Wind power plant lightning stroke risk assessment method and device considering downlink lightning stroke and uplink lightning stroke

Abstract

The invention relates to the technical field of high voltage, in particular to a wind power plant lightning stroke risk assessment method and device giving consideration to downlink thunder and uplink thunder, and the method comprises the steps: obtaining environment data of the current position of a target wind power plant and multiple pieces of parameter information of triggering downlink thunder, self-triggering uplink thunder and externally triggering uplink thunder; establishing a structure-function relationship between the multiple pieces of parameter information and downlink thunder, self-triggering uplink thunder and external triggering uplink thunder based on the environment data; and based on the structure-function relationship, calculating the downlink lightning quantity, the self-triggering uplink lightning quantity and the external triggering uplink lightning quantity of the target wind power plant within the target time so as to evaluate the lightning stroke risk of the target wind power plant. According to the method, the characteristics of obvious large-scale trend and the like of the current wind turbine generator can be combined, the lightning stroke quantity change conditions in three lightning stroke discharge forms of downlink lightning stroke, self-triggering uplink lightning stroke and external triggering uplink lightning stroke are comprehensively considered, comprehensive and accurate evaluation of the lightning stroke risk of the target wind power plant is guaranteed, and design and construction of a lightning protection project of the large wind power plant are facilitated.

Description

Technical Field

[0001] The present application relates to the field of high voltage technology, and in particular to a method and device for assessing the lightning strike risk of a wind farm taking into account both downward and upward lightning. Background Art

[0002] The scale of new and cumulative wind turbine installations is rapidly increasing, and turbine heights and rotor diameters are also increasing. This significantly alters the fundamental physical characteristics of lightning strikes in clusters of ultra-tall wind turbines. The upward leader originating from the blade tip is longer, resulting in a higher incidence of upward lightning strikes and a gradually increasing risk of upward lightning strikes. Furthermore, the uncertainty and high risk of lightning activity mean that the probability of wind turbines being struck by lightning remains high, potentially leading to electromagnetic transient overvoltages within the turbine body and on the collector lines, threatening the safe and stable operation of wind farms. Therefore, lightning risk assessment for large wind farms is crucial.

[0003] In related technologies, there are many assessments of lightning strike risks for wind turbines, most of which focus on smaller-sized wind turbines and conduct downward lightning strike risk assessments on smaller-sized wind turbines.

[0004] However, the assessment method of wind turbine lightning strike risk in related technologies ignores the changes in wind turbines, that is, small-sized wind turbines are gradually replaced by large-sized and large-power wind turbines. As the height of the wind turbine body increases, the number and probability of being struck by upward lightning also increase accordingly. It is difficult to meet the calculation requirements of lightning strike risks of large-sized wind turbines and large wind farms in actual scenarios, and it needs to be solved urgently. Summary of the Invention

[0005] The present application provides a wind farm lightning strike risk assessment method and device that takes into account both downward and upward lightning, so as to solve the problem that the wind turbine lightning strike risk assessment method in the related art ignores the changes in wind turbines, that is, small-sized wind turbines are gradually replaced by large-sized and large-power wind turbines. As the height of the wind turbine body increases, the number and probability of being struck by upward lightning also increase significantly, which makes it difficult to meet the calculation requirements of the lightning strike risk of large-sized wind turbines and large wind farms in actual scenarios.

[0006] A first aspect of the present application provides a method for assessing the lightning strike risk of a wind farm that takes into account both downlink and uplink lightning, comprising the following steps: obtaining environmental data of the current location of a target wind farm, and obtaining multiple parameter information of triggered downlink lightning, self-triggered uplink lightning, and externally triggered uplink lightning in the target wind farm; based on the environmental data, establishing a structure-activity relationship between the multiple parameter information and the downlink lightning, the self-triggered uplink lightning, and the externally triggered uplink lightning; based on the structure-activity relationship, calculating the number of downlink lightning, the number of self-triggered uplink lightning, and the number of externally triggered uplink lightning in the target wind farm within a target time, so as to assess the lightning strike risk of the target wind farm based on the number of downlink lightning, the number of self-triggered uplink lightning, and the number of externally triggered uplink lightning.

[0007] Optionally, in one embodiment of the present application, the structure-activity relationship between the multiple parameter information and the downlink lightning, the self-triggered uplink lightning and the externally triggered uplink lightning is established based on the environmental monitoring data, including: calculating the equivalent collection area of the wind turbines in the target wind farm for the downlink lightning within the target time based on the environmental data; calculating the number of lightning strikes caused by the downlink lightning in the target wind farm within the target time based on the equivalent collection area; determining the structure-activity relationship between the multiple parameter information and the downlink lightning based on the number of lightning strikes, the number of channel grounding terminals in the wind farm struck by a single downlink lightning in the target wind farm, and the number of wind turbines in the target wind farm.

[0008] Optionally, in one embodiment of the present application, the structure-activity relationship between the multiple parameter information and the downlink thunder, the self-triggered uplink thunder and the externally triggered uplink thunder is established based on the environmental monitoring data, including: constructing the electric potential function, thundercloud electric potential density distribution function and density probability distribution function of the self-triggered uplink thunder based on the environmental monitoring data to calculate the probability that the local thundercloud electric field of the self-triggered uplink thunder exceeds the critical electric field threshold within the target time; calculating the number of times the local thundercloud electric field exceeds the critical electric field threshold based on the probability and the number of active thunderstorms in the self-triggered uplink thunder; determining the structure-activity relationship between the multiple parameter information and the self-triggered uplink thunder based on the number of times the local thundercloud electric field exceeds the critical electric field threshold and the average number of upward leaders of the self-triggered uplink thunder.

[0009] Optionally, in one embodiment of the present application, the density probability distribution function is:

[0010]

[0011] Among them, f E (E c ) is the density distribution probability function of cloud height, H max is the maximum height of thundercloud, H c is the cloud height, f H (H c ) is the cloud height density distribution function, f v (E c ·H c ) is the probability density distribution function of cloud potential.

[0012] Optionally, in one embodiment of the present application, the establishing of the structure-activity relationship between the multiple parameter information and the downlink lightning, the self-triggered uplink lightning and the externally triggered uplink lightning based on the environmental monitoring data includes: constructing the Weibull distribution function of the positive polarity ground-to-ground lightning events in the target wind farm based on the environmental monitoring data to calculate the number of ground-to-ground lightning generated by the wind turbines in the target wind farm within the target time; calculating the number of externally triggered uplink lightning of a single wind turbine within the target time based on the number of ground-to-ground lightning and the probability of the electric field generated by ground-to-ground lightning of the wind turbines in the target wind farm within the target time; determining the structure-activity relationship between the multiple parameter information and the externally triggered uplink lightning based on the number of externally triggered uplink lightning of the single wind turbine within the target time and the number of externally triggered uplink lightning within the target range around the location of the single wind turbine.

