A method and apparatus for lightning strike risk assessment of offshore wind turbines

Abstract

This application provides a method and apparatus for lightning strike risk assessment of offshore wind turbines, relating to the field of offshore lightning simulation. The method includes: constructing a thunderstorm cloud-initiated discharge model based on the electrical structure parameters of the thunderstorm cloud; constructing a spatial background electric field that evolves over time based on the thunderstorm cloud-initiated discharge model; building a leader development model based on the spatial background electric field and the corresponding size parameters of various target structural parts of the target offshore wind turbine, outputting upward discharge spatial tendency parameters; constructing an upward lightning stochastic discharge model based on the upward discharge spatial tendency parameters, and outputting upward leader evolution process parameters; constructing upward leader spatiotemporal evolution parameters corresponding to the target offshore wind turbine based on the upward leader evolution process parameters, and conducting lightning strike risk assessment using the upward leader spatiotemporal evolution parameters. This application solves the problem that existing assessment systems lack the ability to identify short-term high-risk situations, resulting in low accuracy in lightning strike risk assessment.

Description

Technical Field

[0001] This application relates to the field of marine lightning simulation, and in particular to a method and apparatus for assessing the lightning strike risk of offshore wind turbines. Background Technology

[0002] Offshore wind turbines are typically deployed in nearshore or deep-sea areas, characterized by tall towers, long blades, and a high degree of structural exposure. They are also exposed to complex meteorological environments with frequent severe convective weather, high air humidity, and high salt spray concentrations. Under thunderstorm conditions, they are more likely to become the preferred target structures for lightning strikes. Therefore, how to simulate the thunderstorm environment around offshore wind turbines and detect their lightning strike risks has become an important research issue.

[0003] Currently, existing offshore wind turbine lightning strike risk assessment systems mostly rely on empirical methods based on historical lightning strike statistics and annual average lightning strike frequency models to quantitatively estimate the probability of a wind turbine being struck by lightning in a specific area. These methods typically simplify the thunderstorm environment to a stable or uniform background electric field and treat the wind turbine as an ideal lightning conductor with a fixed geometry. They only provide long-term average lightning strike probability indicators, failing to reflect the evolution of the thunderstorm cloud's electrical structure over time, nor can they characterize the sequential triggering relationships and spatial differences between different structural components during the same thunderstorm. Therefore, existing assessment systems suffer from insufficient ability to identify short-term high-risk scenarios, resulting in low accuracy in lightning strike risk assessment.

[0004] Therefore, there is an urgent need for a method and device for assessing lightning strike risks for offshore wind turbines. Summary of the Invention

[0005] This application provides a method and apparatus for lightning strike risk assessment of offshore wind turbines, which solves the problem that existing assessment systems are not capable of identifying short-term high-risk situations, resulting in low accuracy of lightning strike risk assessment.

[0006] The first aspect of this application provides a method for assessing the lightning strike risk of offshore wind turbines. The method includes: acquiring the electrical structure parameters of thunderstorm clouds surrounding the target offshore wind turbine under lightning conditions, and constructing a thunderstorm cloud initiation discharge model based on these parameters; constructing a spatial background electric field that evolves over time based on the thunderstorm cloud initiation discharge model; building a pilot development model based on the spatial background electric field and the corresponding size parameters of various target structural parts of the target offshore wind turbine, and outputting upward discharge spatial tendency parameters based on the pilot development model. These upward discharge spatial tendency parameters include parameters that satisfy the upward discharge initiation discharge conditions under the current thunderstorm electric field. The system identifies the positional parameters of the target structural part under initial conditions, as well as the directional deviation parameters of the upward leader extending along different spatial directions after the formation of upward discharge. An upward lightning stochastic discharge model is constructed based on the upward discharge spatial tendency parameters, and upward leader evolutionary process parameters are output based on this model. These parameters represent the dynamic formation and evolution of the upward leader at the target structural part. Spatiotemporal evolution parameters of the upward leader corresponding to the target offshore wind turbine are constructed based on these parameters, and lightning strike risk assessment is performed using these parameters.

[0007] Optionally, the electrical structure parameters of thunderstorm clouds surrounding the target offshore wind turbine are obtained under lightning conditions, and a thunderstorm cloud discharge model is constructed based on these parameters. Specifically, this includes: obtaining the electrical structure parameters of thunderstorm clouds surrounding the target offshore wind turbine under lightning conditions; lightning conditions include strong electric field environments, dense salt spray environments, and high humidity environments; thunderstorm cloud electrical structure parameters include cloud-to-ground potential difference parameters, air equivalent conductivity parameters, and relative humidity parameters; and constructing a thunderstorm cloud discharge model based on these parameters by establishing a closed-loop prediction equation set. The closed-loop prediction equation set consists of atmospheric motion equations, pressure equations, thermodynamic energy equations, hydrostatic mass continuity equations, and hydrostatic charge density equations.

[0008] Optionally, a spatial background electric field evolving over time is constructed based on a thunderstorm cloud-initiated discharge model. Specifically, this includes: constraining the potential boundary conditions between the thunderstorm cloud and the ground surface based on the cloud-to-ground potential difference parameter in the thunderstorm cloud-initiated discharge model; updating the spatial distribution of the thunderstorm cloud's electrical structure parameters in a time-series manner based on the model, reflecting the evolution of the electrical structure over time during the thunderstorm cloud-initiated discharge process; calculating the corresponding potential distribution within the spatial range where the target offshore wind turbine is located after the time-series update of the thunderstorm cloud's electrical structure parameters; and obtaining the spatial background electric field by solving for the spatial variation relationship of the potential based on the potential distribution.

[0009] Optionally, a pilot development model is built based on the spatial background electric field and the dimensional parameters corresponding to each target structural part of the target offshore wind turbine. Specifically, this includes: calculating the electric field distribution at the target structural parts under the influence of the spatial background electric field, combined with the dimensional parameters corresponding to each target structural part of the target offshore wind turbine; the dimensional parameters include tower height parameters, tower top geometric curvature parameters, nacelle external dimensions parameters, and blade geometric dimensions parameters; using the dimensional parameters as modeling constraints, a pilot development model is built based on the electric field distribution.

[0010] Optionally, the upward discharge spatial tendency parameters are output based on the leader development model, specifically including: determining whether the target structure meets the initiation conditions for upward discharge based on the electric field distribution at the target structure; if the target structure meets the initiation conditions for upward discharge, the target structure is identified as a candidate initiation site; determining the spatial position parameters corresponding to the candidate initiation site, and after upward discharge is formed at the candidate initiation site, outputting the trend differences of the upward leader's development along different spatial directions under the influence of the spatial background electric field based on the leader development model; constructing corresponding directional bias parameters based on the trend differences; combining the spatial position parameters and the directional bias parameters, and outputting the upward discharge spatial tendency parameters.

[0011] Optionally, the uplink leader evolution process parameters are output based on the uplink lightning stochastic discharge model. Specifically, this includes: randomly determining the order of uplink discharge at each target structural location based on the uplink discharge spatial tendency parameter, and determining the uplink leader start time parameter corresponding to each target structural location; stochastically evolving the gradual extension behavior of the uplink leader in space based on the uplink leader start time parameter and combined with the direction bias parameter, and outputting the evolution state change of the uplink leader at the target structural location; randomly selecting the extension behavior of the uplink leader along different spatial directions at each evolution time based on the direction bias parameter, and outputting the spatial development path parameter corresponding to the uplink leader; and jointly determining the uplink leader start time parameter and the spatial development path parameter as the uplink leader evolution process parameters.

[0012] Optionally, lightning strike risk assessment is performed using uplink leader spatiotemporal evolution parameters. Specifically, this includes: assessing the likelihood of lightning strike, evaluating the distribution of lightning strike structures, and assessing lightning strike time sensitivity; calculating risk consistency under spatiotemporal constraints based on the risk component values ​​calculated from each lightning strike risk assessment, and outputting a comprehensive lightning strike risk value; determining whether the comprehensive lightning strike risk value exceeds a preset threshold, and if it is confirmed that the comprehensive lightning strike risk value exceeds the preset threshold, confirming that the target offshore wind turbine has a lightning strike risk and outputting the corresponding lightning strike structure location; if the comprehensive lightning strike risk value does not exceed the preset threshold, confirming that the target offshore wind turbine does not have a lightning strike risk.

[0013] A second aspect of this application provides a lightning strike risk assessment device for offshore wind turbines, the device comprising an acquisition module and a processing module, wherein, The acquisition module is used to acquire the electrical structure parameters of thunderstorm clouds around the target offshore wind turbine in a lightning environment, and to construct a thunderstorm cloud discharge model based on the thunderstorm cloud electrical structure parameters; and to construct the spatial background electric field that evolves over time based on the thunderstorm cloud discharge model.

