Annual failure rate assessment method of lightning arresters for offshore wind farms considering lightning randomness

Abstract

The invention discloses a method for evaluating the annual failure rate of lightning arresters in an offshore wind farm considering the randomness of lightning, belonging to the field of lightning protection for offshore wind farms, and comprising the following steps: S1, confirming the electrical parameters prone to exceeding limits; S2, calculating the failure probability of a lightning arrester for a single lightning strike based on the electrical parameters prone to exceeding limits; S3, obtaining the cumulative probability of lightning current amplitude; S4, obtaining the interval failure probability of the lightning arrester considering the cumulative probability of lightning current amplitude; S5, considering the lightning attraction area of the wind turbines in the offshore wind farm, and calculating the annual lightning strike failure rate of the lightning arresters in the offshore wind farm based on the interval failure probability of the lightning arrester. By adopting the above method for evaluating the annual failure rate of lightning arresters in an offshore wind farm considering the randomness of lightning, through incorporating the randomness of lightning, realizing quantitative failure calculation and comprehensive analysis of multiple parameters to support the selection of lightning arresters, the technical upgrade of the reliability analysis of lightning arresters in offshore wind farms from qualitative to quantitative and from theory to application is completed.

Description

Technical Field

[0001] The present invention relates to the technical field of lightning protection for offshore wind farms, and particularly to a method for evaluating the annual failure rate of arresters in offshore wind farms considering the randomness of lightning. Background Art

[0002] Offshore wind power has been developing rapidly as an important part of clean energy. Among them, the arrester is the core lightning protection equipment of the electrical system of offshore wind turbines, and its operating reliability directly affects the safe and stable operation of the wind farm.

[0003] To determine its stability, the prior art needs to analyze the electrical stress of the arrester, and the analysis means are as follows: (1) Analysis object: a single arrester under specific working conditions; (2) Evaluation index: whether the voltage, current, and energy exceed the limit; (3) Simulation means: using electromagnetic transient software such as PSCAD / EMTP; (4) Failure criterion: deterministic analysis based on threshold comparison.

[0004] Since the construction of offshore wind farms changes the local atmospheric electric field and affects the characteristics of cloud-to-ground lightning activities, and the lightning parameters (lightning current amplitude, lightning return stroke type) have significant randomness, the existing analysis means have the following defects:

[0005] 1. Evaluation limitation: only targeting a single arrester, it cannot reflect the overall lightning protection performance of the wind farm;

[0006] 2. Defect of calculation model: ignoring the probability distribution characteristics of lightning parameters and lacking differential analysis of different return stroke orders;

[0007] 3. Insufficient engineering application: unable to quantify the annual failure rate index of arresters in offshore wind farms, and it is difficult to support the optimization decision of arrester selection. Summary of the Invention

[0008] The purpose of the present invention is to provide a method for evaluating the annual failure rate of arresters in offshore wind farms considering the randomness of lightning to solve the above technical problems.

[0009] To achieve the above purpose, the present invention provides a method for evaluating the annual failure rate of arresters in offshore wind farms considering the randomness of lightning, including the following steps:

[0010] S1. Build a lightning electromagnetic transient simulation model of an offshore wind turbine, and conduct lightning strikes simulations under multiple return stroke orders to obtain the change results of the electrical stress parameters of the arrester in the offshore wind turbine. Based on the change results of the electrical stress parameters of the arrester, confirm the electrical parameters that are prone to exceeding the limit;

[0011] S2. Based on the electrical parameters that are prone to exceeding the limit, use the Weibull distribution to calculate the failure probability of the arrester for a single lightning strike;

[0012] S3. Obtain the statistical results of offshore lightning parameters based on the data of the lightning location system, and obtain the cumulative probability of lightning current amplitude based on the statistical results of offshore lightning parameters;

[0013] S4. Divide the lightning current into intervals, and based on the median lightning current of the divided intervals, combined with the single-stroke arrester failure probability described in step S2 and the cumulative probability of lightning current amplitude described in step S3, obtain the arrester interval failure probability considering the cumulative probability of lightning current amplitude;

[0014] S5. Considering the lightning attraction area of the wind turbines in the offshore wind farm, calculate the annual lightning strike failure rate of the arresters in the offshore wind farm based on the arrester interval failure probability described in step S4.