[0013] Optionally, in one embodiment of the present application, the calculation formula for the number of ground-to-ground flashes is:

[0014]

[0015] Among them, n +CG is the annual number of electric field flashovers generated at the wind turbine location, k +CG / CG is the positive polarity ground flash coefficient, π is the circumference of the circle, r eq is the equivalent radius, N g is the density of ground-to-ground lightning.

[0016] A second aspect of the present application provides a wind farm lightning strike risk assessment device that takes into account both downlink and uplink lightning, including: an acquisition module for acquiring environmental data of the current location of a target wind farm, and acquiring multiple parameter information of triggered downlink lightning, self-triggered uplink lightning, and externally triggered uplink lightning in the target wind farm; an establishment module for establishing, based on the environmental data, a structure-activity relationship between the multiple parameter information and the downlink lightning, the self-triggered uplink lightning, and the externally triggered uplink lightning; an evaluation module for calculating, based on the structure-activity relationship, the number of downlink lightning, the number of self-triggered uplink lightning, and the number of externally triggered uplink lightning in the target wind farm within a target time, so as to evaluate the lightning strike risk of the target wind farm according to the number of downlink lightning, the number of self-triggered uplink lightning, and the number of externally triggered uplink lightning.

[0017] Optionally, in one embodiment of the present application, the establishment module includes: a first calculation unit, used to calculate the equivalent collection area of the wind turbines in the target wind farm for the downward lightning within the target time based on the environmental data; a second calculation unit, used to calculate the number of lightning strikes caused by the downward lightning in the target wind farm within the target time based on the equivalent collection area; a first determination unit, used to determine the structure-activity relationship between the multiple parameter information and the downward lightning based on the number of lightning strikes, the number of channel grounding terminals in the wind farm struck by a single downward lightning in the target wind farm, and the number of wind turbines in the target wind farm.

[0018] Optionally, in one embodiment of the present application, the establishment module includes: a third calculation unit, used to construct the electric potential function, thundercloud electric potential density distribution function and density probability distribution function of the self-triggered upward lightning based on the environmental monitoring data, so as to calculate the probability that the local thundercloud electric field of the self-triggered upward lightning exceeds the critical electric field threshold within the target time; a fourth calculation unit, used to calculate the number of times the local thundercloud electric field exceeds the critical electric field threshold based on the probability and the number of active thunderstorms in the self-triggered upward lightning; a second determination unit, used to determine the structure-activity relationship between the multiple parameter information and the self-triggered upward lightning based on the number of times the local thundercloud electric field exceeds the critical electric field threshold and the average number of upward leaders of the self-triggered upward lightning.

[0019] Optionally, in one embodiment of the present application, the density probability distribution function is:

[0020]

[0021] Among them, f E (E c ) is the density distribution probability function of cloud height, H max is the maximum height of thundercloud, H c is the cloud height, f H (H c ) is the cloud height density distribution function, f v (E c ·H c ) is the probability density distribution function of cloud potential.

[0022] Optionally, in one embodiment of the present application, the establishment module includes: a fifth calculation unit, used to construct a Weibull distribution function of positive polarity ground-to-ground lightning events in the target wind farm based on the environmental monitoring data, so as to calculate the number of ground-to-ground lightning generated by the wind turbines in the target wind farm within the target time; a sixth calculation unit, used to calculate the number of externally triggered upward lightning of a single wind turbine within the target time based on the number of ground lightning and the probability of the electric field generated by ground lightning of the wind turbines in the target wind farm within the target time; a third determination unit, used to determine the structure-activity relationship between the multiple parameter information and the externally triggered upward lightning based on the number of externally triggered upward lightning of the single wind turbine within the target time and the number of externally triggered upward lightning within the target range around the location of the single wind turbine.

[0023] Optionally, in one embodiment of the present application, the calculation formula for the number of ground-to-ground flashes is:

[0024]

[0025] Among them, n +CG is the annual number of electric field flashovers generated at the wind turbine location, k +CG / CG is the positive polarity ground flash coefficient, π is the circumference of the circle, r eq is the equivalent radius, N g is the density of ground-to-ground lightning.

[0026] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the wind farm lightning strike risk assessment method that takes into account both downward and upward lightning as described in the above embodiment.

[0027] A fourth aspect of the present application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned method for assessing the lightning risk of a wind farm taking into account both downward and upward lightning.

[0028] A fifth aspect of the present application provides a computer program product, including a computer program. When the computer program is executed, it is used to implement the above-mentioned wind farm lightning strike risk assessment method that takes into account both downward and upward lightning.

[0029] The embodiment of the present application can establish a structure-effect relationship between multiple parameters and down-going lightning, self-triggered up-going lightning, and externally triggered up-going lightning based on environmental information, and then calculate the number of down-going lightning, self-triggered up-going lightning, and externally triggered up-going lightning in the target wind farm within the target time to evaluate the lightning strike risk of the target wind farm. In this way, it is achieved by combining the characteristics of the current large-scale trend of wind turbines, comprehensively considering the changes in the number of lightning strikes under the three lightning discharge forms of down-going lightning, self-triggered up-going lightning, and externally triggered up-going lightning, ensuring a comprehensive and accurate assessment of the lightning strike risk of the target wind farm, and helping to serve the design and construction of lightning protection projects for large wind farms in a simple and efficient manner. In this way, it solves the problem that the wind turbine lightning strike risk assessment method in the related art ignores the changes in wind turbines, that is, small-sized wind turbines are gradually replaced by large-sized and high-power wind turbines. As the height of the wind turbine increases, the number and probability of being struck by up-going lightning also increase accordingly, making it difficult to meet the calculation requirements of the lightning strike risk of large-sized wind turbines and large wind farms in actual scenarios.

