Lightning stroke risk assessment method, system and equipment for power transmission line of hydropower station and medium

Abstract

The invention relates to the technical field of hydropower station lightning protection, and relates to a hydropower station power transmission line lightning stroke risk assessment method comprising the following steps: based on power transmission line tower footing types and position information, combining a preset height threshold to divide lightning stroke types, and marking high-risk candidate tower footing according to protection range parameters of a lightning suppressor; operating parameters and overvoltage monitoring data of the lightning suppressor are collected in real time, environmental factors and tower footing insulation configuration differences are fused, and a tower footing correlation model is constructed; carrying out vulnerability evaluation on the high-risk candidate tower footing by adopting the tower footing type correction coefficient; constructing a lightning stroke risk assessment model for the tower footing exceeding the preset height threshold, optimizing risk assessment model parameters by using the overvoltage monitoring data, and generating a risk assessment result; and correcting protection range parameters according to lightning stroke event feedback, and iteratively updating the risk assessment model in combination with historical operation data of the lightning suppressor. Lightning stroke risk assessment of the whole hydropower station power transmission line is realized, and lightning stroke risk assessment efficiency and accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of lightning protection for hydropower stations, and in particular to a method, system, equipment and medium for assessing lightning strike risks for transmission lines in hydropower stations. Background Art

[0002] Hydropower stations are core infrastructure in the power system, and their transmission lines carry the critical function of transmitting electricity. Due to the unique geographical location of hydropower stations, which are often located in mountainous valleys, transmission lines are often exposed to areas of frequent lightning activity. This poses risks of lightning strikes causing insulation flashover, equipment damage, and line tripping, seriously threatening the safety and reliability of the power grid. In this context, accurate and efficient lightning risk assessment of transmission lines is a critical prerequisite for developing differentiated lightning protection strategies and ensuring the safe operation of hydropower stations.

[0003] Although current methods for assessing lightning strike risks on overhead transmission lines have introduced dynamic modeling and multi-source data fusion technologies, they have significant limitations in hydropower station application scenarios: on the one hand, existing methods do not effectively integrate parameters such as the spatial protection range and current attenuation characteristics of lightning protection facilities, resulting in the inability to quantify the actual effectiveness of protective devices for different types of tower bases; on the other hand, there is a lack of targeted modeling for the structural differences between different tower bases of hydropower station transmission lines and the differentiation of lightning strike paths caused by terrain, making it difficult for assessment results to adapt to complex environments such as mountainous areas and river valleys. Ultimately, this results in low risk assessment efficiency and insufficient accuracy, making it difficult to support the precise decision-making needs for differentiated protection of hydropower station transmission lines. Summary of the Invention

[0004] In order to implement lightning strike risk assessment for the entire transmission line of a hydropower station based on lightning suppressors, improve the efficiency and accuracy of lightning strike risk assessment for the entire line, and provide decision support for differentiated lightning protection measures, the present invention provides a method, system, equipment, and medium for lightning strike risk assessment for the transmission line of a hydropower station. The technical solutions adopted are as follows: The technical solution of the first aspect of the present invention provides a method for assessing lightning strike risk of hydropower station transmission lines, the method comprising: Based on the tower type and location information of the transmission line, the lightning strike type is classified in combination with the preset height threshold, and high-risk candidate tower bases are marked according to the protection range parameters of the lightning suppressor; Real-time collection of lightning suppressor operating parameters and overvoltage monitoring data, combined with environmental factors and tower base insulation configuration differences, to build a tower base correlation model; Based on the tower foundation association model, a tower foundation type correction coefficient is used to perform a vulnerability assessment on the high-risk candidate tower foundation; Based on the vulnerability assessment results, a lightning strike risk assessment model is constructed for tower foundations exceeding a preset height threshold. Real-time overvoltage monitoring data is used to optimize the risk assessment model parameters and generate risk assessment results. The protection range parameters are modified according to the feedback of lightning strike events during the operation of the lightning suppressor, and the risk assessment model is iteratively updated in combination with the historical operation data of the lightning suppressor.

[0005] Furthermore, based on the tower type and location information of the transmission line, the lightning strike type is divided according to the preset height threshold, and high-risk candidate tower bases are marked according to the protection range parameters of the lightning suppressor, including: Distinguish between straight towers and tension towers based on transmission line topology data, and obtain the coordinates of each tower base; The lightning stroke types are divided into overhead lightning stroke and side lightning stroke by pre-set height threshold; Calculate the spatial distance between each tower base and the lightning suppressor based on the protection range parameters of the lightning suppressor; Mark the tension towers within the protection range and with a height greater than a preset height threshold as candidates with high risk of side lightning strikes; Linear towers outside the protection range and with a height less than or equal to a preset height threshold are marked as candidates with high risk of over-the-top lightning strikes.

[0006] Furthermore, the operating parameters and overvoltage monitoring data of the lightning suppressor are collected in real time, and the environmental factors and tower base insulation configuration differences are integrated to build a tower base correlation model, including: Collect the interception success rate and current attenuation rate parameters of the lightning suppressor; Obtain lightning current waveform characteristics from overvoltage monitoring data; Integrate environmental humidity, salt density data and differences in the number of tower base insulator strings; A dynamic correlation matrix of lightning suppressor parameters, lightning current characteristics and environmental factors is established.