[0014] The processing module is used to build a leader development model based on the spatial background electric field and the size parameters of each target structural part of the target offshore wind turbine. Based on the leader development model, it outputs upward discharge spatial tendency parameters, including the position parameters of the target structural parts that meet the upward discharge initiation conditions under the current thunderstorm electric field, and the directional deviation parameters of the upward leader extending along different spatial directions after the formation of the upward discharge. Based on the upward discharge spatial tendency parameters, it constructs an upward lightning stochastic discharge model and outputs upward leader evolution process parameters. These parameters represent the dynamic formation and evolution of the upward leader at the target structural parts. Based on the upward leader evolution process parameters, it constructs the spatiotemporal evolution parameters of the upward leader corresponding to the target offshore wind turbine and uses these parameters to assess the lightning strike risk.

[0015] A third aspect of this application provides an electronic device 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 to cause the electronic device to perform the method as described above.

[0016] A fourth aspect of this application provides a non-transitory computer-readable storage medium storing a computer program, the computer program being executed by a processor using any of the methods described above.

[0017] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. A thunderstorm cloud-initiated discharge model is constructed based on the electrical structure parameters of the thunderstorm cloud. A spatial background electric field evolving over time is constructed based on the thunderstorm cloud-initiated discharge model. A leader development model is built based on the spatial background electric field and the corresponding size parameters of each target structural part of the offshore wind turbine, outputting upward discharge spatial tendency parameters. An upward lightning stochastic discharge model is constructed based on the upward discharge spatial tendency parameters, and upward leader evolution process parameters are output. Upward leader spatiotemporal evolution parameters corresponding to the target offshore wind turbine are constructed based on the upward leader spatiotemporal evolution parameters, and lightning interception risk assessment is conducted through these parameters. This allows for the simultaneous characterization of the time-varying constraints of the spatial background electric field and the triggering and spatiotemporal development characteristics of the upward leader at each target structural part, even under conditions of rapid changes in the thunderstorm electrical structure over time. This improves the consistency and accuracy of assessments regarding the probability of lightning interception, the distribution of lightning-affected structural parts, and the time sensitivity to lightning interception, reducing misjudgments and omissions caused by empirical static assessments.

[0018] 2. Obtain the electrical structure parameters of thunderstorm clouds around the target offshore wind turbine under lightning conditions; based on the electrical structure parameters of thunderstorm clouds, construct a thunderstorm cloud initiation and discharge model by establishing a closed prediction equation set, thereby incorporating the potential drive, dielectric electrical properties and humidity modulation effect of thunderstorm clouds into a unified physical constraint framework without relying on empirical fixed electric field assumptions, and obtaining a thunderstorm initiation and discharge state characterization that can be updated over time, providing a consistent electrical environment basis for the subsequent temporal construction of the spatial background electric field.

[0019] 3. Under the influence of the spatial background electric field, the electric field distribution at each target structural part of the offshore wind turbine is calculated based on the corresponding dimensional parameters. The dimensional parameters include tower height, tower top geometric curvature, nacelle dimensions, and blade geometric dimensions. Using the dimensional parameters as modeling constraints, a leader development model is constructed based on the electric field distribution. This allows for the differentiation of local electric field enhancement differences at different parts such as the tower top, nacelle edge, and blade tip under the same thunderstorm background electric field conditions. It also clarifies the structural parts where upward discharge is more likely to occur first and the spatial bias of its subsequent leader development, providing a consistent structural scale calculation basis for the output of upward discharge spatial tendency parameters. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating a lightning strike risk assessment method for offshore wind turbines provided in an embodiment of this application. Figure 2 This is a schematic diagram of a lightning strike risk assessment device for offshore wind turbines provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0021] Explanation of reference numerals in the attached figures: 21. Acquisition module; 22. Processing module; 301. Processor; 302. Communication bus; 303. User interface; 304. Network interface; 305. Memory. Detailed Implementation

[0022] 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 with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0023] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification of this application, the singular expressions “a,” “an,” “the,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to and includes any or all possible combinations of one or more of the listed items.

[0024] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0025] To enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0026] Please refer to Figure 1 The diagram illustrates a flowchart of a lightning risk assessment method for offshore wind turbines provided in this application embodiment. The flowchart mainly includes the following steps: S101 to S105.

[0027] Step S101: Obtain the electrical structure parameters of the thunderstorm cloud around the target offshore wind turbine under lightning conditions, and construct a thunderstorm cloud discharge model based on the thunderstorm cloud electrical structure parameters.

[0028] Specifically, the lightning environment is a complex electrical environment dominated by strong convective weather systems. Its typical characteristics include significant charge separation within thunderstorm clouds, continuous accumulation of potential differences between clouds and the ground, and various forms of discharge activities such as intra-cloud discharge and cloud-to-ground discharge. In offshore areas, due to the high conductivity of the underlying surface and the persistently high levels of salt spray and humidity in the air, the electric field of thunderstorm clouds is more easily conducted to near-ground space and distorted around tall conductive structures. Offshore wind turbines typically have structural features such as tall towers, long blades, and prominent nacelles. Under the influence of the electric field of thunderstorm clouds, local electric field enhancement areas are easily formed at the top of the tower, the outer shell of the nacelle, and the leading edge and tip of the blades, thus meeting the physical conditions for upward discharge or the formation of upward leaders. This makes offshore wind turbines naturally located as potential lightning targets in the lightning environment, thus posing a high risk of lightning strikes.

[0029] In existing technologies, the assessment of lightning strike risk for offshore wind turbines typically relies on historical lightning strike statistics, annual lightning strike frequency estimates, or empirical models based on simplified background electric field assumptions. These methods statically estimate the probability of a wind turbine being struck by lightning by treating it as an ideal conductor or a regular geometric shape. However, these methods generally ignore the rapid evolution of the electrical structure of thunderstorm clouds in time and space, fail to characterize the dynamic impact of cloud-to-ground potential relationships, charge distribution, and discharge activity on the local electric field during the discharge process of thunderstorm clouds, and also struggle to reflect the modulating effects of marine environmental factors such as dense salt spray and high humidity on electric field transmission and discharge conditions. As a result, there is a significant discrepancy between the lightning strike risk assessment results and the actual lightning process, making it difficult to accurately reflect the true lightning strike risk of offshore wind turbines at a specific moment and under specific thunderstorm conditions.

[0030] To address the aforementioned issues, the technical solution of this application no longer relies on fixed or empirical electric field assumptions for risk assessment. Instead, it first obtains the electrical structure parameters of thunderstorm clouds surrounding the target offshore wind turbine under lightning conditions. By physically characterizing the electrical relationship between the thunderstorm cloud and the ground surface, a thunderstorm cloud initiation discharge model that reflects the initiation discharge mechanism of the thunderstorm cloud is constructed. This provides a realistic and dynamic electrical environment foundation for the subsequent temporal construction of the spatial background electric field and the analysis of the formation and evolution of the uplink leader.

[0031] In one possible implementation, step S101 further includes: acquiring the electrical structure parameters of thunderstorm clouds around the target offshore wind turbine under lightning conditions; the lightning environment includes a strong electric field environment, a dense salt spray environment, and a high humidity environment; the electrical structure parameters of thunderstorm clouds include cloud-to-ground potential difference parameters, air equivalent conductivity parameters, and relative humidity parameters; based on the electrical structure parameters of thunderstorm clouds, constructing a thunderstorm cloud discharge model by establishing a closed prediction equation set; the closed prediction equation set consists of atmospheric motion equations, pressure equations, thermodynamic energy equations, hydromorphic mass continuity equations, and hydromorphic charge density equations.

[0032] Specifically, a strong electric field environment refers to the high potential difference state formed within thunderstorm clouds and between the cloud and the ground due to charge separation. This state directly determines the thunderstorm cloud's ability to initiate discharge. The corresponding cloud-to-ground potential difference parameter is used to characterize the magnitude and variation level of the potential difference between the bottom of the thunderstorm cloud and the sea surface. This parameter reflects the overall intensity of the electric field exerted by the thunderstorm cloud on the near-ground space and is the basic basis for determining whether the thunderstorm cloud is in a critical state of initiation and discharge. A dense salt spray environment is a typical environmental feature that persists in marine areas. A large number of salt spray particles in the air significantly alter the electrical properties of the near-ground atmosphere, causing changes in the migration, dissipation, and redistribution of charges in the air. This is addressed by measuring the equivalent conductivity of air. The parameter is used to characterize the overall air's ability to conduct current under the influence of salt spray particles. Its value directly affects the efficiency of the downward transmission of the electric field in thunderstorm clouds and the enhancement or attenuation trend of the local electric field around the wind turbine structure. High humidity environment refers to the state of high water vapor content in the air during thunderstorms. High humidity affects the formation, growth and charge-carrying capacity of water-bearing organisms, and also changes the breakdown characteristics of air. This is characterized by the relative humidity parameter, which reflects the degree of water vapor saturation in the air and its modulation effect on the charge carrying and discharge conditions of water-bearing organisms. It is an important environmental constraint for describing the level of electrical activity inside thunderstorm clouds.