[0030] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0032] Figure 1 This is a flow chart of a method for assessing the risk of lightning strikes on a wind farm that takes into account both downward and upward lightning strikes, provided according to an embodiment of the present application;

[0033] Figure 2 A schematic diagram of different types of lightning strikes according to an embodiment of the present application;

[0034] Figure 3 This is a schematic diagram showing the proportion of lightning strike probability of externally triggered upward lightning as a function of distance according to one embodiment of the present application;

[0035] Figure 4 This is a schematic diagram of calculation results of the number of downlink lightning strikes suffered by a target wind farm according to one embodiment of the present application;

[0036] Figure 5 A schematic diagram of a probability function of the density distribution of cloud heights in a target wind farm according to one embodiment of the present application;

[0037] Figure 6 This is a schematic diagram of calculation results of the number of self-triggered uplighting and externally triggered uplighting strikes suffered by a target wind farm in one embodiment of the present application;

[0038] Figure 7This is a schematic structural diagram of a wind farm lightning strike risk assessment device that takes into account both downward and upward lightning strikes, provided according to an embodiment of the present application;

[0039] Figure 8 A schematic diagram of the structure of an electronic device provided according to an embodiment of the present application.

[0040] Reference numerals:

[0041] 10- Wind farm lightning risk assessment device taking into account both downward and upward lightning: 100- acquisition module, 200- establishment module and 300- assessment module; 801- memory, 802- processor and 803- communication interface. DETAILED DESCRIPTION

[0042] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0043] The following describes a method and device for assessing the lightning strike risk of a wind farm that takes into account both downward and upward lightning according to an embodiment of the present application with reference to the accompanying drawings. In view of the fact that the wind turbine lightning strike risk assessment method in the related art mentioned in the above background technology ignores the changes in wind turbines, that is, small-sized wind turbines are gradually replaced by large-sized and large-power wind turbines, and as the height of the wind turbine body increases, the number and probability of being struck by upward lightning also increase accordingly, making it difficult to meet the calculation requirements of the lightning strike risk of large-sized wind turbines and large wind farms in actual scenarios, the present application provides a method for assessing the lightning strike risk of a wind farm that takes into account both downward and upward lightning. In this method, a structure-effect relationship between multiple parameters and downward lightning, self-triggered upward lightning, and externally triggered upward lightning can be established based on environmental information, and then the number of downward lightning, self-triggered upward lightning, and externally triggered upward lightning in the target wind farm within the target time can be calculated to assess the lightning strike risk of the target wind farm. This approach, combined with the current trend toward larger wind turbines, comprehensively considers the changes in the number of lightning strikes under the three lightning discharge forms of downward, self-triggered upward, and externally triggered upward lightning. This ensures a comprehensive and accurate assessment of the lightning strike risk at the target wind farm, contributing to the simple and efficient design and construction of lightning protection projects for large wind farms. This addresses the problem that existing methods for assessing lightning strike risk for wind turbines in related technologies ignore the changes in wind turbines, namely, the gradual replacement of small-sized wind turbines with large-sized, high-power wind turbines. As the height of the wind turbine increases, the number and probability of upward lightning strikes also increase significantly, making it difficult to meet the calculation requirements for lightning strike risks for large-sized wind turbines and large wind farms in actual scenarios.

[0044] Specifically, Figure 1This is a flow chart of a method for assessing the lightning risk of a wind farm taking into account both downward and upward lightning, provided in an embodiment of the present application.

[0045] like Figure 1 As shown, the wind farm lightning strike risk assessment method considering both downward and upward lightning includes the following steps:

[0046] In step S101 , environmental data of the current location of the target wind farm is obtained, and multiple parameter information of triggered downlink mines, self-triggered uplink mines and externally triggered uplink mines in the target wind farm is obtained.

[0047] It is understandable that the target wind farm here refers to a large wind farm with large wind turbines for wind power generation. In the current operation of wind farms, the length of large wind turbine blades has reached 120 meters and the fuselage height is as high as 200 meters. Such large-power and large-sized wind turbines are more susceptible to upward lightning strikes. According to natural lightning observation data, when the height reaches 100 meters, the risk of upward lightning strikes is only 15%. When the height reaches 200 meters and 300 meters, the risk of upward lightning strikes accounts for 50% and 75% respectively. At the same time, considering the distribution of lightning density at different ground flashovers, the number of upward lightning strikes suffered by large-sized wind turbines increases significantly with the increase in the height of the body. That is, the proportion of upward lightning strikes increases rapidly, and the risk of upward lightning strikes is also gradually increasing.

[0048] The fundamental lightning strike characteristics of wind turbines have changed significantly as wind turbines are becoming larger. In the wind turbine blade lightning strike risk assessment method considering the pilot development model, upward lightning strikes are an important part of the lightning strikes suffered by wind turbines. Figure 2 Schematic diagram of different types of lightning strikes according to an embodiment of the present application. Figure 2 As shown in the figure, with the trend toward larger wind turbine sizes, the discharge pattern of upward lightning strikes is not only related to self-triggered upward lightning strikes induced by cloud-to-ground flashes within the cloud, but also closely related to externally triggered upward lightning strikes induced by positive ground-to-ground flashes within tens of kilometers. Furthermore, depending on the charge polarity and structural distribution characteristics of the cloud layer directly above the wind turbine, charges of different polarities are transmitted from the leader to the wind turbine and then to the ground, generating corresponding positive, negative, and bipolar upward lightning strikes.

[0049] Based on this, when conducting a lightning strike risk assessment on a wind farm, the embodiments of the present application can be carried out from multiple aspects such as but not limited to downward lightning, self-triggered upward lightning and externally triggered upward lightning. Since these lightning strikes are closely related to the local atmospheric environment and ground lightning, cloud lightning density, positive polarity ground lightning distribution characteristics, etc., the embodiments of the present application can obtain the atmospheric environment data of the current location of the target wind farm and multiple parameter information of the triggered downward lightning, self-triggered upward lightning and externally triggered upward lightning in the target wind farm, and then conduct further lightning strike risk assessment research based on this information.

[0050] Step S102: Based on the environmental data, a structure-activity relationship is established between a plurality of parameter information and downlink mines, self-triggered uplink mines and externally triggered uplink mines.

[0051] Based on the relevant descriptions of other embodiments, it can be understood that lightning strikes such as downward lightning, self-triggered upward lightning and externally triggered upward lightning are closely related to the local atmospheric environment of the target wind farm and the density of ground lightning, cloud lightning, and the distribution characteristics of positive polarity ground lightning. Therefore, the embodiments of the present application can establish a structure-activity relationship between multiple parameter information and downward lightning, self-triggered upward lightning and externally triggered upward lightning based on environmental data.