[0007] Furthermore, based on the tower foundation association model, a tower foundation type correction coefficient is used to perform a vulnerability assessment on the high-risk candidate tower foundation, including: Assigning a first correction coefficient to the straight tower and a second correction coefficient to the tension tower, wherein the second correction coefficient is greater than the first correction coefficient; Extract environmental factor weights and overvoltage impact values ​​from the dynamic correlation matrix; The first correction coefficient, the second correction coefficient and the environmental factor weight are weighted and superimposed to output the dynamic vulnerability index of the tower foundation.

[0008] Furthermore, based on the vulnerability assessment results, a lightning strike risk assessment model is constructed for tower foundations exceeding a preset height threshold, including: For high-risk tension towers with heights greater than a preset height threshold, a side lightning strike risk assessment sub-model is constructed; The combined impact factor of altitude and terrain ruggedness is embedded in the lateral lightning strike risk assessment sub-model; The tower foundation dynamic vulnerability index is associated with the tower foundation dynamic vulnerability index and the model parameters are initialized.

[0009] Furthermore, real-time overvoltage monitoring data is used to optimize risk assessment model parameters and generate risk assessment results, including: Set parameter optimization weights according to the operating status of the lightning suppressor; Use real-time overvoltage waveform data to correct lightning current waveform characteristics; The model parameters are iteratively optimized through the gradient descent algorithm to generate quantitative results of risk levels.

[0010] Furthermore, the protection range parameters are modified based on the feedback of lightning strike events during the operation of the lightning suppressor, and the risk assessment model is iteratively updated based on the historical operation data of the lightning suppressor, including: When the lightning suppressor records a lightning strike event, it locates the tower base coordinates of the event and reversely deduces the protection blind area; Narrow the radius estimation of protection range parameters according to the distribution of protection blind areas; The parameters of the long-term risk prediction model are modified based on the annual interception times of lightning suppressors.

[0011] The technical solution of the second aspect of the present invention provides a hydropower station transmission line lightning strike risk assessment system, which adopts the hydropower station transmission line lightning strike risk assessment method described in the technical solution of the first aspect of the present invention, and the system includes: The scenario classification module is configured to classify lightning strike types based on the tower type and location information of the transmission line and the preset height threshold, and mark high-risk candidate towers according to the protection range parameters of the lightning suppressor; The data fusion module is configured to collect the operating parameters and overvoltage monitoring data of the lightning suppressor in real time and integrate the environmental factors and tower base insulation configuration differences to build a tower base correlation model; a vulnerability assessment module configured to perform a vulnerability assessment on the high-risk candidate tower foundation based on the tower foundation association model and using a tower foundation type correction coefficient; a risk assessment module configured to construct a lightning strike risk assessment model for tower foundations exceeding a preset height threshold based on vulnerability assessment results, and to optimize risk assessment model parameters using real-time overvoltage monitoring data to generate risk assessment results; The closed-loop update module is configured to modify the protection range parameters based on the feedback of lightning events during the operation of the lightning suppressor, and iteratively update the risk assessment model in combination with the lightning suppressor operation data.

[0012] The technical solution of the third aspect of the present invention provides an electronic device, comprising: a processor and a memory communicatively connected to the processor; wherein the memory stores instructions executable by the processor, and the instructions are executed by the processor so that the processor can execute the steps of the method for assessing the lightning strike risk of a hydropower station transmission line described in the technical solution of the first aspect of the present invention.

[0013] The technical solution of the fourth aspect of the present invention provides a computer-readable storage medium, on which is stored a program for implementing a method for assessing the lightning strike risk of a hydropower station transmission line. The program for implementing a method for assessing the lightning strike risk of a hydropower station transmission line is executed by a processor to implement the steps of the method for assessing the lightning strike risk of a hydropower station transmission line described in the technical solution of the first aspect of the present invention.

[0014] The present invention has the following beneficial effects: The present invention provides a method for assessing the lightning strike risk of hydropower station transmission lines. The overall technical solution divides lightning strike scenarios and marks high-risk targets based on tower base type and height thresholds, thereby achieving differentiated risk identification, narrowing the assessment scope and clarifying assessment priorities, reducing invalid calculations and improving assessment efficiency. A correlation model is constructed by integrating lightning suppressor operating parameters, overvoltage monitoring data, environmental factors and tower base insulation differences, and a tower base type correction coefficient is introduced to achieve differentiated vulnerability assessment. Combined with the sub-model design for complex terrain, the tower base type correction coefficient and the terrain optimization sub-model solve adaptation problems such as the structural differences between straight towers and tension towers and the differentiation of over-top / side lightning strike paths in mountainous areas, eliminating the structural generalization bias in traditional assessments and improving the accuracy of assessments. Finally, model iteration based on lightning strike events and historical operating data gives the system the ability to continuously adapt to complex environments, ensuring the reliability of long-term risk assessments, and forming an optimization system of accurate identification-efficient assessment-directional protection-dynamic evolution, which provides a decision-making basis for targeted lightning protection measures and supports the differentiated lightning protection needs of the entire hydropower station transmission line. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 A flow chart of a method for assessing lightning strike risk of a hydropower station transmission line provided by one embodiment of the present invention; Figure 2 A schematic structural diagram of a hydropower station transmission line lightning strike risk assessment system provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0017] To further illustrate the technical means and effectiveness of the present invention in achieving its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail a method, system, device, and medium for assessing lightning strike risk for hydropower station transmission lines, including its specific implementation, structure, features, and effectiveness. In the following description, references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0018] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0019] The following describes in detail a method, system, equipment and medium for assessing lightning strike risk of a hydropower station transmission line provided by the present invention with reference to the accompanying drawings.