[0033] After obtaining parameters such as cloud-to-ground potential difference, air equivalent conductivity, and relative humidity, a thunderstorm cloud discharge model is constructed using the electrical structure parameters of the thunderstorm cloud as unified input conditions by establishing a closed-loop prediction equation set. This closed-loop prediction equation set is not an arbitrary selection of a single equation, but rather includes at least several equations from the following sources: atmospheric motion equation, pressure equation, thermodynamic energy equation, hydromorphic mass continuity equation, and hydromorphic charge density equation. These equations are coupled together to form a closed loop. Specifically, the atmospheric motion equation and pressure equation describe the airflow motion and its force state within the thunderstorm cloud; the thermodynamic energy equation characterizes the thermodynamic changes within the cloud; the hydromorphic mass continuity equation reflects the generation, transport, and transformation processes of hydromorphs; and the hydromorphic charge density equation describes the carrying, migration, and accumulation of charge within the hydromorphs. In the actual construction of the thunderstorm cloud-initiated discharge model, the above equations do not exist in isolation, but are solved collaboratively under the common constraints of cloud-to-ground potential difference parameters, air equivalent conductivity parameters, and relative humidity parameters. This allows the aerodynamic, thermodynamic, hydromorphic evolution, and charge evolution processes inside the thunderstorm cloud to form a consistent physical description, thereby obtaining a thunderstorm cloud-initiated discharge model that can reflect the conditions and evolution trend of thunderstorm cloud-initiated discharge. This provides a physically consistent electrical environment foundation for the subsequent temporal construction of the spatial background electric field.

[0034] Step S102: Construct the spatial background electric field that evolves over time based on the thunderstorm cloud discharge model.

[0035] Specifically, based on the thunderstorm cloud initiation discharge model, the change process of the electrical structure of the thunderstorm cloud in the time dimension is characterized, and the evolution of the potential relationship between the thunderstorm cloud and the sea surface over time is determined accordingly. Under the constraint of the thunderstorm cloud initiation discharge model, the change of electrical structure formed during the thunderstorm cloud initiation discharge process is mapped into the dynamic update result of the spatial potential distribution. Furthermore, by solving the spatial change relationship of the potential distribution, the spatial background electric field where the electric field intensity and electric field direction in the target offshore wind turbine area change continuously over time is obtained.

[0036] In one possible implementation, step S102 further includes: constraining the potential boundary conditions between the thunderstorm cloud and the ground surface based on the cloud-to-ground potential difference parameter in the thunderstorm cloud discharge model; updating the spatial distribution of the thunderstorm cloud electrical structure parameters in a time series based on the thunderstorm cloud discharge model, and reflecting the evolution of the electrical structure over time during the thunderstorm cloud discharge process; calculating the potential distribution corresponding to the spatial range where the target offshore wind turbine is located after the thunderstorm cloud electrical structure parameters have been updated in a time series; and obtaining the spatial background electric field by solving the spatial variation relationship of the potential based on the potential distribution.

[0037] Specifically, in the thunderstorm cloud-initiated discharge model, the potential boundary conditions between the thunderstorm cloud and the ground surface are constrained based on the cloud-to-ground potential difference parameter. The potential boundary condition is that the potential difference between the equipotential surface at the bottom of the thunderstorm cloud and the equipotential surface of the sea surface remains consistent with the cloud-to-ground potential difference parameter, and is updated synchronously in the time dimension during the thunderstorm cloud-initiated discharge process. The equipotential surface at the bottom of the thunderstorm cloud and the equipotential surface of the sea surface are considered as two boundary surfaces respectively. Under the constraint of the cloud-to-ground potential difference parameter, the potential at the bottom of the thunderstorm cloud boundary and the potential at the sea surface boundary satisfy a fixed difference relationship, thus transforming the macroscopic electrical drive given by the thunderstorm cloud-initiated discharge model into potential solution conditions in the target space. One expression satisfying this constraint is:

[0038] in, For the bottom edge boundary of thunderstorm clouds at time The potential value, For the sea surface boundary at any time The potential value, The cloud-to-ground potential difference parameter at time The value of , It can be obtained from the field electric field instrument array, cloud-to-ground potential inversion, or consistency correction with the thunderstorm cloud-initiated discharge model. Its value changes dynamically within the evaluation time window as the thunderstorm evolves.

[0039] The distribution state refers to the "location-intensity" configuration of the electrical structure parameters of a thunderstorm cloud in three-dimensional space. Specifically, it describes how the strength, aggregation, and migration trends of the electrical structure at different spatial locations within the thunderstorm cloud's coverage area update over time. To avoid introducing new independent concepts, the distribution state is directly expressed as a field representation of the thunderstorm cloud's electrical structure parameters in a spatial grid or continuous spatial coordinate system. For example, the cloud-to-ground potential difference parameter, the equivalent conductivity of air, and the relative humidity parameter are mapped together as time-varying dielectric parameters and source term parameters that constrain the solution of the potential field. This time-series update reflects the evolution of the thunderstorm cloud's discharge process and is modulated by salt spray conductivity and humidity conditions. The expression for this spatiotemporal evolution is as follows:

[0040] in, A unified characterization quantity representing the state field of the electrical structure, used to carry spatial distribution information of the electrical structure parameters of thunderstorm clouds. It is a spatial position vector. For a moment, The wind velocity, derived from the atmospheric motion equations, is used to characterize the migration of electrical structures carried by airflow. The diffusion coefficient is used to characterize the spatial diffusion intensity of electrical structures under turbulent and microscale mixing. The relaxation coefficient is used to characterize the rate at which an electrical structure reverts to an equilibrium state. This represents the equilibrium electrical structure state given by the thunderstorm cloud-initiated discharge model under the current thermodynamic and hydromorphic conditions. The source term is used to characterize the redistribution of electrical structures by intracloud discharge activity. It can be constructed from the surrogate quantity of the intensity of discharge activity and obtained through self-consistent model solution.

[0041] After updating the time-series parameters of the thunderstorm cloud's electrical structure, the potential distribution within the spatial range of the target offshore wind turbine is calculated. To reflect the influence of concentrated salt spray and high humidity on charge migration and potential field distribution, the equivalent conductivity parameter of air and the relative humidity parameter are applied together to the dielectric and source terms of the potential field equation, and an improved generalized Poisson form is used to solve for the potential.

[0042] in, The potential distribution in space With time The value of , This is the equivalent dielectric coefficient, used to comprehensively reflect the influence of humidity-induced changes in dielectric polarization and the micro-water film effect on the field distribution. This is an equivalent source term used to characterize the driving strength of the electrical structure in space given by the thunderstorm cloud-initiated discharge model. To incorporate salt spray and humidity information directly into the solution, we can... and Rewrite the algorithm as an improved expression composed of measurable parameters, making the algorithm more concrete and reproducible:

[0043] in, As a reference dielectric constant, For relative humidity parameters in The value at this location, the range of values ​​is to Or equivalent percentage normalized result, For the air equivalent conductivity parameter in The value at that location, The humidity modulation weighting coefficient is used to control the intensity of the influence of humidity on the media equivalence. The salt spray modulation weighting coefficient is used to control the intensity of the effect of salt spray on the media equivalence. A monotonically saturated mapping function is used to map measurements of different dimensions and scales to... to modulation range, Optional Form, in which Controlling the steepness of the change, The expression is centered and biased. It explicitly incorporates the equivalent changes in the medium under high humidity and salt spray conditions into the potential equation, thus making it closer to the marine scenario than the conventional "fixed medium" solution.

[0044] in, The fundamental driving source term, derived from the intrinsic evolution of the thunderstorm cloud-originating discharge model, is used to characterize the spatial driving distribution caused by electrical structure migration and discharge activity. This is the geometric propagation kernel function of the cloud-ground potential difference parameter in space, used to project the driving force of the boundary potential difference on the interior domain onto... place, The potential difference drives the gain coefficient. The conduction-discharge coefficient is used to characterize the weakening effect of salt spray-enhanced conduction on the local potential. The last term is obtained through... and The coupling embodies the effect that "the stronger the conduction, the easier it is for the potential to be dissipated", thus incorporating the influence of the concentrated salt spray environment on the potential distribution into the same solution framework.