[0015] Preferably, in step S1, use PSCAD electromagnetic transient simulation software for segmented modeling to obtain the offshore wind turbine lightning electromagnetic transient simulation model:

[0016] Establish a chain equivalent circuit for the downlead of the offshore wind turbine blade, nacelle, tower barrel and cable respectively;

[0017] Model the arrester and surge protector using non-linear resistors;

[0018] Model the transformer using a high-frequency model;

[0019] Use the ground capacitance to equivalent the high-frequency characteristics during the lightning strike of the switchgear at the bottom of the tower barrel;

[0020] Use Comsol finite element software to calculate the coupling capacitance between the tower barrel and the cable armor layer, between the cable armor layer and the shielding layer, between the cable shielding layers, and between the cable shielding layer and the core wire;

[0021] Use the Heidler function to simulate the lightning current waveform, and set the lightning current waveform corresponding to the positive single-stroke to 22 / 230 μs, the lightning current waveform corresponding to the negative single-stroke to 2.6 / 50 μs, the lightning current waveform corresponding to the positive first return stroke to 10 / 350 μs, the lightning current waveform corresponding to the negative first return stroke to 1 / 200 μs, and the lightning current waveforms corresponding to the subsequent positive and negative return strokes to 0.25 / 100 μs;

[0022] The electrical stress parameters described in step S1 include voltage, current, and energy; the electrical parameters prone to exceedance are determined based on the critical values of voltage, current, and energy, including voltage and current.

[0023] Preferably, in step S2, set the division interval of the lightning current to 5 kA, and divide it into intervals. At this time, conduct lightning strike simulations for the th interval and the th stroke order, and use the Weibull distribution to calculate the Interval Failure probability of single lightning arrester under different return stroke sequences ,

[0024] (1);

[0025] in,

[0026] (2);

[0027] (3);

[0028] In the formula, For the Interval Voltage amplitude of lightning arrester under different return stroke sequences Exceeding the residual voltage under the rated discharge current of the arrester The voltage failure probability of a single lightning strike arrester; For the Interval Lightning current amplitude under different return stroke sequences Exceeding the rated discharge current of the arrester The probability of arrester failure due to a single lightning strike; An intermediate amount.

[0029] Preferably, step S3 specifically includes the following steps:

[0030] S31. Use ArcGIS geographic software to filter the lightning current data of the sea area where the offshore wind farm is located in the lightning location system data, record each return stroke as a lightning strike, and count the return stroke density in the corresponding area. , the proportion of various return stroke sequences and the lightning current amplitude characteristics corresponding to each return stroke sequence;

[0031] Among them, each return stroke sequence ratio includes the positive polarity single lightning stroke ratio , Negative polarity single lightning strike ratio , Positive polarity first strike ratio , Negative polarity first strike ratio , Positive polarity follow-up strike ratio , Negative polarity follow-up strike ratio ;

[0032] S32. Using the lightning current amplitude cumulative probability function in IEEE, the lightning current amplitude corresponding to each return stroke sequence is fitted to obtain the cumulative probability of the lightning current amplitude. ,in .

[0033] Preferably, the lightning current amplitude cumulative probability function expression described in step S32 is as follows:

[0034] (4);

[0035] Wherein, represents the magnitude of the lightning current at the -th return stroke order exceeding the critical lightning current probability; is the lightning current magnitude parameter; is the shape parameter;

[0036] Thus, the cumulative probabilities of positive single - strike ratio, negative single - strike ratio, positive first - return stroke ratio, negative first - return stroke ratio, positive subsequent - return stroke ratio, negative subsequent - return stroke ratio , , , , , .