[0020] The present invention takes a single-base single-circuit line of a hydropower station as an example. The total length of the line is 15.847 km, including 38 iron towers, including 16 straight towers and 22 tension towers. The line is mainly located in mountainous valleys. The insulators use J70BP anti-fouling glass insulators, of which 7 straight towers are in a string and 9 tension towers are in a string.

[0021] See also Figure 1 , which shows a method flow chart of a method for assessing lightning strike risk of a hydropower station transmission line provided by one embodiment of the present invention, the method comprising: Step S100: Based on the tower type and location information of the transmission line, the lightning strike type is classified in combination with a preset height threshold, and high-risk candidate tower foundations are marked according to the protection range parameters of the lightning suppressor; Step S100 specifically includes: Step S110: Distinguish between straight towers and tension towers based on the transmission line topology data, and obtain the coordinate position of each tower base; by retrieving the transmission line topology data from the hydropower station transmission line engineering design phase, such as line direction, tower distribution, structural parameters, etc., combined with the tower ledger information in the line operation and maintenance management system, distinguish the types by the number of insulator strings and structural function: Straight tower: no corner function, the insulators are 7 pieces of J70BP anti-fouling glass insulators in a string. The towers with "no corner mark and insulator string number = 7" are selected from the topological data; Tension tower: bears corner or terminal tension, uses 9 pieces of the same type of insulators in a string, and selects towers with "corner mark / terminal mark and insulator string number = 9"; Then, GPS positioning technology or total station is used to conduct field measurements of the 38 towers to obtain the latitude and longitude coordinates and altitude data of each tower base. The coordinate information is entered into the geographic information system (GIS) to generate a tower base location distribution map and establish a digital archive.

[0022] Step S120: The lightning strike type is divided into overhead lightning strike and side lightning strike by a preset height threshold. The lightning suppressor has the function of automatically identifying the spatial location of lightning and reducing the lightning current. In this embodiment, the preset height threshold is set based on the height limit characteristics of the lightning suppressor and the terrain characteristics of the hydropower station transmission line passing through the mountain valley. Based on this threshold, lightning strike types are divided into overhead lightning strikes and side lightning strikes: Overhead lightning strike: height of the lightning strike point , mainly affects the low-altitude area of ​​the line, and the straight tower is more susceptible to the impact due to its lower height; Side lightning strike: lightning strike point height , which often occurs in high-altitude or high-tower areas. Tension towers are more susceptible to such lightning strikes due to their higher height.

[0023] Step S130: Calculate the spatial distance between each tower base and the lightning suppressor based on the protection range parameters of the lightning suppressor; specifically, establish a three-dimensional rectangular coordinate system with the lightning suppressor installation position as the origin, with the x-axis being the horizontal direction along the transmission line; the y-axis being the horizontal direction perpendicular to the line; and the z-axis being the vertical direction perpendicular to the ground; and then calculate the spatial distance between the tower base and the lightning suppressor. ; The protection range parameters of the lightning suppressor include: Downwind protection range: Based on suppressor parameters Downwind protection range: , ,judge Is it within the scope; Magnetic field strength verification: combined , is the radius of the magnetic field of 2.4Gs under 30kA lightning current, if , it means that the tower base is within the direct magnetic field protection range of the suppressor, further confirming the effectiveness of the protection.

[0024] Step S140: Mark the tension towers within the protection range and with a height greater than a preset height threshold as candidates for high risk of side lightning strikes. Specifically, for each tower base (straight tower / tension tower), the following judgment is performed based on its type, height, and distance from the suppressor: Candidates with high risk of side lightning strike: Meet the requirements of "tension tower, , and exceeds the height threshold", it is marked as "high risk of side lightning strike"; Candidates with high risk of overhead lightning strikes: Meet the "straight tower, , and does not exceed the height threshold", marked as "high risk of over-the-top lightning strike"; Finally, the tower base number, risk type and other marking results are stored in the assessment system database to generate a list of high-risk candidate tower bases. For example, 5 tension towers with high risk of side lightning strikes and 8 straight towers with high risk of overhead lightning strikes were selected from 38 towers. This embodiment achieves accurate identification of high-risk candidate tower foundations through a closed-loop process of type differentiation, coordinate positioning, lightning strike classification, distance calculation, and risk marking. On the one hand, based on the differences in tower foundation structure, spatial location, and height characteristics (that is, a "multi-dimensional coupling" risk screening standard is established, which addresses the one-sidedness of "judging only by distance or height factors" in traditional assessments. On the other hand, through GIS digitization and quantitative calculation, the objectivity and repeatability of high-risk object identification are ensured, providing a precise assessment object foundation for the subsequent construction of association models and vulnerability assessments, and improving the pertinence and efficiency of lightning risk assessments.