[0045] The spatial background electric field refers to the time-varying electric field vector field formed in the spatial domain of the wind turbine by the discharge process of thunderstorm clouds, without introducing details of local distortion of the wind turbine structure. It includes the time-varying results of the electric field intensity and direction at each spatial location, and is used as an external electrical environment constraint for subsequent lead development models. The spatial background electric field is obtained from the spatial variation of the electric potential distribution, and adopts a vector expression that is more consistent with three-dimensional numerical solutions.

[0046] in, For the background electric field in space The value at that location, This indicates that the direction of the electric field always points in the direction of the fastest decrease in electric potential, and its strength is determined by the rate of change of electric potential in space. To make the solution process more feasible and adaptable to engineering calculation grids, the gradient can be approximated on the discrete grid using the potential difference between adjacent nodes, thus directly outputting the electric field vector at each grid point:

[0047] in, For the first Location of each spatial grid point and They represent in direction and The positions of adjacent grid points before and after, The grid spacing in the three directions is determined by the solution domain scale and the desired resolution. The potential values ​​are assigned to the corresponding grid points.

[0048] Step S103: Build a pilot development model based on the spatial background electric field and the size parameters of each target structural part of the target offshore wind turbine, and output the upward discharge spatial tendency parameters based on the pilot development model.

[0049] Specifically, the upward discharge spatial tendency parameters include the positional parameters of the target structure that meet the upward discharge initiation conditions under the current thunderstorm electric field, and the directional deviation parameters of the upward leader extending along different spatial directions after the formation of the upward discharge.

[0050] Step S104: Construct an upward lightning stochastic discharge model based on the upward discharge spatial tendency parameters, and output the upward preliminary calculus parameters based on the upward lightning stochastic discharge model.

[0051] Specifically, under the constraint of the upward discharge spatial tendency parameter, a random discharge mechanism is introduced to characterize the actual occurrence process of the upward leader. By randomly determining the upward discharge triggering time and leader development behavior at different target structural locations, an upward leader evolutionary result consistent with the uncertainty of lightning processes is obtained. The upward leader evolutionary process parameters are used to represent the dynamic formation and evolution process of the upward leader at the target structural location. Dynamic formation means that the upward leader does not appear simultaneously or necessarily at different structural locations, but occurs in an uncertain sequence with changes in the thunderstorm electric field. Evolution process means that the extension path of the upward leader in the post-formation space is not fixed, but gradually develops and forms a specific spatiotemporal trajectory under the constraint of a given electric field.

[0052] In one possible implementation, step S104 further includes: under the influence of the spatial background electric field, calculating the electric field distribution state at the target structural parts in combination with the size parameters corresponding to each target structural part of the target offshore wind turbine; the size parameters include tower height parameters, tower top geometric curvature parameters, nacelle external dimensions parameters, and blade geometric dimensions parameters; using the size parameters as modeling constraints, constructing a pilot development model based on the electric field distribution state.

[0053] Specifically, under the influence of the spatial background electric field, the target offshore wind turbine is first decomposed into several target structural parts such as the top of the tower, the edge of the nacelle, and the leading edge and tip of the blades. A set of size parameters consistent with the geometric shape is established for each target structural part, so that the subsequent electric field distribution calculation is directly applied to the specific structural surface and its adjacent space rather than to abstract points. Taking the top of the tower as an example, the tower height parameter can be taken as a specific value in the range of 90m to 140m commonly seen at sea. The geometric curvature parameter of the top of the tower can be represented by the equivalent curvature radius of the top fillet and taken as a specific value in the range of 0.5m to 3m. Taking the nacelle shape as an example, the nacelle shape dimension parameter can be characterized by the nacelle length of 8m to 15m, the nacelle width of 3m to 6m, and the equivalent curvature radius of the top fillet of 0.2m to 1.5m. Taking the blade as an example, the blade geometric dimension parameter can be characterized by the blade length of 60m to 110m, the equivalent curvature radius of the blade tip of 0.01m to 0.2m, and the local thickness of the blade leading edge of 0.02m to 0.15m. The values ​​of the above parameters directly determine the degree of concentration of electric field lines by the structure and the distribution of the strength of local electric field enhancement.

[0054] Modeling constraints are manifested by incorporating dimensional parameters into the geometric boundaries, candidate initiation regions, and candidate extension regions of the leader development model. This ensures that the model calculates the electric field and leader development only within the geometrically permissible space where the structure truly exists, preventing the generation of false initiation points or false development directions in non-structural regions. The tower height parameter limits the upper boundary of the vertical solution domain and the position of the tower axis. The tower top geometric curvature parameter limits the surface shape of the tower top region and the curvature distribution of the candidate initiation regions. The nacelle external dimension parameter limits the boundary shape of the nacelle shell and the range of candidate initiation regions at the top and leading edge of the nacelle. The blade geometric scale parameter limits the spatial occupancy of the blade swept body and the set of candidate initiation regions and their available extension directions at the blade tip and leading edge, thus ensuring that subsequent upward leader initiation and stepping are consistent with the actual structural geometry.

[0055] The electric field distribution refers to the spatial distribution of electric field intensity and direction on the surface of a target structure and in its vicinity, given a known background electric field. This distribution is formed by the local enhancement and shading caused by the structure's geometry. To explicitly define this distribution as a computable quantity, the local electric field of each target structure is expressed as the product of the background electric field and the geometric enhancement coefficient. The geometric enhancement coefficient is then written as a function determined by the size parameters, allowing different parts to obtain different local electric field distributions under the same background electric field. The expressions for the local electric field vectors of different target structure parts at different locations and times are as follows:

[0056] in, Indicates the first The target structural parts are located at the following positions. With time The local electric field vector at that location, This represents the spatial background electric field vector at the same location and time. Indicates the first The target structural parts are located at the following positions. The geometric enhancement coefficient at a given location is greater than 0 and has a larger value at locations with smaller curvature and higher sharpness, thereby increasing the local electric field with the sharpness of the structure.

[0057] In engineering implementation, in order to It can directly calculate and cover different shapes such as the top of the tower, the edge of the nacelle and the blade tip from the size parameters. It adopts an expression that modulates the radius of curvature and the height, so that the tip effect and the height effect can be included in the same calculation framework at the same time. The calculation method is as follows:

[0058] in, Indicates the tower height parameter. This represents a height reference value, and 100m can be used as the normalization baseline. Indicates the first The target structural parts are located at the following positions. The equivalent radius of curvature at the top of the tower can be 0.5m to 3m, the radius of curvature at the top of the nacelle can be 0.2m to 1.5m, and the radius of curvature at the blade tip can be 0.01m to 0.2m. This represents a curvature reference value, and 1m can be taken as the normalization reference. This indicates a stable term that avoids numerical divergence caused by an excessively small denominator and can be taken as an example. to constants within the range, This represents the height modulation coefficient and is used to characterize the strength of the contribution of tall structures to local field enhancement. It represents the curvature modulation coefficient and is used to characterize the strength of the contribution of tip curvature to local field enhancement. and It represents the power exponent and is used to control the degree of nonlinearity of the enhancement as it varies with height and curvature. Values ​​ranging from 0.5 to 1.5 can be used to cover scale sensitivity under different sea states and thunderstorm scenarios. Values ​​ranging from 0.8 to 2.5 can be used to cover the enhancement differences from blunt to sharp. The formula reflects the principle that the higher the tower, the more pronounced the local enhancement; the smaller the radius of curvature, the more pronounced the local enhancement; and the blade tip, due to… Smaller usually gets bigger Next, the outer edge of the nacelle is considered, followed by the rounded corner area at the top of the tower.

[0059] After obtaining the local electric field vector, the intensity distribution in the electric field distribution state is further given for subsequent determination of the upward discharge initiation conditions and leader development trend. The expressions for the local electric field intensity of the target structure at different locations and times are as follows:

[0060] in, Indicates the first The target structural parts are located at the following positions. With time The local electric field intensity at that location, This indicates that the intensity value is obtained by taking the modulus of the electric field vector, and the intensity value varies with... Increased with the enhancement, and in Larger, sharper locations exhibit higher peak values, thus creating a hotspot distribution in space that can be used for initial determination.