[0037] Preferably, in step S4, based on step S2, the cumulative probabilities of positive single - strike ratio, negative single - strike ratio, positive first - return stroke ratio, negative first - return stroke ratio, positive subsequent - return stroke ratio, negative subsequent - return stroke ratio , , , , , are obtained; combined with the lightning current magnitude cumulative probability described in step S3, calculate the probability of the failure interval of the arrester considering the lightning current magnitude cumulative probability at the -th return stroke order in the -th interval:

[0038] (5);

[0039] Wherein, and are respectively the upper and lower limits of the lightning current in the -th interval.

[0040] Preferably, step S5 specifically includes the following steps:

[0041] S51. Set the lightning attracting area of a single wind turbine as the circular area with the wind turbine as the center and three times the height of the wind turbine as the radius. Obtain the lightning attracting area of a single wind turbine based on the circular area calculation formula, and then multiply it by the number of wind turbines in the offshore wind farm to get the total lightning attracting area ;

[0042] S52. Based on the return stroke density and the total lightning attracting area , calculate the annual lightning strike times of the wind turbines in the offshore wind farm :

[0043] (6);

[0044] S53. Combine the probability of the arrester failure interval , and calculate the annual lightning strike failure rate of the arresters in the offshore wind farm :

[0045] (7).

[0046] Therefore, the present invention adopts the above-mentioned method for evaluating the annual failure rate of arresters in an offshore wind farm considering the randomness of lightning, and has the following beneficial effects:

[0047] 1. Considering the randomness of lightning: Breaking through the traditional single working condition analysis, integrating the random characteristics such as lightning current amplitude and return stroke order, and being closer to the actual lightning strike scenario;

[0048] 2. Quantitative evaluation of failure: Quantifying the failure rate with the help of models such as Weibull distribution, carrying out quantitative failure evaluation for the arresters of the entire wind farm, changing the traditional local and qualitative evaluation mode, and improving the analysis accuracy;

[0049] 3. Comprehensive analysis of multiple parameters: Combining the over-limit parameters of voltage and current to calculate the failure probability, comprehensively covering the influencing factors of arrester failure, and making the evaluation more scientific.

[0050] The technical solution of the present invention will be further described in detail below with reference to the drawings and embodiments. Description of the Drawings

[0051] Figure 1 is the flowchart of a method for evaluating the annual failure rate of arresters in an offshore wind farm considering the randomness of lightning according to the present invention;

[0052] Figure 2 is the equivalent circuit diagram of the lightning strike electromagnetic transient simulation model of an offshore wind turbine in the simulation experiment of the present invention;

[0053] Figure 3This is the curve graph of the electrical stress parameter variation in the simulation experiment of the present invention. Among them, (a) is the curve graph of the arrester voltage variation, (b) is the curve graph of the arrester current variation, and (c) is the curve graph of the arrester energy variation. Detailed implementation manners

[0054] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the following further describes the embodiments of the present invention in detail with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the embodiments of the present invention, and are not used to limit the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of this application. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions throughout.

[0055] It should be noted that the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or server that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products or devices.

[0056] The following further describes the embodiments of the present invention in detail with reference to the drawings.

[0057] As Figure 1 shown, a method for evaluating the annual failure rate of arresters in an offshore wind farm considering the randomness of lightning includes the following steps:

[0058] S1. Build a lightning electromagnetic transient simulation model for an offshore wind turbine, conduct lightning simulations under multiple strike sequences, obtain the variation results of the electrical stress parameters of the arrester in the offshore wind turbine, and confirm the electrical parameters that are prone to exceed the limit based on the variation results of the electrical stress parameters of the arrester;

[0059] In step S1, use the PSCAD electromagnetic transient simulation software to perform segmented modeling to obtain a lightning electromagnetic transient simulation model for an offshore wind turbine:

[0060] Respectively establish a chain equivalent circuit for the lightning conductor of the offshore wind turbine blade, nacelle, tower barrel and cable;