[0025] Step S200: Real-time acquisition of lightning suppressor operating parameters and overvoltage monitoring data is combined with environmental factors and tower base insulation configuration differences to construct a tower base correlation model. Specifically, the real-time operating parameters of the lightning suppressor are collected and combined with overvoltage signals monitored by the transient overvoltage recorder to construct a ternary relationship model of "environment-equipment-lightning suppressor." The transient overvoltage recorder's technical parameters are optimized to include three independent sampling channels, a maximum sampling rate of 40MS / s per channel, and isochronous triggering and synchronous recording across modules. The entire system consists of an overvoltage signal monitor, sensors, a host computer, and system software. The overvoltage signal monitor can be connected to a remote host computer via a network cable. Under the control of the system software, it forms a three-channel substation overvoltage online monitoring system, providing functions such as equipment control, data transmission, waveform display, data processing, and data storage. 14-bit high-precision A / D is preferred, and the maximum sampling rate of each channel can reach 40MSps at the same time. The sampling rate can be set in a programmable manner, so that transient overvoltage signals can be captured promptly and accurately, with a measurement accuracy of less than ±0.5%. The dedicated test and analysis software supporting the transient overvoltage online monitoring device can complete the monitoring, recording, analysis, and report output of various types of overvoltages.

[0026] Step S200 specifically includes: Step S210: Collect the interception success rate and current attenuation rate parameters of the lightning suppressor; for the lightning suppressor corresponding to the 38 tower bases, the built-in intelligent monitoring module records the operating data in real time. The core parameters include: interception success rate , used to reflect the suppressor's effective interception capability against lightning strikes; current attenuation rate , which is used to measure the suppressor's weakening effect on lightning current; the interception success rate can be calculated by counting the ratio of the number of lightning strikes actually intercepted by the lightning suppressor per unit time to the total number of lightning strikes monitored. For example, in a continuous 24-hour monitoring period, if 100 lightning strikes are monitored and 85 are successfully intercepted, the interception success rate is 85%; the current attenuation rate can be calculated by comparing the current peak value at the lightning strike point without a suppressor and the current peak value after the suppressor acts, that is, = (peak current before suppression - peak current after suppression) / peak current before suppression × 100%. To meet the suppressor design standard, this value must be no less than 75%. The collected parameters are sent to the data processing center in real time via the 4G wireless transmission module and the tower base number is used. and timestamp " format storage, such as 、 , forming a suppressor parameter time series database.

[0027] Step S220: Obtain the lightning current waveform characteristics in the overvoltage monitoring data; specifically, deploy transient overvoltage recorders at both ends of the insulator string of each tower base and at the connection point between the tower body and the conductor, perform waveform analysis on the collected overvoltage signal, and extract four core characteristic parameters to Moment Take the base tower data as an example: Wavefront time : The time it takes for the lightning current to rise from 0 to the peak value, in μs; Half peak time : The time it takes for the lightning current to drop from the peak value to 50% of the peak value, in μs; Peak current : The maximum current value in the waveform, in kA; Steepness : The average slope of the current rising phase, in kA / μs; Finally, the data is stored in a three-dimensional structure of "tower base number-time stamp-characteristic parameters" to form a lightning current waveform characteristic dataset, which provides input for subsequent correlation modeling. Step S230: Integrate the ambient humidity, salt density data and the difference in the number of tower base insulator strings; install a temperature and humidity sensor near each tower base, collect data once an hour, and record the relative humidity value; sample the insulator surface every quarter and measure the salt density data by weight in mg / cm²; distinguish the number of insulator strings based on the tower base type: the number of insulator strings for straight towers ; Number of insulator strings on tension tower The insulation configuration difference coefficient is defined to quantify the difference in insulation capacity between the two. To eliminate the influence of dimension, all parameters are normalized to the interval [0, 1] and then included in the data fusion pool after eliminating the dimension effect.

[0028] Step S240: Establish a dynamic correlation matrix of lightning suppressor parameters, lightning current characteristics and environmental factors; using the lightning suppressor parameters of step S210, the lightning current waveform characteristics of step S220, and the environment and insulation parameters of step S230 as input variables, construct a 38×9 dimensional state correlation matrix , where: row dimension configuration is: 38 base tower base, number Column dimension: 9 types of parameters, including 2 types of suppressor parameters, 4 types of waveform characteristics, 2 types of environmental parameters, and 1 type of insulation difference, recorded as ; Matrix elements express Moment Taki's parameter values; for any two parameters j and k in the matrix, calculate their Pearson correlation coefficient , such as the negative correlation between lightning current peak and current attenuation rate, the positive correlation between salt density and insulation configuration, etc., the correlation coefficient is embedded into the matrix as a weight to form a dynamic correlation model of "lightning suppressor parameters, lightning current characteristics, environment and insulation parameters", realizing the organic integration of multi-source data.