[0061] Based on this, using size parameters as modeling constraints, when constructing the lead development model based on the electric field distribution state, the candidate starting region is limited to the set of points on the surface of each target structure that satisfy the local electric field strength being higher than the starting criterion, and the candidate extension region is limited to the space near the outward normal direction from the candidate starting region along the local electric field direction. This makes the lead development model geometrically fit the structure and electrically fit the electric field distribution state, and provides a direct and calculable basis for the subsequent upward discharge space tendency parameters.

[0062] In one possible implementation, step S104 further includes: randomly determining the order of upward discharge at each target structural location based on the upward discharge spatial tendency parameter, and determining the upward leader start time parameter corresponding to each target structural location; randomly evolving the gradual extension behavior of the upward leader in space based on the upward leader start time parameter and combined with the direction bias parameter, and outputting the evolution state change of the upward leader at the target structural location; randomly selecting the extension behavior of the upward leader along different spatial directions at each evolution time based on the direction bias parameter, and outputting the spatial development path parameter corresponding to the upward leader; and jointly determining the upward leader start time parameter and the spatial development path parameter as the upward leader evolution process parameter.

[0063] Specifically, when conducting random determination based on the upward discharge spatial tendency parameters, a correspondence is established between the position parameters of each target structural part and the values ​​of the spatial background electric field at the corresponding positions. The local electric field intensity is then used to characterize the imminent triggering of the upward discharge at that location, so that the sequence is no longer determined by a fixed order, but by the triggering intensity that changes over time. To ensure that the random determination reflects both the structural differences in the directional bias parameters and the triggering window drift caused by the time evolution of the thunderstorm electric field, the [missing information - likely a parameter related to the random determination] is... The target structural parts at time The trigger strength is expressed as an intensity function. And regard the uplink leader start time parameter as being determined by... The random arrival time of the drive allows different parts of the same thunderstorm to be triggered in different sequences. The triggering intensity of different target structural parts at different times can be denoted as... :

[0064] in, For the first The target structural parts at time The trigger strength is used to characterize the degree of proximity of the part to entering the upward discharge initiation condition at that moment. The baseline strength coefficient is used to set the overall triggering time scale. The monotonically saturated mapping function is used to map the degree of electric field exceeding the threshold to... arrive The trigger ratio between them For the first The target structural part has its position parameters The local electric field strength at the location is calculated from the previous step S104 and its sign remains unchanged. This is the initial criterion electric field threshold corresponding to this region, used to describe the critical level at which this region enters the upward discharge initiation condition under material and geometric conditions. This is an electric field scale parameter used to control the rate at which the intensity increases when the electric field moves from near a threshold to significantly exceeding the threshold. The spatiotemporal evolution of the electrical structure state of thunderstorm clouds The value at this point is used to reflect the degree of modulation of the triggering environment by the thunderstorm cloud-initiated discharge process. The modulation coefficient is used for control. The amplification effect on triggering intensity. The principle of this formula is to directly link whether the upward discharge is triggered with whether the local electric field exceeds the threshold, while allowing the electrical structure of the thunderstorm cloud to change over time to amplify or suppress the triggering intensity, thus giving the same location different triggering probabilities at different times.

[0065] After the trigger intensity function is determined, when randomly determining the order of upward discharge at each target structural part, a cumulative trigger quantity is constructed for each part. The uplink leader start time parameter is defined as the earliest time when the cumulative trigger amount reaches the random threshold, thus transforming the sequential relationship into a comparison relationship between multiple random arrival times.

[0066] in, For the first Each target structural component from the assessment starting point At the time The cumulative trigger amount, This is the trigger intensity function at the corresponding time. Let be the integral variable. The principle of this formula is to accumulate the trigger intensity that changes over time into a monotonically non-decreasing quantity; the faster the accumulation, the earlier the part enters the triggerable state. The initial time parameter can be denoted as:

[0067] in, For the first The parameters of the upward leader start time corresponding to each target structural part. This indicates the earliest time that satisfies the condition. For random threshold variables, it can be obtained from generate, for arrive A uniformly distributed random number between these values ​​is used to introduce randomness. The principle behind this formula is that a random threshold represents the cumulative random amount required for a single trigger. When the cumulative trigger amount reaches the threshold first, its corresponding... Smaller, thus naturally forming a sequence among multiple parts.

[0068] After determining the starting time parameters of the upward leader corresponding to each target structural part, and combining the direction bias parameter to stochastically evolve the gradual extension behavior of the upward leader in space, the development of the upward leader is represented as a stepping process consisting of discrete evolution times. Each step starts from the current position and randomly selects from several candidate extension directions. The direction bias parameter is used to bias the direction selection probability, ensuring randomness without losing physical constraints. Let the... The position of the leader of the step is The candidate direction set is Each of them The direction bias parameter is a unit vector. Indicate and with the If we associate each target structural component with a preferred direction under the constraints of the local electric field direction and the structural normal, then the th... Step 1 Select the first The probabilities in each direction can be written as:

[0069] in, For the first Step-by-step selection of candidate directions The probability, This is the bias intensity coefficient, used to control the degree to which the direction bias parameter dominates the random selection. The exponent term is the dot product of two vectors, used to measure the consistency between the candidate direction and the preferred direction. The higher the consistency, the larger the exponent term, and thus the higher the probability. The principle of this formula is to use an exponential mapping to transform the consistency into relative weights, and then normalize it to obtain a probability distribution, thereby achieving a direction selection that is both random and biased.

[0070] After direction selection, the leader position is updated using a step size. This step size reflects both the driving force of the local electric field on the development capability and introduces fluctuations caused by discharge instability. Let the... Step length is The position is then updated to:

[0071] in, To be according to A randomly selected unit vector in the direction of the direction. Let be the corresponding step size random variable. The principle of this formula is to control the spatial advancement distance of each step with the step size and the advancement direction with the direction, thereby discretizing the spatial development path into a computable sequence of points.

[0072] To ensure that the step size aligns with the electric field distribution while allowing for random fluctuations, a monotonic relationship is established between the expected value of the step size and the local electric field strength, and a truncation perturbation is introduced near this expected value: in, This is the minimum step size, used to prevent the step size from degenerating to zero when the electric field approaches the threshold. This is the maximum step size, used to limit the path distortion caused by excessively large single-step spans. For the first The values ​​of the local electric field intensity associated with each target structural part at the current location and at the current evolution time. and To maintain consistency with the aforementioned trigger strength and ensure that the symbol and technical feature name remain unchanged, This is a step size perturbation term, used to introduce step size fluctuations caused by discharge instability. It can be obtained from a mean of 0 and is restricted to Generated by random distribution within the range, This represents the upper limit of the perturbation. The principle behind this formula is that the more significantly the electric field exceeds the threshold, the greater the perturbation. The closer it is to 1, the closer the step size is to... When the electric field approaches the threshold The size is relatively small, so the step size is close to and through Retain random fluctuations.

[0073] The evolutionary state changes mentioned in the above stochastic evolution process correspond to the state sequence indexed by evolution time, which is used to completely preserve the process results of the upward leader from the beginning to the development stage. It can be expressed by the position sequence and the corresponding evolution time sequence, where the evolution time can be obtained by the step time interval and is related to the strength of the local electric field: in, For the first The corresponding evolutionary moment of each step The step time interval, and These represent the minimum and maximum time intervals, used to define the temporal resolution and upper limit of evolutionary progression. The principle behind this formula is that the stronger the electric field, the more the molecules tend to move towards negative values. Smaller, therefore Closer This manifests as faster development and a weaker electric field. Larger, which manifests as slower development.

[0074] When randomly selecting and outputting spatial evolution path parameters based on the directional bias parameter to analyze the extension behavior of the ascending leader along different spatial directions at various evolution times, the spatial evolution path parameters are defined as the leader head position sequence from the starting position to the ending position and its corresponding time sequence, i.e.: in, In order to be with the first Spatial evolution path parameters associated with each target structural component To determine the starting position and starting time when the upward leader is triggered at this location. To determine the termination position and termination time when the termination condition is met. The number of steps is determined by the termination condition. The principle of this formula is to bind the spatial trajectory with the temporal trajectory using a discrete point sequence, so that it can be directly called when constructing the spatiotemporal evolution parameters of the uplink leader.

[0075] When the uplink leader initiation time parameter and the spatial evolution path parameter are jointly determined as the uplink leader evolution process parameters, they can be directly written as: in, In order to be with the first The parameters of the uplink pre-calculation process associated with each target structural part. This refers to the upward leader start time parameter for this region. This represents the spatial development path parameters for this region. The principle behind this formula is to use the minimum two-class results to cover the temporal and spatial information required for the dynamic formation and evolution of the upward leader, thereby maintaining a direct connection with the construction of subsequent upward leader spatiotemporal evolution parameters.