[0052] For example, the present application can collect a large amount of atmospheric environment data, including but not limited to meteorological data (such as temperature, humidity, air pressure, wind speed, wind direction, etc.), electric field data (such as atmospheric electric field strength, direction, etc.), and ground lightning, cloud-to-ground lightning density, positive polarity ground lightning distribution and other related data. Then, data analysis methods and mathematical models are used to process and analyze these data. For example, statistical analysis methods are used to find the correlation between different parameters and the frequency and intensity of different types of lightning strikes, etc., and to establish a structure-activity relationship that can accurately describe the lightning risk of the target wind farm with multiple parameter information such as cloud-to-ground lightning density or cloud-to-ground lightning density, wind field size, equivalent radius and other parameters.

[0053] Therefore, the embodiments of the present application can establish a structure-activity relationship between multiple parameter information and different types of lightning strikes based on atmospheric environment data. By establishing this relationship, we can better understand the intrinsic connection and laws between factors such as the atmospheric environment and downward lightning, self-triggered upward lightning, and externally triggered upward lightning, thereby improving the ability to predict the conditions for the occurrence of different types of lightning strikes in the target wind farm and the accuracy of the prediction of their occurrence probability, thereby providing important theoretical support and technical guidance for lightning protection of the target wind farm.

[0054] Optionally, in one embodiment of the present application, based on environmental monitoring data, a structure-effect relationship between multiple parameter information and downlink lightning, self-triggered uplink lightning and externally triggered uplink lightning is established, including: calculating the equivalent collection area of the wind turbines in the target wind farm for downlink lightning within the target time based on the environmental data; calculating the number of lightning strikes caused by downlink lightning in the target wind farm within the target time based on the equivalent collection area; determining the structure-effect relationship between multiple parameter information and downlink lightning based on the number of lightning strikes, the number of channel grounding terminals in the wind farm struck by a single downlink lightning in the target wind farm, and the number of wind turbines in the target wind farm.

[0055] In some embodiments, when establishing a structure-effect relationship between multiple parameter information and downlink lightning, the present application may calculate the equivalent collection area of downlink lightning for wind turbines in a target wind farm within a target time based on environmental data, and calculate the number of lightning strikes caused by downlink lightning within the target time based on the equivalent collection area. The target time here can be understood as the length of time referenced when assessing the lightning strike risk of a target wind farm, for example, six months, one year, etc.

[0056] For example, the embodiment of the present application can understand the number of annual hazardous events for general structures based on environmental data, and then evaluate the incidence of down-going lightning strikes in the target wind farm based on the established standard of the number of annual hazardous events for general structures. Among them, the general structure here can be understood as a building or facility structure with a certain universality, such as ordinary buildings, transmission line towers, etc., which are similar to the structures of wind farms to a certain extent and are faced with the risk of being struck by lightning. The electrical characteristics, physical form and other characteristics of these general structures in the lightning environment are comparable to those of wind farms to a certain extent, and the situations and laws of their being struck by lightning can provide a reference for the study of lightning strikes in target wind farms.

[0057] For general structures, the annual number of hazardous events refers to the number of dangerous events that occur within a year that could cause damage or affect their normal operation. Lightning strikes are a significant example of such dangerous events. By counting and analyzing the annual number of hazardous events, such as lightning strikes, for general structures, we can understand the level of risk these structures face in the natural environment and summarize the patterns and frequency of these events.

[0058] For example, considering that the wind turbine may be affected by the expected lightning current (the expected lightning current that the wind turbine may suffer under specific meteorological conditions, geographical environment and lightning activity laws) and the probability density function of the rotation angle (the blades of the wind turbine will continue to rotate during operation, and the rotation angle is a random variable, and its probability density function describes the probability distribution of the blades at different rotation angles), the equivalent collection area A of the wind turbine in the embodiment of the present application is g It can be expressed as, but not limited to:

[0059]

[0060] Among them, f(I p ) is the expected lightning current, g(θ) is the rotation angle, θ is the blade angle, a (k) represents the blade tip angle, I pmax Indicates the maximum lightning current, I pmin Indicates the minimum lightning current.

[0061] Furthermore, in the embodiment of the present application, the lightning strike N caused by the downlink lightningDL The calculation formula of quantity can be expressed as but not limited to:

[0062] N DL =N g ·A g ·C(2)

[0063] Among them, A g is the equivalent area of the structure. The additional location factor C is usually used to consider the impact of surrounding objects and terrain on lightning incidence. N g Indicates the density of ground-to-ground lightning strikes. The equivalent area of a structure is understood here as a measure of how much area a structure has to effectively collect lightning in a lightning environment. This is achieved by taking into account factors such as the complex shape and structure of a wind turbine and its position in space, and converting them into an equivalent plane area to indicate its likelihood of being struck by lightning.

[0064] Determine the number of lightning strikes N caused by down-going lightning DL Then, the embodiment of the present application can determine the structure-effect relationship between multiple parameter information and downward lightning based on the number of lightning strikes, the number of channel grounding terminals in the target wind farm that were struck by a single downward lightning strike, and the number of wind turbines in the target wind farm. That is, the annual average number of downward lightning strikes (downward lightning) in the target wind farm can be evaluated as:

[0065]

[0066] Among them, n MDL is the number of channel grounding terminals in a single down-stroke wind farm, n turb is the number of wind turbines.

[0067] Optionally, in one embodiment of the present application, based on environmental monitoring data, a structure-activity relationship between multiple parameter information and downlink lightning, self-triggered uplink lightning, and externally triggered uplink lightning is established, including: constructing the electric potential function, thundercloud electric potential density distribution function, and density probability distribution function of the self-triggered uplink lightning based on the environmental monitoring data to calculate the probability that the local thundercloud electric field exceeds the critical electric field threshold within the target time of the self-triggered uplink lightning; calculating the number of times the local thundercloud electric field exceeds the critical electric field threshold based on the probability and the number of active thunderstorms in the self-triggered uplink lightning; determining the structure-activity relationship between multiple parameter information and the self-triggered uplink lightning based on the number of times the local thundercloud electric field exceeds the critical electric field threshold and the average number of uplink leaders of the self-triggered uplink lightning. Among them, the density probability distribution function is:

[0068]

[0069] Among them, f E (E c ) is the density distribution probability function of cloud height, H maxis the maximum height of thundercloud, which is usually 6000m. c is the cloud height, f H (H c ) is the cloud height density distribution function, f v (E c ·H c ) is the probability density distribution function of cloud potential.