[0061] Use non-linear resistors to model arresters and surge protectors;

[0062] Use a high-frequency model to model the transformer;

[0063] Use the ground capacitance to equivalent the high-frequency characteristics during the lightning strike process of the switchgear at the bottom of the tower barrel;

[0064] Use Comsol finite element software to calculate the coupling capacitances between the tower barrel and the cable armor layer, between the cable armor layer and the shielding layer, between the cable shielding layers, and between the cable shielding layer and the core wire;

[0065] Use the Heidler function to simulate the lightning current waveform, and set the lightning current waveform corresponding to a single positive lightning strike to 22 / 230 μs, the lightning current waveform corresponding to a single negative lightning strike to 2.6 / 50 μs, the lightning current waveform corresponding to the first positive return stroke to 10 / 350 μs, the lightning current waveform corresponding to the first negative return stroke to 1 / 200 μs, and the lightning current waveforms corresponding to subsequent positive and negative return strokes to 0.25 / 100 μs;

[0066] The electrical stress parameters described in step S1 include voltage, current, and energy; based on the critical values of voltage, current, and energy, the electrical parameters prone to exceeding the limit include voltage and current.

[0067] S2. Based on the electrical parameters prone to exceeding the limit, use the Weibull distribution to calculate the failure probability of the lightning arrester for a single lightning strike;

[0068] In step S2, set the division interval of the lightning current to 5 kA, and divide it into intervals. At this time, perform lightning strike simulations for the th interval and the th return stroke order, and use the Weibull distribution to calculate the failure probability of the lightning arrester for a single lightning strike in the th interval and the th return stroke order ,

[0069] (1);

[0070] Among them,

[0071] (2);

[0072] (3);

[0073] In the formula, is the failure probability of the lightning arrester voltage for a single lightning strike when the voltage amplitude in the th interval and the th return stroke order exceeds the residual voltage under the nominal discharge current of the lightning arrester (i.e., the critical lightning voltage) ; is the failure probability of the lightning arrester current for a single lightning strike when the current amplitude in the th interval and the th return stroke order exceeds the nominal discharge current of the lightning arrester (i.e., the critical lightning current) ; is an intermediate quantity.

[0074] S3. Based on the data of the lightning location system, obtain the statistical results of the offshore lightning parameters, and obtain the cumulative probability of the lightning current amplitude based on the statistical results of the offshore lightning parameters;

[0075] Step S3 specifically includes the following steps:

[0076] S31. Use the Arcgis geographic software to screen the lightning current data in the sea area where the offshore wind farm is located in the lightning location system data, and record each return stroke as a lightning strike, and count the return stroke density in the corresponding area , the proportion of various return stroke orders, and the lightning current amplitude characteristics corresponding to each return stroke order;

[0077] Among them, the proportion of each return stroke order includes the proportion of positive single lightning strikes , the proportion of negative single lightning strikes , the proportion of positive first return strokes , the proportion of negative first return strokes , the proportion of positive subsequent return strokes , the proportion of negative subsequent return strokes ;

[0078] S32. Use the cumulative probability function of the lightning current amplitude in IEEE to fit the lightning current amplitude corresponding to each return stroke order to obtain the cumulative probability of the lightning current amplitude , where .

[0079] The expression of the cumulative probability function of the lightning current amplitude described in step S32 is as follows:

[0080] (4);

[0081] In the formula, represents the probability that the lightning current amplitude exceeds the critical lightning current under the th return stroke order; is the lightning current amplitude parameter; is the shape parameter;

[0082] Thus, the cumulative probabilities under the proportion of positive single lightning strikes , the proportion of negative single lightning strikes , the proportion of positive first return strokes , the proportion of negative first return strokes , the proportion of positive subsequent return strokes , and the proportion of negative subsequent return strokes are obtained respectively; , , , , .