[0076] Step S105: Construct the spatiotemporal evolution parameters of the target offshore wind turbine based on the uplink leader evolution process parameters, and conduct a lightning strike risk assessment using the uplink leader spatiotemporal evolution parameters.

[0077] Specifically, the upward leader results, which are scattered across different target structural parts, starting times, and development paths, are uniformly organized to form a spatiotemporal description that comprehensively reflects the upward leader behavior of the target offshore wind turbine under lightning conditions, and a lightning strike risk assessment is completed accordingly. Specifically, the upward leader starting time parameters and spatial development path parameters corresponding to each target structural part are aligned under a unified time axis and spatial coordinate system to construct upward leader spatiotemporal evolution parameters covering the entire assessment time window, enabling a holistic characterization of when, where, and how the upward leader develops in space. Based on this, the spatiotemporal coupling relationship between the upward leader spatiotemporal evolution parameters and the thunderstorm cloud discharge process is analyzed to determine whether the upward leader possesses the conditions to connect with the thunderstorm discharge channel. Based on this, a comprehensive assessment of the lightning strike probability, lightning strike location distribution, and lightning strike timing characteristics of the target offshore wind turbine is conducted, thereby outputting the lightning strike risk assessment results for the target offshore wind turbine.

[0078] In one possible implementation, step S105 further includes: performing a lightning strike risk assessment using uplink leader spatiotemporal evolution parameters, the lightning strike risk assessment including a lightning strike probability assessment, a lightning strike structure distribution assessment, and a lightning strike time sensitivity assessment; performing risk consistency discrimination calculation under spatiotemporal constraints based on the risk component values ​​calculated from each lightning strike risk assessment, and outputting a comprehensive lightning strike risk value; determining whether the comprehensive lightning strike risk value exceeds a preset threshold, and if it is confirmed that the comprehensive lightning strike risk value exceeds the preset threshold, confirming that the target offshore wind turbine has a lightning strike risk, and outputting the corresponding lightning strike structure location; if the comprehensive lightning strike risk value does not exceed the preset threshold, confirming that the target offshore wind turbine does not have a lightning strike risk.

[0079] Specifically, when assessing lightning interception risk using the spatiotemporal evolution parameters of the uplink leader, the starting time parameters and spatial development path parameters of the uplink leader corresponding to each target structural part in the spatiotemporal evolution parameters are uniformly mapped to the same assessment time window and the same three-dimensional coordinate system. This allows the occurrence order, duration, and spatial extension trajectory of the uplink leader at different parts to be compared in parallel. Furthermore, the time series results of the spatial background electric field are aligned with the spatiotemporal evolution parameters of the uplink leader to form a common constraint on lightning interception risk in both time and space. This provides a consistent data foundation for assessing the probability of lightning interception, the distribution of lightning interception structural parts, and the time sensitivity of lightning interception.

[0080] The assessment of the probability of lightning strikes focuses on characterizing the overall probability of at least one lightning strike occurring within the assessment time window. It is correlated with whether the upward leader is triggered within the window, whether it forms a continuous extension, and whether it enters the lightning-sensitive spatial domain. The lightning-sensitive spatial domain is jointly defined by the thunderstorm cloud-initiated discharge model and the spatial background electric field. A continuous spatial region where the spatial background electric field intensity exceeds a preset threshold can be used as the lightning-sensitive spatial domain. The degree of spatiotemporal overlap between the spatial development path parameters of each target structural part and the lightning-sensitive spatial domain is used as the contribution to the probability of lightning strikes, thereby avoiding giving a lightning strike conclusion based solely on the initiation event of a single part.

[0081] The assessment of lightning strike distribution focuses on characterizing where lightning is more likely to occur. It correlates this with the relative order of the upward leader start time parameters of different target structural parts, the degree of proximity of the corresponding spatial development path parameters to the lightning-sensitive spatial domain, and the number of times or duration of repeated triggering of the part within the window. This allows the output to not only provide a set of possible lightning strike locations but also the relative dominance of each location, thereby highlighting the risk differences between locations such as the top of the tower, the edge of the nacelle, the blade tip, and the leading edge of the blade under the same lightning environment.

[0082] The lightning strike time sensitivity assessment focuses on characterizing whether the lightning strike risk is concentrated in a few short time windows. It correlates the risk with the degree of aggregation of the parameters at the start of the upward leader on the time axis, the rising slope and fluctuation amplitude of the spatial background electric field on the time dimension, and the rapid approach behavior of the spatial development path parameters to the lightning-sensitive spatial domain at critical moments. This allows the assessment results to show the transition characteristics of risk from low to high, avoiding the dilution of obvious short-term high-risk events by averaging them over the entire window.

[0083] When performing risk consistency discrimination calculations under spatiotemporal constraints based on the risk component values ​​calculated from each lightning strike risk assessment, the three types of assessment results are abstracted into three risk component values ​​and limited to comparable quantities within the same numerical domain, which are respectively denoted as the lightning strike probability component values. Distribution component values ​​of lightning-shielding structural parts and lightning time sensitivity component value It also introduces a spatiotemporal consistency coefficient directly calculated from the spatiotemporal evolution parameters of the uplink leader. : in, This represents the minimum spatial distance between the spatial development path parameters and the boundary of the lightning-sensitive spatial domain. It is obtained by taking the minimum value of the distance from each path point to the lightning-sensitive spatial domain. This represents the distance decay scale parameter, used to characterize the sensitivity of distance changes to uniformity decay. This represents the minimum time interval between the moment when the spatial evolution path parameter first enters the lightning-sensitive spatial domain and the uplink leader start time parameter. It is obtained by taking the minimum difference between the entry time and the corresponding start time of each path. This represents the time decay scale parameter, used to characterize the sensitivity of time interval changes to consistency decay. The principle behind this formula is that the closer the path is to the lightning-sensitive spatial domain and the faster it enters that domain, the more common the spatiotemporal basis among the three types of assessments, thus resulting in higher consistency. The calculation method for the combined risk intensity without imposed consistency constraints is as follows:

[0084] in, This indicates the portfolio risk intensity without imposed consistency constraints. It is obtained from the probability assessment of lightning strike occurrence and can be derived from the cumulative arrival probability statistics of the trigger intensity within the window. The risk predominance of each part can be assessed by evaluating the distribution of lightning-affected structural components, and the maximum value or the entropy inverse quantification result can be taken. The combined lightning strike risk value is obtained from the lightning strike time sensitivity assessment and can be normalized from the peak percentage or rising slope of the risk over time. The principle behind this formula is that an increase in any component value will increase the combined risk intensity, while retaining the enhancement effect when multiple components increase simultaneously. The calculation method for the combined lightning strike risk value is as follows:

[0085] in, This indicates the overall risk value of lightning strikes. By imposing spatiotemporal constraints on the combined risk intensity, the overall risk remains high only when the three assessments corroborate each other under the same spatiotemporal facts. When component values ​​are high but lack path convergence or time alignment, the overall risk is suppressed by the consistency coefficient. The principle embodied in this formula is to use the spatiotemporal evolution results as adjudicative information, avoiding false alarms based solely on high statistical component values.

[0086] When determining whether the comprehensive risk value of lightning strike exceeds a preset threshold, the preset threshold is recorded as follows: ,when When it is confirmed that the target offshore wind turbine has a lightning strike risk, the target structural parts with the highest risk in the lightning strike structural parts distribution assessment are taken as the output parts; when It can confirm that there is no risk of lightning strike to the target offshore wind turbine and output a low-risk conclusion within the assessment time window for the maintenance of subsequent scheduling or monitoring strategies.