[0029] This embodiment uses multi-dimensional data collection and dynamic correlation modeling. On the one hand, it comprehensively covers the key factors affecting lightning strike risk, from suppressor performance such as interception success rate and current attenuation rate, lightning current characteristics, environmental impact to equipment differences, and solves the problem of single data dimension in traditional assessments. On the other hand, through standardization processing and Pearson correlation weighting, heterogeneous parameters are integrated into a dynamic correlation matrix, and the intrinsic connections between parameters are quantified, providing coupled and accurate data support for subsequent vulnerability assessments. At the same time, relying on real-time transmission and dynamic update mechanisms, it ensures that the data responds immediately to environmental changes, significantly improving the robustness and accuracy of the assessment model.

[0030] Step S300: Based on the tower foundation association model, a tower foundation type correction coefficient is used to perform a vulnerability assessment on the high-risk candidate tower foundation; Step S300 specifically includes: Step S310: Assign a first correction coefficient to the straight tower and a second correction coefficient to the tension tower, and the second correction coefficient is greater than the first correction coefficient; based on the structural differences in tower base types in step S110, the 7 insulators of the straight tower and the 9 insulators of the tension tower, and historical lightning strike data, the lateral lightning strike failure rate of the tension tower is 1.2 times that of the straight tower, and the definition of the first correction coefficient : Straight tower, characterized by low structural height, small number of insulator strings, and low risk of side lightning strikes, with a value of 1.0; the second correction factor : Tension tower, characterized by high structural height, high tension, and high risk of side lightning strike, with a value of 1.2; both meet , quantify the higher foundation vulnerability of the tension tower; for the high-risk candidate tower foundations marked in step S140, match the correction coefficient by type: assign 1.0 to the straight tower with high risk of over-the-top lightning strike; assign 1.2 to the tension tower with high risk of side lightning strike; Step S320: Extract environmental factor weights and overvoltage impact values ​​from the dynamic correlation matrix; Screening of 5 core environmental factors, including: environmental humidity , salt dense , lightning current peak , waveform steepness , Difference in the number of insulator strings ; Use the analytic hierarchy process to calculate the weight : Construct a judgment matrix: assign values ​​on a scale of 1-9 based on the degree of influence of each factor on vulnerability. For example, "peak lightning current is more important than humidity" is assigned a value of 3; final weight example: 、 、 、 、 ; Extract the actual impact value of each factor from the dynamic correlation matrix M and use it as the overvoltage impact value after normalization; Step S330: The first correction coefficient, the second correction coefficient and the environmental factor weight are weighted and superimposed to output the dynamic vulnerability index of the tower foundation; The vulnerability index calculation formula for high-risk candidate tower foundation is:

[0031] Where, Indicates the The dynamic vulnerability index of the base tower ranges from 0 to 1, with larger values ​​indicating higher vulnerability. Indicates the Kitadi Standardized impact value of the class factor; Indicates the The type correction coefficient of the tower base is 1.0 for straight towers and 1.2 for tension towers. The vulnerability indexes of all high-risk candidate tower bases are calculated and sorted from high to low. The vulnerability indexes can be graded to generate a dynamic vulnerability list of tower bases.

[0032] This embodiment achieves a precise assessment of the vulnerability of high-risk tower foundations through a quantitative method that combines a type correction coefficient with a multi-factor weighting. Based on the tower foundation type classification of S100 and the dynamic association matrix of S200, it organically integrates structural differences with the environmental and lightning coupling effects, addressing the one-sidedness of traditional assessments that prioritize the environment over the structure, or the structure over the environment. Furthermore, the objectivity and comparability of vulnerability indicators are ensured by determining weights and standardizing them through the hierarchical analysis method. The quantitative results not only reflect the individual risks of a single tower foundation, but also provide a grading basis for the subsequent S400 risk assessment model, significantly improving the refinement of lightning risk assessment.

[0033] Step S300 introduces a tower foundation type correction factor, combining environmental factor weights with a weighted calculation of overvoltage impact values, to quantitatively assess the vulnerability of high-risk candidate tower foundations. The differentiated setting of the correction factor accurately reflects the impact of structural differences between straight towers and tension towers on vulnerability. The integration of environmental factors and overvoltage data reflects the synergistic effect of the external environment and equipment status. The resulting dynamic vulnerability index not only quantifies the risk level of a single tower foundation but also provides a grading basis for subsequent targeted risk assessments. This effectively addresses the vulnerability assessment bias caused by traditional assessments that rely solely on a single factor or ignore differences in tower foundation types.