[0083] S4. Divide the lightning current into intervals, and based on the median lightning current of the divided intervals, combine the single-stroke arrester failure probability described in step S2 and the lightning current amplitude cumulative probability described in step S3 to obtain the arrester interval failure probability considering the lightning current amplitude cumulative probability;

[0084] In step S4, based on step S2, obtain the proportion of positive single-stroke lightning , the proportion of negative single-stroke lightning , the proportion of positive first return stroke , the proportion of negative first return stroke , the proportion of positive subsequent return strokes , the proportion of negative subsequent return strokes under the , , , , , ; Combine the lightning current amplitude cumulative probability , calculate the arrester failure interval probability in the th interval and the th return stroke order considering the lightning current amplitude cumulative probability :

[0085] (5);

[0086] In the formula, and are respectively the upper and lower limits of the lightning current in the th interval.

[0087] S5. Considering the lightning attracting area of the wind turbines in the offshore wind farm, calculate the annual lightning strike failure rate of the arresters in the offshore wind farm based on the arrester interval failure probability described in step S4.

[0088] Step S5 specifically includes the following steps:

[0089] S51. Set the lightning attracting area of a single wind turbine as the circular area with the wind turbine as the center and three times the height of the wind turbine as the radius. Obtain the lightning attracting area of a single wind turbine based on the circular area calculation formula, and then multiply it by the number of wind turbines in the offshore wind farm to get the total lightning attracting area ;

[0090] S52. Based on the return stroke density and the total lightning attracting area , calculate the annual lightning strike times of the wind turbines in the offshore wind farm :

[0091] (6);

[0092] S53. Combine the probability of the arrester failure interval , calculate the annual lightning strike failure rate of the arresters in the offshore wind farm :

[0093] (7).

[0094] Simulation experiment

[0095] Using the design of a certain 35kV typical wind turbine in the offshore wind farm, build the offshore wind turbine lightning electromagnetic transient simulation model as shown in Figure 2 . Under the condition of a lightning current amplitude of 200kA, carry out lightning strikesimulation under 6 kinds of return stroke sequences, and conduct maximum voltage, current, and energy analysis for arrester #1 and arrester #2. The results are shown in Table 1.

[0096] Table 1 Arrester electrical stress

[0097] ;

[0098] Set the critical values of voltage, current, and energy of the 35kV arrester to 134kV, 5kA, and 80.4kJ respectively. According to the simulation results in Table 1, under the condition of a lightning current amplitude of 200kA, the voltage and current of the arrester are likely to exceed the threshold, while the energy is much smaller than the threshold (reason: taking the voltage, current, and energy of arrester #1 under 0.25 / 100μs as shown in Figure 3 as an example, it can be seen that although the voltage and current exceed the design threshold, due to the short transient time, the energy does not exceed the limit), so the voltage and current are taken as the electrical parameters that are likely to exceed the limit.

[0099] At the same time, through statistics, the return stroke density of this area is obtained as 12.68 times / (km 2 •a), and use the geographical software Arcgis to screen all the data of the offshore wind farms in the lightning location system of this area from 2010 to 2023 for a total of ten years, and obtain the proportion of 6 kinds of return stroke sequences as shown in Table 2.

[0100] Table 2 Proportion of 6 kinds of return stroke sequences

[0101] ;

[0102] Furthermore, fit with the lightning current amplitude cumulative probability function as shown in Table 3.

[0103] Table 3 Lightning current amplitude cumulative probability function parameters

[0104] ;

[0105] Then, take the lower limit of the lightning current amplitude as 0 kA and the upper limit as 250 kA. Divide it into 50 intervals with each interval being 5 kA. Use the median of each interval as the lightning current amplitude to represent the interval. Calculate the single - strike arrester failure probability using formula (1). For example, under the first negative - polarity return stroke, the arrester failure probabilities in the lightning current amplitude intervals [90 kA, 95 kA], [95 kA, 100 kA], [100 kA, 105 kA], [105 kA, 110 kA] are the values corresponding to the 19th, 20th, 21st, and 22nd intervals in Table 4, respectively , , and .