[0087] Taking a 12MW offshore wind turbine as an example, the tower height of the target offshore wind turbine is set at 110m, the geometric curvature of the tower top is set at 1.2m, the nacelle dimensions are set at a length of 12m and an equivalent radius of curvature of 0.6m for the top corner, and the blade geometry is set at a length of 95m and an equivalent radius of curvature of 0.05m for the blade tip. In a lightning environment, the cloud-to-ground potential difference increases from 260MV to 330MV within the evaluation time window, the air equivalent conductivity is at a relatively high level under dense salt spray conditions and shows an increasing trend with the intensification of sea fog, and the relative humidity is close to saturation and remains above 0.92. The inputs to the thunderstorm cloud-initiated discharge model are the cloud-to-ground potential difference, the air equivalent conductivity, and the relative humidity, and the output is the thunderstorm cloud-initiated discharge state updated over time, which is used to construct the spatial background electric field that evolves over time. The output of the spatial background electric field is the distribution of electric field intensity and direction in the three-dimensional space where the target offshore wind turbine is located, which varies over time. The leader development model takes the space background electric field and the dimensional parameters of each target structural component as inputs and outputs upward discharge spatial tendency parameters. In this example, the upward discharge spatial tendency parameters indicate that the outer surfaces of the blade tip and the top of the nacelle first satisfy the upward discharge initiation conditions, and the directional bias parameter points to the region slightly above and forward of the dominant direction of the space background electric field. The upward lightning stochastic discharge model takes the upward discharge spatial tendency parameters as inputs and outputs upward leader evolution process parameters. In this example, the upward leader initiation time parameter at the blade tip is earlier than that at the top of the nacelle, and the spatial evolution path parameter approaches the high-intensity corridor region of the space background electric field faster. The upward leader spatiotemporal evolution parameters are obtained by aligning the initiation time parameters and spatial evolution path parameters of each component and serve as direct inputs for lightning strike risk assessment. In this example, the calculated parameters are as follows: Smaller and Shorter, therefore High, lightning strike probability component value With lightning time sensitivity component value Synchronous rise, distribution component value of lightning-resistant structural parts The direction of the blade tip's outer surface is dominant, resulting in the final comprehensive lightning risk value. Exceeding the preset threshold Based on this, it was confirmed that the unit had a risk of flashing within the assessment time window, and the outer surface of the blade tip was identified as the corresponding flashing structure.

[0088] Please refer to Figure 2 The diagram illustrates a module schematic of a lightning strike risk assessment device for offshore wind turbines provided in an embodiment of this application. The device includes an acquisition module 21 and a processing module 22, wherein... The acquisition module 21 is used to acquire the electrical structure parameters of the thunderstorm cloud around the target offshore wind turbine in a lightning environment, and to construct a thunderstorm cloud discharge model based on the thunderstorm cloud electrical structure parameters; and to construct a spatial background electric field that evolves over time based on the thunderstorm cloud discharge model.

[0089] Processing module 22 is used to build a leader development model based on the spatial background electric field and the size parameters of each target structural part of the target offshore wind turbine, and output upward discharge spatial tendency parameters based on the leader development model. The upward discharge spatial tendency parameters include the position parameters of the target structural parts that meet the upward discharge initiation conditions under the current thunderstorm electric field conditions, and the directional deviation parameters of the upward leader extending along different spatial directions after the formation of upward discharge in the target structural parts. Based on the upward discharge spatial tendency parameters, an upward lightning stochastic discharge model is constructed, and upward leader evolution process parameters are output based on the upward lightning stochastic discharge model. The upward leader evolution process parameters are used to represent the dynamic formation and evolution process of the upward leader at the target structural parts. Based on the upward leader evolution process parameters, the spatiotemporal evolution parameters of the upward leader corresponding to the target offshore wind turbine are constructed, and the lightning strike risk assessment is performed through the spatiotemporal evolution parameters of the upward leader.

[0090] In one possible implementation, the acquisition module 21 is used to acquire the electrical structure parameters of the thunderstorm cloud around the target offshore wind turbine under lightning conditions, and to construct a thunderstorm cloud discharge model based on the thunderstorm cloud electrical structure parameters. Specifically, this includes: acquiring the electrical structure parameters of the thunderstorm cloud around the target offshore wind turbine under lightning conditions; the lightning environment includes a strong electric field environment, a dense salt spray environment, and a high humidity environment; the thunderstorm cloud electrical structure parameters include cloud-to-ground potential difference parameters, air equivalent conductivity parameters, and relative humidity parameters; and constructing a thunderstorm cloud discharge model based on the thunderstorm cloud electrical structure parameters by establishing a closed prediction equation set; the closed prediction equation set consists of atmospheric motion equations, pressure equations, thermodynamic energy equations, hydrostatic mass continuity equations, and hydrostatic charge density equations.

[0091] In one possible implementation, the acquisition module 21 is used to construct a spatial background electric field that evolves over time based on a thunderstorm cloud-initiated discharge model. Specifically, this includes: constraining the potential boundary conditions between the thunderstorm cloud and the ground surface based on the cloud-to-ground potential difference parameter in the thunderstorm cloud-initiated discharge model; updating the spatial distribution of the electrical structure parameters of the thunderstorm cloud in a time series based on the thunderstorm cloud-initiated discharge model, and reflecting the evolution of the electrical structure over time during the thunderstorm cloud-initiated discharge process; calculating the potential distribution corresponding to the spatial range where the target offshore wind turbine is located after the temporal update of the thunderstorm cloud electrical structure parameters; and obtaining the spatial background electric field by solving the spatial variation relationship of the potential based on the potential distribution.

[0092] In one possible implementation, the processing module 22 is used to build a pilot development model based on the spatial background electric field and the size parameters corresponding to each target structural part of the target offshore wind turbine. Specifically, it includes: calculating the electric field distribution state at the target structural part under the action of the spatial background electric field, combined with the size parameters corresponding to each target structural part of the target offshore wind turbine; the size parameters include tower height parameters, tower top geometric curvature parameters, nacelle outer dimension parameters, and blade geometric dimension parameters; using the size parameters as modeling constraints, a pilot development model is built based on the electric field distribution state.

[0093] In one possible implementation, the processing module 22 is used to output upward discharge spatial tendency parameters based on the leader development model, specifically including: determining whether the target structural part meets the starting conditions for upward discharge based on the electric field distribution state at the target structural part; if the target structural part meets the starting conditions for upward discharge, determining the target structural part as a candidate starting part; determining the spatial position parameters corresponding to the candidate starting part, and after upward discharge is formed at the candidate starting part, outputting the trend difference of the upward leader developing along different spatial directions under the action of the spatial background electric field based on the leader development model; constructing the corresponding direction bias parameters based on the trend difference; combining the spatial position parameters and the direction bias parameters, and outputting the upward discharge spatial tendency parameters.

[0094] In one possible implementation, the processing module 22 is used to output uplink leader evolution process parameters based on the uplink lightning stochastic discharge model. Specifically, it includes: randomly determining the order of uplink discharge at each target structural part based on the uplink discharge spatial tendency parameter, and determining the uplink leader start time parameter corresponding to each target structural part; stochastically evolving the gradual extension behavior of the uplink leader in space based on the uplink leader start time parameter and combined with the direction bias parameter, and outputting the evolution state change of the uplink leader at the target structural part; randomly selecting the extension behavior of the uplink leader along different spatial directions at each evolution time based on the direction bias parameter, and outputting the spatial development path parameter corresponding to the uplink leader; and jointly determining the uplink leader start time parameter and the spatial development path parameter as the uplink leader evolution process parameters.

[0095] In one possible implementation, the processing module 22 is used to perform lightning strike risk assessment using uplink leader spatiotemporal evolution parameters. Specifically, this includes: performing lightning strike risk assessment using uplink leader spatiotemporal evolution parameters, whereby the lightning strike risk assessment includes assessment of the probability of lightning strike, assessment of the distribution of lightning strike structures, and assessment of lightning strike time sensitivity; performing risk consistency discrimination calculation under spatiotemporal constraints based on the risk component values ​​calculated from each lightning strike risk assessment, and outputting a comprehensive lightning strike risk value; determining whether the comprehensive lightning strike risk value exceeds a preset threshold, and if it is confirmed that the comprehensive lightning strike risk value exceeds the preset threshold, confirming that the target offshore wind turbine has a lightning strike risk, and outputting the corresponding lightning strike structure; if the comprehensive lightning strike risk value does not exceed the preset threshold, confirming that the target offshore wind turbine does not have a lightning strike risk.

[0096] It should be noted that the above embodiments of the apparatus are only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0097] This application also provides an electronic device. (See reference...) Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include: at least one processor 301, at least one communication bus 302, a user interface 303, at least one network interface 304, and a memory 305.

[0098] The communication bus 302 is used to enable communication between these components.

[0099] The user interface 303 may include a display screen and a camera. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0100] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0101] The processor 301 may include one or more processing cores. The processor 301 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 305, and by calling data stored in memory 305. Optionally, the processor 301 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 301 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 301 and may be implemented as a separate chip.

[0102] The memory 305 may include random access memory (RAM) or read-only memory. Optionally, the memory 305 may include a non-transitory computer-readable storage medium. The memory 305 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 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 touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 305 may also be at least one storage device located remotely from the aforementioned processor 301. (Refer to...) Figure 3 The memory 305, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and a lightning risk assessment application for offshore wind turbines.