[0034] Step S400: Based on the vulnerability assessment results, a lightning strike risk assessment model is constructed for tower foundations exceeding a preset height threshold, and the risk assessment model parameters are optimized using real-time overvoltage monitoring data to generate a risk assessment result. Step S400 specifically includes: Step S410: For high-risk tension towers with a height greater than a preset height threshold, a side lightning strike risk assessment sub-model is constructed; specifically, from the vulnerability assessment results of step S300, tower bases that simultaneously meet the following conditions are selected: the height is greater than the preset height threshold; the vulnerability index In this embodiment, out of the 38 towers in the hydropower station, there are 8 high-risk tension towers that meet the conditions, and the numbers are defined as Then, a sub-model with the side lightning strike risk probability as the output is constructed. The core input variables include: lightning current intensity ;Tower base tolerance , that is, based on the number of insulator strings: 9 pieces for tension towers; the frequency of side lightning strikes ; Basic correlation curve fitting: Using the lateral lightning strike records in the area over the past five years, a binary linear regression was used to fit the lightning current intensity-damage probability curve:

[0035] in: Indicates the The probability of damage to the side of the base tension tower by lightning strike is 0~1; 、 、 is the regression coefficient, which can be calculated by the least squares method ; Indicates the Number of insulator strings on the tower; Step S420: Embed the joint impact factor of altitude and terrain ruggedness in the side lightning strike risk assessment sub-model; wherein, the altitude data is determined by the tower base elevation obtained in step S110, and the terrain ruggedness is obtained by calculating the standard deviation of the terrain slope within a 1km range around the tower base. The larger the standard deviation, the more rugged the terrain. The joint impact factor is calculated as a weighted product of the two, where the altitude weight is set to 0.6 and the terrain ruggedness weight is set to 0.4. This quantifies the enhanced effect of high altitude and complex terrain on the probability of side lightning strikes. The higher the altitude and the more rugged the terrain, the larger the joint impact factor and the higher the risk of side lightning strikes. Step S430: Associate the dynamic vulnerability index of the tower base and initialize the model parameters; use the dynamic vulnerability index of the tower base output in step S300 as an input parameter, associate it with the side lightning strike risk assessment sub-model, and complete the model parameter initialization. Specifically, after the vulnerability index value is standardized in the range of 0-1, it is assigned to the initial risk reference value in the sub-model, where the higher the vulnerability index, the larger the initial risk reference value. For example, if the dynamic vulnerability index of a high-risk tension tower is 0.8, then the "initial risk coefficient" parameter in the sub-model is initialized to 0.8 as the basic reference value for subsequent risk calculations; Step S440: Setting parameter optimization weights according to the operating state of the lightning suppressor; dynamically adjusting the state coefficient according to the operating parameters of the lightning suppressor collected in step S210 : Normal operation status: interception success rate And there is no fault alarm, ; Interception success status: current attenuation rate , ; For the first Model parameters at time , the update formula is:

[0036] Where, Indicates the learning rate, the value is 0.1; express Moment loss function The gradient, The deviation between the predicted risk and the actual failure; for Real-time monitoring data at all times; The formula for updating the environmental factor weight is:

[0037] Where, 、 express and Moment The difference in risk value between factor classes; Indicates the adjustment coefficient, with a value of 0.05; It represents the altitude correction coefficient, which increases by 0.1 for every 100m increase in altitude, so as to achieve dynamic optimization of environmental factor weights with altitude changes and risk trends; Step S450: Use real-time overvoltage waveform data to correct lightning current waveform characteristics; call the real-time overvoltage waveform data collected by the transient overvoltage recorder in step S200 to extract the spectrum characteristics of the lightning current; compare these characteristics with the historical lightning current spectrum database, calculate the spectrum deviation value, and if the deviation value exceeds 5%, modify the lightning current spectrum parameters in the model to ensure the model's adaptability to the current lightning current characteristics; Step S460: Iteratively optimize model parameters using a gradient descent algorithm to generate a quantitative risk level result. The loss function is the mean square error between the risk value predicted by the sub-model and the actual degree of lightning damage, such as insulator flashover. With each iteration, model parameters such as lightning current weight and environmental factor weight are adjusted based on the gradient direction of the loss function. The number of iterations is set to 100 to ensure convergence. The final output risk level is divided into five levels, with level 5 corresponding to the highest risk. The tower base's lightning protection priority is directly determined based on the quantitative results.

[0038] Step S400 achieves an accurate assessment of the lightning strike risk of super-threshold high-risk tension towers. Based on the tower base height and type screening of S100, the real-time overvoltage data of S200 and the vulnerability index of S300, the constructed side lightning strike sub-model accurately captures the lightning strike characteristics under high altitude and complex terrain, and solves the limitations of traditional models; on the other hand, through the dynamic adjustment of parameter weights according to the state of the lightning suppressor and the iterative optimization of the gradient descent algorithm, the model parameters are ensured to adapt to the environment and equipment status in real time. The final output of the five-level risk level not only quantifies the risk differences of individual tower bases, but also provides a direct basis for the priority division of lightning protection measures, thereby improving the dynamic nature and decision-making support capabilities of the lightning strike risk assessment of hydropower station transmission lines.