[0070] In some embodiments, when establishing a structure-activity relationship between multiple parameter information of self-triggered upward lightning based on environmental monitoring data, the present application can first construct the potential function, thundercloud potential density distribution function and density probability distribution function of the self-triggered upward lightning based on the environmental monitoring data to calculate the probability that the local thundercloud electric field of the self-triggered upward lightning exceeds the critical electric field threshold within the target time, and then calculate the number of times the local thundercloud electric field exceeds the critical electric field threshold based on the probability and the number of active thunderstorms in the self-triggered upward lightning.

[0071] For example, the annual frequency (N) of spontaneous upward lightning (self-triggered upward lightning) of wind turbines is represented by the number of times the local thundercloud electric field in the target wind farm exceeds the critical field environment each year. UL-self ).

[0072] First, the potential function V of the local thundercloud electric field in the target wind farm in the embodiment of the present application is cloud (unit V) can be expressed as the peak current of the first return stroke of the downward lightning I p The function of (unit kA) can be expressed as, but not limited to:

[0073]

[0074] Thundercloud potential density distribution function f v (V cloud ) can be expressed as a logarithmic distribution:

[0075]

[0076] Among them, μ v It represents the position parameter, which reflects the average level of thundercloud potential density on a logarithmic scale and is related to factors such as the average potential state of the thundercloud as a whole. It can generally be taken as μ v =17.74V;σ v It represents the scaling function, which describes the degree of dispersion or fluctuation of the electric potential density of thunderclouds around the mean. The larger σ is, the more dispersed the distribution of electric potential density is, the higher the degree of dispersion of the data is, and the flatter the distribution curve is. The smaller σ is, the more concentrated the distribution is around the mean, and the steeper the curve is. Generally, σ is taken as v =0.53.

[0077] Then, the density probability function f E(E c ) can be expressed as a proportional distribution:

[0078]

[0079] Among them, f E (E c ) is the density distribution probability function of cloud height, H max is the maximum height of thundercloud, which is usually 6000m. c is the cloud height, f H (H c ) is the cloud height density distribution function, f v (E c ·H c ) is the probability density distribution function of cloud potential.

[0080] Different thundercloud heights correspond to different distribution probabilities. Therefore, the embodiment of the present application can obtain the probability P of the local thundercloud electric field exceeding the critical field environment in the target wind farm each year based on the density probability function. Ecrit1 .

[0081] According to the probability P of the local thundercloud electric field exceeding the critical field environment each year Ecrit1 and the number of active thunderstorms in the target wind farm each year caused by self-triggered upward lightning. In this embodiment of the present application, the number of times the local thundercloud electric field in the target wind farm exceeds the critical electric field threshold each year, that is, the number of times the electric field intensity in a certain local area of the thundercloud increases to exceed the minimum electric field intensity value that can cause ionization, breakdown, and discharge of a medium such as air. The calculation formula can be, but is not limited to, expressed as:

[0082] N UL-self =n storm ·P Ecrit1 (7)

[0083] Among them, N UL-self is the annual frequency of spontaneous rising lightning of wind turbines, n storm is the number of active thunderstorms, P Ecrit1 is the annual probability that the local thundercloud electric field exceeds the critical electric field threshold.

[0084] The number of active thunderstorms in the embodiment of the present application can be roughly estimated by, but not limited to, the number of active thunderstorms occurring in a certain area from lightning density data monitored by a lightning location system (LLS). The formula can be, but not limited to, expressed as:

[0085] n storm =(N g +N IC )·A storm (8)

[0086] Among them, N IC represents the number of cloud-to-ground flashes without ground-to-ground flash activity, A storm is the size of the thunderstorm that affects the wind farm, N g Indicates the density of ground-to-ground lightning.

[0087] After evaluating the value of lightning strike accident of a single wind turbine, N UL-self , combined with the number of times the local thundercloud electric field exceeds the critical electric field threshold and the average number of upward leaders of self-triggered upward thunder, the embodiment of the present application can determine the structure-activity relationship between multiple parameter information and self-triggered upward thunder. That is, the annual number of self-triggered upward thunder in the entire target wind farm It can be expressed as, but not limited to:

[0088]

[0089] Among them, n UL-self is the average number of upward leaders of self-triggered upward lightning in the wind farm.

[0090] Optionally, in one embodiment of the present application, based on environmental monitoring data, a structure-activity relationship between multiple parameter information and downlink lightning, self-triggered uplink lightning and externally triggered uplink lightning is established, including: based on environmental monitoring data, constructing a Weibull distribution function of positive polarity ground-to-ground lightning events in the target wind farm to calculate the number of ground-to-ground lightning generated by wind turbines in the target wind farm within the target time; calculating the number of externally triggered uplink lightning of a single wind turbine within the target time based on the number of ground-to-ground lightning and the probability of the electric field generated by ground-to-ground lightning of wind turbines in the target wind farm within the target time; determining the structure-activity relationship between multiple parameter information and externally triggered uplink lightning based on the number of externally triggered uplink lightning of a single wind turbine within the target time and the number of externally triggered uplink lightning within the target range around the location of the single wind turbine. The calculation formula for the number of ground-to-ground lightning is:

[0091]

[0092] Among them, n +CG is the annual number of electric field flashovers generated at the wind turbine location, k +CG / CG is the positive polarity ground flash coefficient, π is the circumference of the circle, r eq is the equivalent radius, N g is the density of ground-to-ground lightning.

[0093] In other embodiments, when establishing a structure-activity relationship between multiple parameter information and externally triggered upward lightning based on environmental monitoring data, the present application may, but is not limited to, first construct a Weibull distribution function of positive polarity ground-to-ground lightning events in the target wind farm based on the environmental monitoring data to calculate the number of ground-to-ground lightning generated by the wind turbines in the target wind farm within the target time, and then calculate the number of externally triggered upward lightning of a single wind turbine within the target time based on the number of ground-to-ground lightning and the probability of the electric field generated by the ground-to-ground lightning of the wind turbines in the target wind farm within the target time. Wherein, a positive polarity ground-to-ground lightning event refers to the discharge phenomenon that occurs between positive charges in the cloud and the ground during thunderstorm weather.

[0094] For example, Figure 3 This is a diagram showing the percentage of lightning strikes caused by externally triggered upward lightning as a function of distance, according to one embodiment of the present application. Distance refers to the distance between the trigger source (e.g., externally triggered upward lightning) and the wind turbine, and percentage refers to the relative probability of externally triggered upward lightning occurring at different distances within a certain statistical range. For example, within a 5-kilometer radius centered on a tower, statistics show that upward lightning strikes triggered within 1 kilometer of the tower account for 30% of the total upward lightning strikes, and within 2 kilometers account for 50%. This allows for analysis of the distribution of lightning strikes as a function of distance.