[0103] exist Figure 3In the illustrated electronic device, the user interface 303 is primarily used to provide an input interface for the user and acquire user input data; while the processor 301 can be used to call the lightning risk assessment application for offshore wind turbines stored in the memory 305. When executed by one or more processors 301, the electronic device performs one or more of the methods described in the above embodiments. It should be noted that, for the foregoing method embodiments, for the sake of simplicity, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0104] This application also provides a non-transitory computer-readable storage medium storing instructions. When executed by one or more processors, these instructions cause an electronic device to perform one or more of the methods described in the above embodiments.

[0105] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0106] In the various embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between apparatuses or units may be electrical or other forms.

[0107] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0108] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0109] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, 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. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0110] The above description is merely an exemplary embodiment disclosed in this application and should not be construed as limiting the scope of this application. Any equivalent changes and modifications made in accordance with the teachings of this application shall still fall within the scope of this application.

[0111] This application is intended to cover any variations, uses, or adaptations disclosed herein that follow the general principles disclosed herein and include common knowledge or customary technical means in the art that are not described in this application.

Claims

1. A method for assessing lightning strike risk for offshore wind turbines, characterized in that, The method includes: In a lightning environment, the electrical structure parameters of the thunderstorm cloud around the target offshore wind turbine are obtained, and a thunderstorm cloud discharge model is constructed based on the thunderstorm cloud electrical structure parameters. Based on the aforementioned thunderstorm cloud-initiated discharge model, a spatial background electric field evolving over time is constructed; A pilot development model is built based on the spatial background electric field and the size parameters of each target structural part of the target offshore wind turbine. The upward discharge spatial tendency parameters are output based on the pilot development model. The upward discharge spatial tendency parameters include the position parameters of the target structural parts that meet the upward discharge initiation conditions under the current thunderstorm electric field conditions, and the directional deviation parameters of the upward pilot extending in different spatial directions after the target structural parts form an upward discharge. An upward lightning stochastic discharge model is constructed based on the upward discharge spatial tendency parameters, and upward leader evolution process parameters are output based on the upward lightning stochastic discharge model; the upward leader evolution process parameters are used to represent the dynamic formation and evolution process of the upward leader at the target structural location; Based on the aforementioned uplink leader evolution process parameters, the uplink leader spatiotemporal evolution parameters corresponding to the target offshore wind turbine are constructed, and the lightning strike risk is assessed using the uplink leader spatiotemporal evolution parameters.

2. The method according to claim 1, characterized in that, The process of acquiring the electrical structure parameters of thunderstorm clouds surrounding the target offshore wind turbine under lightning conditions, and constructing a thunderstorm cloud discharge model based on these parameters, specifically includes: The electrical structure parameters of the thunderstorm cloud surrounding the target offshore wind turbine are obtained under the lightning environment; the lightning environment includes a strong electric field environment, a dense salt spray environment, and a high humidity environment; the electrical structure parameters of the thunderstorm cloud include cloud-to-ground potential difference parameters, air equivalent conductivity parameters, and relative humidity parameters. Based on the electrical structure parameters of the thunderstorm cloud, a thunderstorm cloud discharge model is constructed by establishing a closed prediction equation set; the closed prediction equation set consists of atmospheric motion equation, pressure equation, thermodynamic energy equation, hydromorphic mass continuity equation, and hydromorphic charge density equation.

3. The method according to claim 2, characterized in that, The construction of the time-evolving spatial background electric field based on the thunderstorm cloud-initiated discharge model specifically includes: In the thunderstorm cloud-to-ground discharge model, the potential boundary conditions between the thunderstorm cloud and the ground surface are constrained based on the cloud-to-ground potential difference parameter. Based on the thunderstorm cloud initiation discharge model, the spatial distribution of the electrical structure parameters of the thunderstorm cloud is updated over time, reflecting the evolution of the electrical structure over time during the thunderstorm cloud initiation discharge process. After the timing update of the electrical structure parameters of the thunderstorm cloud is completed, the potential distribution within the spatial range where the target offshore wind turbine is located is calculated. Based on the potential distribution, the spatial background electric field is obtained by solving the spatial variation relationship of the potential.

4. The method according to claim 1, characterized in that, The process of building a pilot development model based on the spatial background electric field and the dimensional parameters of each target structural component of the target offshore wind turbine specifically includes: Under the influence of the spatial background electric field, the electric field distribution at each of the target structural parts of the target offshore wind turbine is calculated in combination with the corresponding dimensional parameters. The dimensional parameters include tower height, tower top geometric curvature, nacelle external dimensions, and blade geometric dimensions. Using the aforementioned size parameters as modeling constraints, the lead development model is constructed based on the aforementioned electric field distribution state.

5. The method according to claim 4, characterized in that, The uplink discharge spatial tendency parameters output based on the aforementioned leader development model specifically include: Based on the electric field distribution at the target structural location, determine whether the target structural location meets the initiation conditions for upward discharge; If the target structural part meets the initiation condition for upward discharge, the gate will determine the target structural part as a candidate initiation part; Determine the spatial position parameters corresponding to the candidate starting point, and after the upward discharge is formed at the candidate starting point, output the trend difference of the upward leader's development along different spatial directions under the influence of the spatial background electric field based on the leader development model; Based on the aforementioned trend differences, corresponding directional bias parameters are constructed; The spatial position parameter is combined with the directional bias parameter, and the upward discharge spatial tendency parameter is output.

6. The method according to claim 5, characterized in that, The parameters for the uplink pre-directed computational process output based on the uplink lightning random discharge model specifically include: Based on the upward discharge spatial tendency parameter, the order of upward discharge of each target structural part is randomly determined, and the upward leader start time parameter corresponding to each target structural part is determined. Based on the uplink leader start time parameter and combined with the direction bias parameter, the gradual extension behavior of the uplink leader in space is stochastically evolved, and the evolution state change of the uplink leader at the target structural part is output. Based on the aforementioned directional bias parameters, the extension behavior of the uplink leader along different spatial directions at each evolution time is randomly selected, and the spatial evolution path parameters corresponding to the uplink leader are output. The uplink leader start time parameter and the spatial evolution path parameter are jointly determined as the uplink leader programming process parameter.

7. The method according to claim 1, characterized in that, The lightning strike risk assessment using the uplink leader spatiotemporal evolution parameters specifically includes: The lightning strike risk assessment is performed using the uplink leader spatiotemporal evolution parameters. The lightning strike risk assessment includes assessment of the probability of lightning strike, assessment of the distribution of lightning strike structural parts, and assessment of lightning strike time sensitivity. Based on the risk component values ​​calculated from each of the aforementioned lightning interception risk assessments, a risk consistency judgment calculation is performed under spatiotemporal correlation constraints, and a comprehensive lightning interception risk value is output. Determine whether the comprehensive lightning strike risk value exceeds a preset threshold, and if it is confirmed that the comprehensive lightning strike risk value exceeds the preset threshold, confirm that the target offshore wind turbine has a lightning strike risk, and output the corresponding lightning strike structure location; If the comprehensive lightning strike risk value does not exceed the preset threshold, it is confirmed that the target offshore wind turbine does not have a lightning strike risk.

8. A lightning strike risk assessment device for offshore wind turbines, characterized in that, The device includes an acquisition module and a processing module, wherein, The acquisition module is used to acquire the electrical structure parameters of thunderstorm clouds around the target offshore wind turbine under lightning conditions, and to construct a thunderstorm cloud discharge model based on the thunderstorm cloud electrical structure parameters; and to construct a spatial background electric field that evolves over time based on the thunderstorm cloud discharge model. The processing module is used to build a leader development model based on the spatial background electric field and the size parameters of each target structural part of the target offshore wind turbine, and output upward discharge spatial tendency parameters based on the leader development model. The upward discharge spatial tendency parameters include the position parameters of the target structural parts that meet the upward discharge initiation conditions under the current thunderstorm electric field conditions, and the directional deviation parameters of the upward leader extending in different spatial directions after the formation of upward discharge in the target structural parts. Based on the upward discharge spatial tendency parameters, an upward lightning stochastic discharge model is constructed, and upward leader evolution process parameters are output based on the upward lightning stochastic discharge model. The upward leader evolution process parameters are used to represent the dynamic formation and evolution process of the upward leader at the target structural parts. Based on the upward leader evolution process parameters, the spatiotemporal evolution parameters of the upward leader corresponding to the target offshore wind turbine are constructed, and the lightning strike risk assessment is performed through the spatiotemporal evolution parameters of the upward leader.

9. An electronic device, characterized in that, The device includes a processor, a communication bus, a user interface, a network interface, and a memory. The memory is used to store instructions. The user interface and the network interface are used to communicate with other devices. The processor is used to execute the instructions stored in the memory to cause the electronic device to perform the method as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores instructions that, when executed, perform the method as described in any one of claims 1 to 7.

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