[0039] Step S500: Modifying protection range parameters based on lightning event feedback during the operation of the lightning suppressor, and iteratively updating the risk assessment model in combination with historical operation data of the lightning suppressor; Step S500 specifically includes: Step S510: When the lightning suppressor records a lightning strike event, locate the tower base coordinates and reversely deduce the protection blind area; when the intelligent monitoring module of the lightning suppressor records a lightning strike event, the trigger signal timestamp is The corresponding tower base can be located by the following steps: synchronously call the monitoring data of the transient overvoltage recorder in step S220, filter Overvoltage signal with a time difference of ≤1ns; extract the tower base number corresponding to the signal, and through the unique binding relationship between the recorder and the tower base, retrieve its three-dimensional coordinates from the GIS database in step S110 and convert them into rectangular coordinates; then, based on the protection range parameters of the lightning suppressor, that is, the downwind protection range A=πr² / 2, r=2km~4km, calculate the spatial distance between the tower base and the lightning suppressor. If the tower base is within the protection range but lightning still occurs, the area is determined to be a protection blind area; finally, by drawing a positional relationship diagram between the protection range boundary and the actual lightning-struck tower base, reversely deduce the geographical distribution of the blind area, such as the signal attenuation area caused by terrain obstruction or the deviation area between the theoretical value of the suppressor parameter and the actual environment; Step S520: Reduce the radius estimate of the protection range parameter according to the distribution of the protection blind area; correct the radius estimate of the protection range of the lightning suppressor according to the distribution characteristics of the protection blind area determined in step S510. First, calculate the average distance between all tower bases and suppressors in the protection blind area, and use this average distance as the upper limit of the actual effective protection radius to replace the original theoretical radius (2km~4km). For example, if the average distance between the tower base and the suppressor in the protection blind area is 3.5km, the protection range parameter is reduced from the original 4km to 3.5km to ensure that the revised protection range parameter is more in line with the actual protection effectiveness. At the same time, the revised radius parameter is updated to the tower base association model and the risk assessment model, and the protected area and high-risk area are re-divided; Step S530: Modify the long-term risk prediction model parameters based on the annual interception times of the lightning suppressor; specifically, the annual interception times statistics and benchmark value setting: annual interception times , count the number of lightning strikes successfully intercepted by the lightning suppressor in step S210 within one year; the historical average interception number , based on the past 5 years Calculate the arithmetic mean; combine the risk levels of historical lightning events and correct the parameters of the long-term risk prediction model. For example, if the number of interceptions in a certain year is higher than the historical average, the prediction weight of the future lightning strike risk in the area is reduced; if the number of interceptions is lower than the historical average, the prediction weight is increased; this embodiment realizes the dynamic calibration and continuous evolution of the risk assessment model through the mechanism of event feedback, range correction, and long-term optimization. First, based on the lightning strike event, the protection blind area is located and the protection radius is corrected, such as from 4km to 3.5km, which solves the actual deviation between the theoretical protection range and the mountainous terrain, making the division of high-risk areas more accurate; on the other hand, the long-term prediction parameters are adjusted through annual interception data, so that the model can adapt to the changes in the effectiveness of the lightning suppressor. Combined with the real-time evaluation logic of steps S100-S400, a system of short-term accurate identification combined with long-term trend prediction is formed, which can ultimately improve the timeliness and long-term effectiveness of the lightning risk assessment of the hydropower station transmission line, and provide a basis for the dynamic optimization of the lightning protection strategy.

[0040] In summary, the method for assessing the lightning strike risk of hydropower station transmission lines provided by the present invention has an overall technical solution that divides lightning strike scenarios and marks high-risk targets based on tower base type and height threshold, thereby achieving differentiated risk identification, narrowing the assessment scope and clarifying the assessment focus, reducing invalid calculations and improving assessment efficiency; by integrating lightning suppressor operating parameters, overvoltage monitoring data, environmental factors and tower base insulation differences to construct a correlation model, and introducing a tower base type correction coefficient to achieve differentiated vulnerability assessment, combined with sub-model design for complex terrain, the tower base type correction coefficient and the terrain optimization sub-model solve adaptation problems such as the structural differences between straight towers / tension towers and the differentiation of over-top / side lightning strike paths in mountainous areas, eliminating the structural generalization bias in traditional assessments and improving the accuracy of assessments; finally, model iteration based on lightning strike events and historical operation data gives the system the ability to continuously adapt to complex environments, ensuring the reliability of long-term risk assessment, and forming an optimization system of accurate identification-efficient assessment-directional protection-dynamic evolution, which provides a decision-making basis for targeted lightning protection measures and supports the differentiated lightning protection needs of the entire hydropower station transmission line.