[0095] like Figure 3 As shown, in the embodiment of the present application, the positive polarity ground lightning event can be represented by Weibull distribution, and the function can be, but is not limited to, represented as:

[0096]

[0097] Where r is the distance between the trigger source such as external up-going lightning and the wind turbine location, is the Weibull distribution of the positive polarity ground-to-ground lightning event, λ and β are the scale parameter and shape parameter respectively. In the embodiment of the present application, they can be set to, but are not limited to, 24 and 2.5.

[0098] The annual number of electric field flashes generated at the wind turbine location n +CG It can be expressed as:

[0099]

[0100] Among them, k +CG / cG is the positive polarity ground flash coefficient.

[0101] Furthermore, combining formulas (10)-(11), n +CG It can be expressed as

[0102]

[0103] Among them, r eqis the equivalent radius, which in the embodiment of the present application may be, but is not limited to, 27 km.

[0104] Number of externally triggered upward lightning strikes triggered by a single wind turbine N UL-other The estimates may include, but are not limited to:

[0105] N UL-other =n CG ·P CG→ΔEcrit +n IC P IC→ΔEcrit (13)

[0106] Among them, n CG is the number of ground-to-ground lightning (CG) that can affect wind turbines in a year, P CG→ΔEcrit is the probability of the electric field generated by a ground-to-ground (CG) lightning event at the wind turbine location.

[0107] Formula (13) can be simplified as:

[0108] N UL-other ≈n +CG ·P +CG→ΔEcrit (14)

[0109] Among them, n +CG is at the maximum radius r max The annual number of positive polarity ground flashovers affecting wind turbines within the range.

[0110] After obtaining the number of externally triggered uplinks of a single wind turbine within the target time, the embodiment of the present application can determine the structure-effect relationship between multiple parameter information and externally triggered uplinks in combination with the number of externally triggered uplinks within the target range around the location of the single wind turbine.

[0111] That is, the annual number of upward lightning triggered outside the entire wind farm It can be expressed as:

[0112]

[0113] Among them, n UL-other is the number of upward lightning flashes triggered by nearby lightning events, n UL-other It can be expressed as:

[0114] n UL-other ≈[floor(L park / d UL )+1]·[floor(W park / d UL )+1](16)

[0115] Among them, d UL It is 75% of the difference between the height of thundercloud and the height of the entire wind turbine. park and Wpark are the length and width of the wind farm respectively.

[0116] Step S103: Based on the structure-activity relationship, the number of downlink lightning, the number of self-triggered uplink lightning, and the number of externally triggered uplink lightning in the target wind farm within the target time are calculated to evaluate the lightning strike risk of the target wind farm according to the number of downlink lightning, the number of self-triggered uplink lightning, and the number of externally triggered uplink lightning.

[0117] As a possible implementation method, after constructing a structure-activity relationship between multiple parameter information and downlink lightning, self-triggered uplink lightning and externally triggered uplink lightning, the embodiment of the present application can calculate the number of downlink lightning, self-triggered uplink lightning and externally triggered uplink lightning in the target wind farm within the target time based on the calculation formulas of downlink lightning, self-triggered uplink lightning and externally triggered uplink lightning in the structure-activity relationship, thereby evaluating the lightning strike risk of the target wind farm based on the number of downlink lightning, self-triggered uplink lightning and externally triggered uplink lightning.

[0118] For example, assume the target wind farm's wind turbines are at zero angle in a stationary state, with a tower height of 70 meters, a rotor diameter of 80 meters, and a maximum height above the ground of 110 meters. Table 1 shows the equivalent intercept area of three blades at different peak currents at zero angle in the stationary state of the wind turbine, which can be expressed as follows, but is not limited to:

[0119] Table 1

[0120]

[0121] The calculation result of the number of downward lightning strikes on the target wind farm is as follows: Figure 4 shown.

[0122] Furthermore, assuming that the target wind farm has 100 wind turbines and covers an area of 36km 2 The average lightning density is 0.5 times / (km 2 Taking into account the lightning stroke factor of 1 at multiple grounding points, the maximum number of downward lightning strikes in a large wind farm is 11.5 times.

[0123] Considering that the negative charge center area is closely related to the -10℃ isotherm, the embodiment of the present application can first obtain the different negative charge center area height distributions of the target wind farm in spring and winter, summer and autumn, and the annual average based on the relevant meteorological measurement results. Then, by evaluating the -10℃ isotherm height of the negative charge layer, the embodiment of the present application can confirm and obtain the following: Figure 5 The density distribution probability function f of the cloud height of the target wind farm is shown as E (E c ) schematic diagram.

[0124] The calculation results of the number of self-triggered upward lightning and externally triggered upward lightning strikes on the target wind farm are as follows: Figure 6 As shown in the figure, the thunderstorm scale for a large wind farm is within 1 km of the edge of the large wind farm. Considering an ideal square wind farm layout, the calculated number of self-triggered lightning strikes by upward lightning in a large wind farm with 100 turbines can reach more than 35 times, and the number of externally triggered lightning strikes by upward lightning can reach more than 100 times, posing a significant risk to the wind turbines in the wind farm.

[0125] According to the wind farm lightning risk assessment method that takes into account both downlink and uplink lightning, proposed in the embodiment of the present application, a structure-effect relationship between multiple parameters and downlink lightning, self-triggered uplink lightning, and externally triggered uplink lightning can be established based on environmental information, and then the number of downlink lightning, self-triggered uplink lightning, and externally triggered uplink lightning in the target wind farm within the target time can be calculated to assess the lightning risk of the target wind farm. In this way, the lightning risk of the target wind farm can be assessed by comprehensively considering the changes in the number of lightning strikes under the three lightning discharge forms of downlink lightning, self-triggered uplink lightning, and externally triggered uplink lightning, taking into account the current trend of large-scale wind turbines. This ensures a comprehensive and accurate assessment of the lightning risk of the target wind farm, which helps to serve the design and construction of lightning protection projects for large wind farms in a simple and efficient manner. This solves the problem that the assessment method of wind turbine lightning strike risk in related technologies ignores the changes in wind turbines, that is, small-sized wind turbines are gradually replaced by large-sized and large-power wind turbines. As the height of the wind turbine body increases, the number and probability of being struck by upward lightning also increase accordingly, making it difficult to meet the calculation requirements of lightning strike risks of large-sized wind turbines and large wind farms in actual scenarios.