[0106] Table 4 Single - strike arrester failure probability

[0107] ;

[0108] Further calculate the arrester failure interval probability as shown in Table 5 using formula (5).

[0109] Table 5 Arrester failure interval probability

[0110] ;

[0111] At this time, set the calculated result of the lightning - attracting area of the wind turbines in this offshore wind farm as 27.71 km 2 , and the return - stroke density is 12.68 times / (km 2 •year). Calculate the annual lightning strike times of the wind turbines in this wind farm as 351.3628 times using formula (6), and then calculate the annual lightning strike failure rate of the arresters in the offshore wind farm as shown in Table 6 using formula (7).

[0112] Table 6 Annual lightning strike failure rate of arresters in offshore wind farm ;

[0113] Set the nominal current of arrester #1 and arrester #2 as 5 kA or 10 kA, and further compare the annual failure rates of arresters in the offshore wind farm under different arrester selection types, as shown in Table 7 below

[0114] Table 7 Failure rates of arresters under different selections

[0115] ;

[0116] As can be seen from Table 7, by only changing the nominal current of one lightning arrester, the annual failure rate of the lightning arresters in this wind farm can be reduced by 70%, which proves that the calculation of the annual failure rate proposed in the present invention can also provide a theoretical basis for the selection of lightning arresters for offshore wind farms.

[0117] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that they can still modify or equivalently replace the technical solutions of the present invention, and these modifications or equivalent replacements cannot make the modified technical solutions deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for evaluating the annual failure rate of lightning arresters in offshore wind farms considering the randomness of lightning, characterized by: The following steps are involved: S1. Build an electromagnetic transient simulation model for lightning strikes on offshore wind turbines, and perform lightning strike simulations under various return stroke sequences to obtain the results of changes in electrical stress parameters of lightning arresters in offshore wind turbines, and confirm electrical parameters that are prone to exceeding limits based on the results of changes in electrical stress parameters of lightning arresters; S2. Based on the easily exceeded electrical parameters, the failure probability of the arrester under a single lightning strike is calculated using the Weibull distribution; S3. Based on the data of the lightning location system, obtain the statistical results of offshore lightning parameters, and obtain the cumulative probability of lightning current amplitude based on the statistical results of offshore lightning parameters; In step S2, the lightning current division interval is set to 5kA, which is divided into interval, then conduct the Interval The lightning simulation under the return stroke sequence is carried out, and the Weibull distribution is used to calculate the Interval Failure probability of single lightning arrester under different return stroke sequences , （1）； in, （2）； （3）； In the formula, For the Interval Voltage amplitude of lightning arrester under different return stroke sequences Exceeding the residual voltage under the rated discharge current of the arrester The voltage failure probability of a single lightning strike arrester; For the Interval The current amplitude of the arrester under the return stroke sequence Exceeding the rated discharge current of the arrester The failure probability of a single lightning arrester current; is the intermediate amount; S4, dividing the lightning current into intervals, and based on the median of the lightning current in the divided intervals, combined with the single lightning strike arrester failure probability described in step S2 and the cumulative probability of the lightning current amplitude described in step S3, obtaining the arrester failure interval probability considering the cumulative probability of the lightning current amplitude; S5. Considering the lightning induction area of ​​wind turbines in the offshore wind farm, the annual lightning failure rate of lightning arresters in the offshore wind farm is calculated based on the arrester failure interval probability described in step S4.

