation data calculated back during the historical strong wind process are averaged at different time scales including the second level, minute level, and 10-minute level, and the characteristic quantity statistics including variance, extreme value, turbulence intensity, and gust coefficient are performed on the processed data at different time scales; In step S3, the characteristics of the wind resistance parameters of the photovoltaic panel wind resistance measurement are obtained, specifically: by comparing and analyzing various statistical characteristic quantities of different time scales of the processed ultrasonic observation and the corresponding back-calculated forecast, the key wind resistance parameters reflecting the wind resistance performance are obtained, and the characteristics of the key wind resistance parameters are obtained; Step S5: The method for calculating the wind resistance of photovoltaic panels is as follows: the refined Hertz-level wind speed data of the large eddy real-time simulation centered on the photovoltaic power station is averaged at the second and minute levels, and the key wind resistance parameters including the maximum wind speed and turbulence intensity at different time scales are obtained. After correction and processing, the wind-induced stress of the photovoltaic panel at each moment is obtained according to the photovoltaic panel wind resistance calculation model in combination with the photovoltaic panel density and wind resistance area. The wind-induced stress at each moment is compared with the wind resistance stress threshold. If the wind-induced stress at this moment is greater than the wind resistance stress threshold, it is determined that the photovoltaic panel at this moment may be overturned by strong winds. The different levels of wind resistance performance of the photovoltaic panel are determined according to the difference between the wind-induced stress and the wind resistance stress threshold. The above processing and discrimination are performed moment by moment to obtain the wind resistance calculation results of the photovoltaic panel at each moment during the forecast period. The photovoltaic panel wind resistance calculation result described in step S5 is the photovoltaic panel wind-induced stress value at each moment and the photovoltaic panel wind resistance performance at each moment during the forecast period.

2. The method for calculating wind resistance of a photovoltaic power station based on large eddy simulation according to claim 1, characterized in that: The large eddy simulation refined forecast data centered on the photovoltaic power station described in step S2 includes the forecast data during the historical strong wind process calculated back and the real-time refined forecast simulation data. The calculated and real-time refined large eddy simulation data include the Hertz-level wind speed and temperature simulated after parameterized observation and terrain processing.

3. The method for calculating wind resistance of a photovoltaic power station based on large eddy simulation according to claim 1, characterized in that: The forecast of the wind resistance parameters is dynamically adjusted in step S4, and the processing method is as follows: the Hertz-level forecast data of the large eddy real-time simulation is corrected according to the characteristics of the key wind resistance parameters, and different correction coefficients are used according to different wind speed ranges.

4. The method for calculating wind resistance of a photovoltaic power station based on large eddy simulation according to claim 1, characterized in that: The screw stress for fixing the photovoltaic panel in step S1 is specifically calculated based on the screw specification, the screw stress cross-sectional area and the number of screws for fixing the photovoltaic panel.

5. The method for calculating wind resistance of a photovoltaic power station based on large eddy simulation according to claim 1, characterized in that: The ultrasonic observation historical data of the wind tower near the photovoltaic power station described in step S2 includes taking the photovoltaic power station as the center, selecting a wind tower that is close to the photovoltaic power station and has similar terrain and topography as a reference point, and extracting the ultrasonic observation data of the strong wind process with a wind speed greater than level 6 observed by the wind tower in history.

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