[0126] Next, a wind farm lightning strike risk assessment device taking into account both downward and upward lightning strikes, proposed in accordance with an embodiment of the present application, will be described with reference to the accompanying drawings.

[0127] Figure 7 Schematic diagram of the structure of a wind farm lightning risk assessment device that takes into account both downward and upward lightning according to an embodiment of the present application.

[0128] like Figure 7 As shown, the wind farm lightning strike risk assessment device 10 taking into account both downward and upward lightning includes: an acquisition module 100 , an establishment module 200 and an assessment module 300 .

[0129] The acquisition module 100 is used to acquire environmental data of the current location of the target wind farm, and to acquire multiple parameter information of triggered downlink mines, self-triggered uplink mines and externally triggered uplink mines in the target wind farm.

[0130] The establishment module 200 is used to establish the structure-activity relationship between multiple parameter information and downlink mines, self-triggered uplink mines and externally triggered uplink mines based on environmental data.

[0131] The evaluation module 300 is used to calculate the number of downlink lightning, self-triggered uplink lightning and externally triggered uplink lightning in the target wind farm within the target time based on the structure-activity relationship, so as to evaluate the lightning strike risk of the target wind farm based on the number of downlink lightning, self-triggered uplink lightning and externally triggered uplink lightning.

[0132] Optionally, in one embodiment of the present application, the establishment module includes: a first calculation unit, a second calculation unit and a first determination unit.

[0133] The first calculation unit is used to calculate the equivalent collection area of the wind turbines in the target wind farm against downward lightning within the target time based on the environmental data.

[0134] The second calculation unit is used to calculate the number of lightning strikes caused by downgoing lightning in the target wind farm within the target time according to the equivalent collection area.

[0135] The first determining unit is used to determine the structure-effect relationship between multiple parameter information and downlink lightning based on the number of lightning strikes, the number of channel grounding terminals in the target wind farm caused by a single downlink lightning strike, and the number of wind turbines in the target wind farm.

[0136] Optionally, in one embodiment of the present application, the establishment module includes: a third calculation unit, a fourth calculation unit and a second determination unit.

[0137] Among them, the third calculation unit is used to construct the electric potential function, thundercloud electric potential density distribution function and density probability distribution function of self-triggered upward lightning based on environmental monitoring data, so as to calculate the probability that the local thundercloud electric field of self-triggered upward lightning exceeds the critical electric field threshold within the target time.

[0138] The fourth calculation unit is used to calculate the number of times the local thundercloud electric field exceeds the critical electric field threshold based on the probability and the number of active thunderstorms in the self-triggered uplink lightning.

[0139] The second determining unit is used to determine the structure-activity relationship between multiple parameter information and self-triggered upward thunder based on the number of times the local thundercloud electric field exceeds the critical electric field threshold and the average upward leader number of self-triggered upward thunder.

[0140] Optionally, in one embodiment of the present application, the density probability distribution function is:

[0141]

[0142] Among them, f E (E c ) is the density distribution probability function of cloud height, H max is the maximum height of thundercloud, which is usually 6000m. c is the cloud height, f H (Hc ) is the cloud height density distribution function, f v (E c ·H c ) is the probability density distribution function of cloud potential.

[0143] Optionally, in one embodiment of the present application, the establishment module includes: a fifth calculation unit, a sixth calculation unit and a third determination unit.

[0144] The fifth calculation unit is used to construct a Weibull distribution function of positive polarity ground-to-ground lightning events in the target wind farm based on environmental monitoring data, so as to calculate the number of ground-to-ground lightning events generated by wind turbines in the target wind farm within a target time.

[0145] The sixth calculation unit is used to calculate the number of externally triggered upward lightning of a single wind turbine generator set within the target time according to the number of ground lightning and the probability of the electric field generated by ground lightning of the wind turbine generator set in the target wind farm within the target time.

[0146] The third determination unit is used to determine the structure-activity relationship between multiple parameter information and externally triggered uplink mines based on the number of externally triggered uplink mines of a single wind turbine within a target time and the number of externally triggered uplink mines within a target range around the location of the single wind turbine.

[0147] Optionally, in one embodiment of the present application, the calculation formula for the number of ground-to-ground lightning is:

[0148]

[0149] Among them, n +CG is the annual number of electric field flashovers generated at the wind turbine location, k +CG / CG is the positive polarity ground flash coefficient, π is the circumference of the circle, r eq is the equivalent radius, N g is the density of ground-to-ground lightning.

[0150] It should be noted that the above explanation of the embodiment of the wind farm lightning strike risk assessment method taking into account both downward and upward lightning is also applicable to the wind farm lightning strike risk assessment device taking into account both downward and upward lightning in this embodiment, and will not be repeated here.

[0151] According to the wind farm lightning risk assessment device that takes into account both downlink and uplink lightning, proposed in the embodiment of the present application, a structure-effect relationship between multiple parameters and downlink lightning, self-triggered uplink lightning, and externally triggered uplink lightning can be established based on environmental information, and then the number of downlink lightning, self-triggered uplink lightning, and externally triggered uplink lightning in the target wind farm within the target time can be calculated to assess the lightning risk of the target wind farm. In this way, the device takes into account the characteristics of the current trend of large-scale wind turbines, comprehensively considers the changes in the number of lightning strikes under the three lightning discharge forms of downlink lightning, self-triggered uplink lightning, and externally triggered uplink lightning, and ensures a comprehensive and accurate assessment of the lightning risk of the target wind farm, which helps to serve the design and construction of lightning protection projects for large wind farms in a simple and efficient manner. This solves the problem that the assessment method of wind turbine lightning strike risk in related technologies ignores the changes in wind turbines, that is, small-sized wind turbines are gradually replaced by large-sized and large-power wind turbines. As the height of the wind turbine body increases, the number and probability of being struck by upward lightning also increase accordingly, making it difficult to meet the calculation requirements of lightning strike risks of large-sized wind turbines and large wind farms in actual scenarios.

[0152] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0153] A memory 801 , a processor 802 , and a computer program stored in the memory 801 and executable on the processor 802 .

[0154] When the processor 802 executes the program, the wind farm lightning strike risk assessment method taking into account both downward and upward lightning provided in the above embodiment is implemented.

[0155] Furthermore, the electronic device further includes:

[0156] The communication interface 803 is used for communication between the memory 801 and the processor 802 .