2. The method for evaluating the annual failure rate of lightning arresters in offshore wind farms considering the randomness of lightning according to claim 1 is characterized in that: In step S1, PSCAD electromagnetic transient simulation software is used to perform segmented modeling to obtain an offshore wind turbine lightning electromagnetic transient simulation model: Establish chain equivalent circuits for the offshore wind turbine blade downconductors, nacelles, towers and cables respectively; Modeling lightning arresters and surge protectors using nonlinear resistors; Modeling transformers using high-frequency models; Utilize the high-frequency characteristics of the lightning strike during the equivalent tower bottom switchgear capacitance to ground; Comsol finite element software is used to calculate the coupling capacitance between the tower and the cable armor layer, between the cable armor layer and the shield layer, between the shield layers of the cable, and between the cable shield layer and the core wire; The Heidler function is used to simulate the lightning current waveform, and the lightning current waveform corresponding to a single positive lightning stroke is set to 22 / 230μs, the lightning current waveform corresponding to a single negative lightning stroke is set to 2.6 / 50μs, the lightning current waveform corresponding to the first positive return stroke is set to 10 / 350μs, the lightning current waveform corresponding to the first negative return stroke is set to 1 / 200μs, and the lightning current waveform corresponding to subsequent positive and negative return strokes is set to 0.25 / 100μs. The electrical stress parameters described in step S1 include voltage, current, and energy; the electrical parameters that are easily exceeded based on the critical values ​​of voltage, current, and energy include voltage and current.

3. The method for evaluating the annual failure rate of lightning arresters in offshore wind farms considering the randomness of lightning according to claim 2 is characterized in that: Step S3 specifically includes the following steps: S31. Use ArcGIS geographic software to filter the lightning current data of the sea area where the offshore wind farm is located in the lightning location system data, record each return stroke as a lightning strike, and count the return stroke density in the corresponding area. , the proportion of various return stroke sequences and the lightning current amplitude characteristics corresponding to each return stroke sequence; Among them, each return stroke sequence ratio includes the positive polarity single lightning stroke ratio , Negative polarity single lightning strike ratio , Positive polarity first strike ratio , Negative polarity first strike ratio , Positive polarity follow-up strike ratio , Negative polarity follow-up strike ratio ; S32. Using the lightning current amplitude cumulative probability function in IEEE, the lightning current amplitude corresponding to each return stroke sequence is fitted to obtain the cumulative probability of lightning current amplitude. ,in .

4. The method for evaluating annual failure rate of lightning arresters in offshore wind farms considering lightning randomness according to claim 3 is characterized in that: The lightning current amplitude cumulative probability function expression described in step S32 is as follows: （4）； In the formula, Indicates Lightning current amplitude under different return stroke sequences Exceeding critical lightning current probability; is the lightning current amplitude parameter; is the shape parameter; Thus, the proportion of positive polarity single lightning strike is obtained , Negative polarity single lightning strike ratio , Positive polarity first strike ratio , Negative polarity first strike ratio , Positive polarity follow-up strike ratio , Negative polarity follow-up strike ratio Cumulative probability under lightning current amplitude , , , , , .

5. The method for evaluating annual failure rate of lightning arresters in offshore wind farms considering lightning randomness according to claim 4 is characterized in that: In step S4, based on step S2, the proportion of positive polarity single lightning strikes is obtained. , Negative polarity single lightning strike ratio , Positive polarity first strike ratio , Negative polarity first strike ratio , Positive polarity follow-up strike ratio , Negative polarity follow-up strike ratio Next , , , , , Combined with the cumulative probability of lightning current amplitude described in step S3 , calculate the Interval Considering the cumulative probability of lightning current amplitude under the return stroke sequence The probability of arrester failure interval : （5）； In the formula, and Respectively The upper and lower limits of lightning current in the interval.

6. The method for evaluating annual failure rate of lightning arresters in offshore wind farms considering lightning randomness according to claim 5 is characterized in that: Step S5 specifically includes the following steps: S51. Set the lightning attraction area of ​​a single wind turbine to the area of ​​a circle with the wind turbine as the center and three times the wind turbine height as the radius. Obtain the lightning attraction area of ​​a single wind turbine based on the circle area calculation formula, and then multiply it by the number of wind turbines in the offshore wind farm to obtain the total lightning attraction area. ; S52, based on the return density and total lightning area , calculate the annual number of lightning strikes on wind turbines in offshore wind farms : （6）； S53, combined with the arrester failure interval probability , calculate the annual lightning failure rate of lightning arresters in offshore wind farms : （7）。

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