[0157] The memory 801 is used to store computer programs that can be run on the processor 802.

[0158] The memory 801 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0159] If the memory 801, the processor 802, and the communication interface 803 are implemented independently, the communication interface 803, the memory 801, and the processor 802 can be connected to each other via a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0160] Optionally, in a specific implementation, if the memory 801, the processor 802 and the communication interface 803 are integrated on a chip, the memory 801, the processor 802 and the communication interface 803 can communicate with each other through an internal interface.

[0161] The processor 802 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0162] An embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the wind farm lightning strike risk assessment method taking into account both downward and upward lightning is implemented.

[0163] An embodiment of the present application also provides a computer program product, including a computer program, which can run computer instructions. When the computer instructions are executed by a processor, the wind farm lightning strike risk assessment method that takes into account both downward and upward lightning provided in the embodiment of the present application is implemented.

[0164] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0165] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of technical features indicated. Thus, a feature specified as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of this application, "N" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0166] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing a custom logical function or process step, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed in a different order than shown or discussed, including performing functions in a substantially simultaneous manner or in a reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0167] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or N wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program can be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing it in other suitable ways as necessary, and then storing it in a computer memory.

[0168] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiment, the N steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented using hardware, as in another embodiment, it can be implemented using any one or a combination of the following technologies known in the art: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0169] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0170] In addition, the functional units in the various embodiments of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into a module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0171] The storage medium mentioned above may be a read-only memory, a magnetic disk, or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application. Persons skilled in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A method for assessing the lightning risk of a wind farm taking into account both downward and upward lightning, characterized in that: The following steps are involved: Acquire environmental data of the current location of the target wind farm, and acquire multiple parameter information of triggered downlink mines, self-triggered uplink mines, and externally triggered uplink mines in the target wind farm; Based on the environmental data, establishing a structure-activity relationship between the plurality of parameter information and the downlink mine, the self-triggered uplink mine, and the externally triggered uplink mine; Based on the structure-activity relationship, the number of downlink lightning, the number of self-triggered uplink lightning and the number of externally triggered uplink lightning of the target wind farm within the target time are calculated, so as to evaluate the lightning strike risk of the target wind farm according to the number of downlink lightning, the number of self-triggered uplink lightning and the number of externally triggered uplink lightning.

2. The method according to claim 1, characterized in that The establishing, based on the environmental monitoring data, structure-activity relationships between the plurality of parameter information and the downlink mine, the self-triggered uplink mine, and the externally triggered uplink mine comprises: Based on the environmental data, calculating the equivalent collection area of the wind turbines in the target wind farm for the downgoing lightning within the target time; Calculating the number of lightning strikes caused by the downgoing lightning in the target wind farm within the target time according to the equivalent collection area; Based on the number of lightning strikes, the number of channel grounding terminals in the target wind farm caused by a single down-stroke lightning strike, and the number of wind turbines in the target wind farm, a structure-effect relationship between the plurality of parameter information and the down-stroke lightning is determined.

3. The method according to claim 1, characterized in that The establishing, based on the environmental monitoring data, structure-activity relationships between the plurality of parameter information and the downlink mine, the self-triggered uplink mine, and the externally triggered uplink mine comprises: Based on the environmental monitoring data, constructing the electric potential function, thundercloud electric potential density distribution function and density probability distribution function of the self-triggered upward lightning to calculate the probability that the local thundercloud electric field of the self-triggered upward lightning exceeds the critical electric field threshold within the target time; calculating the number of times the local thundercloud electric field exceeds the critical electric field threshold based on the probability and the number of active thunderstorms in the self-triggered uplink thunder; Based on the number of times the local thundercloud electric field exceeds the critical electric field threshold and the average number of upward leaders of the self-triggered upward thunder, a structure-activity relationship between the plurality of parameter information and the self-triggered upward thunder is determined.

4. The method according to claim 3, characterized in that The density probability distribution function is: Among them, f E (E c ) is the density distribution probability function of cloud height, H max is the maximum height of thundercloud, H c is the cloud height, f H (H c ) is the cloud height density distribution function, f v (E c ·H c ) is the probability density distribution function of cloud potential.

5. The method according to claim 1, wherein The establishing, based on the environmental monitoring data, structure-activity relationships between the plurality of parameter information and the downlink mine, the self-triggered uplink mine, and the externally triggered uplink mine comprises: Based on the environmental monitoring data, constructing a Weibull distribution function of positive polarity ground-to-ground lightning events in the target wind farm to calculate the number of ground-to-ground lightning events generated by the wind turbines in the target wind farm within the target time; Calculate the number of externally triggered upward lightning strikes on a single wind turbine generator set within the target time based on the number of ground lightning strikes and the probability of the electric field generated by ground lightning strikes on the wind turbine generator sets in the target wind farm within the target time; Based on the number of externally triggered uplink mines of the single wind turbine generator set within the target time and the number of externally triggered uplink mines within a target range around the location of the single wind turbine generator set, a structure-effect relationship between the multiple parameter information and the externally triggered uplink mines is determined.

6. The method according to claim 5, characterized in that The calculation formula for the number of ground flashes is: Among them, n +CG is the annual number of electric field flashovers generated at the wind turbine location, k +CG / CG is the positive polarity ground flash coefficient, π is the circumference of the circle, r eq is the equivalent radius, N g is the density of ground-to-ground lightning.

7. A wind farm lightning strike risk assessment device that takes into account both downward and upward lightning, characterized in that: include: Acquire environmental data of the current location of the target wind farm, and acquire multiple parameter information of triggered downlink mines, self-triggered uplink mines, and externally triggered uplink mines in the target wind farm; Based on the environmental data, establishing a structure-activity relationship between the plurality of parameter information and the downlink mine, the self-triggered uplink mine, and the externally triggered uplink mine; Based on the structure-activity relationship, the number of downlink lightning, the number of self-triggered uplink lightning and the number of externally triggered uplink lightning of the target wind farm within the target time are calculated, so as to evaluate the lightning strike risk of the target wind farm according to the number of downlink lightning, the number of self-triggered uplink lightning and the number of externally triggered uplink lightning.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for assessing the lightning risk of a wind farm taking into account both downward and upward lightning as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the wind farm lightning strike risk assessment method taking into account both downward and upward lightning as described in any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed, it is used to implement the wind farm lightning strike risk assessment method taking into account both downward and upward lightning as described in any one of claims 1 to 6.

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