[0041] See also Figure 2 , which shows a schematic structural diagram of a hydropower station transmission line lightning strike risk assessment system provided by one embodiment of the present invention, the system comprising: The scenario classification module is configured to classify lightning strike types based on the tower type and location information of the transmission line and the preset height threshold, and mark high-risk candidate towers according to the protection range parameters of the lightning suppressor; The data fusion module is configured to collect the operating parameters and overvoltage monitoring data of the lightning suppressor in real time and integrate the environmental factors and tower base insulation configuration differences to build a tower base correlation model; a vulnerability assessment module configured to perform a vulnerability assessment on the high-risk candidate tower foundation based on the tower foundation association model and using a tower foundation type correction coefficient; a risk assessment module configured to construct a lightning strike risk assessment model for tower foundations exceeding a preset height threshold based on vulnerability assessment results, and to optimize risk assessment model parameters using real-time overvoltage monitoring data to generate risk assessment results; The closed-loop update module is configured to modify the protection range parameters based on the feedback of lightning events during the operation of the lightning suppressor, and iteratively update the risk assessment model in combination with the lightning suppressor operation data.

[0042] The technical solution of the third aspect of the present invention provides an electronic device, comprising: a processor and a memory communicatively connected to the processor; wherein the memory stores instructions executable by the processor, and the instructions are executed by the processor so that the processor can execute the steps of the method for assessing the lightning strike risk of a hydropower station transmission line described in the technical solution of the first aspect of the present invention.

[0043] The technical solution of the fourth aspect of the present invention provides a computer-readable storage medium, on which is stored a program for implementing a method for assessing the lightning strike risk of a hydropower station transmission line. The program for implementing a method for assessing the lightning strike risk of a hydropower station transmission line is executed by a processor to implement the steps of the method for assessing the lightning strike risk of a hydropower station transmission line described in the technical solution of the first aspect of the present invention.

[0044] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0045] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A method for assessing the risk of lightning strikes on hydropower station transmission lines, characterized in that: The method comprises: Based on the tower type and location information of the transmission line, the lightning strike type is classified in combination with the preset height threshold, and high-risk candidate tower bases are marked according to the protection range parameters of the lightning suppressor; Real-time collection of lightning suppressor operating parameters and overvoltage monitoring data, combined with environmental factors and tower base insulation configuration differences, to build a tower base correlation model; Based on the tower foundation association model, a tower foundation type correction coefficient is used to perform a vulnerability assessment on the high-risk candidate tower foundation; Based on the vulnerability assessment results, a lightning strike risk assessment model is constructed for tower foundations exceeding a preset height threshold. Real-time overvoltage monitoring data is used to optimize the risk assessment model parameters and generate risk assessment results. The protection range parameters are modified according to the feedback of lightning strike events during the operation of the lightning suppressor, and the risk assessment model is iteratively updated in combination with the historical operation data of the lightning suppressor.

2. The method for assessing the risk of lightning strikes on hydropower station transmission lines according to claim 1, wherein: Based on the tower type and location information of the transmission line, the lightning strike type is classified in combination with the preset height threshold. High-risk candidate towers are marked according to the protection range parameters of the lightning suppressor, including: Distinguish between straight towers and tension towers based on transmission line topology data, and obtain the coordinates of each tower base; The lightning stroke types are divided into overhead lightning stroke and side lightning stroke by pre-set height threshold; Calculate the spatial distance between each tower base and the lightning suppressor based on the protection range parameters of the lightning suppressor; Mark the tension towers within the protection range and with a height greater than a preset height threshold as candidates with high risk of side lightning strikes; Linear towers outside the protection range and with a height less than or equal to a preset height threshold are marked as candidates with high risk of over-the-top lightning strikes.

3. The method for assessing the risk of lightning strikes on power transmission lines of a hydropower station according to claim 2, wherein: Real-time collection of lightning suppressor operating parameters and overvoltage monitoring data, combined with environmental factors and tower base insulation configuration differences, builds a tower base correlation model, including: Collect the interception success rate and current attenuation rate parameters of the lightning suppressor; Obtain lightning current waveform characteristics from overvoltage monitoring data; Integrate environmental humidity, salt density data and differences in the number of tower base insulator strings; A dynamic correlation matrix of lightning suppressor parameters, lightning current characteristics and environmental factors is established.

4. The method for assessing the risk of lightning strikes on power transmission lines of a hydropower station according to claim 3, wherein: Based on the tower foundation association model, a tower foundation type correction coefficient is used to perform a vulnerability assessment on the high-risk candidate tower foundation, including: Assigning a first correction coefficient to the straight tower and a second correction coefficient to the tension tower, wherein the second correction coefficient is greater than the first correction coefficient; Extract environmental factor weights and overvoltage impact values ​​from the dynamic correlation matrix; The first correction coefficient, the second correction coefficient and the environmental factor weight are weighted and superimposed to output the dynamic vulnerability index of the tower foundation.

5. The method for assessing the risk of lightning strikes on power transmission lines of a hydropower station according to claim 4, wherein: Based on the vulnerability assessment results, a lightning strike risk assessment model is constructed for tower foundations exceeding a preset height threshold, including: For high-risk tension towers with heights greater than a preset height threshold, a side lightning strike risk assessment sub-model is constructed; The combined impact factor of altitude and terrain ruggedness is embedded in the lateral lightning strike risk assessment sub-model; The tower foundation dynamic vulnerability index is associated with the tower foundation dynamic vulnerability index and the model parameters are initialized.

6. The method for assessing the risk of lightning strikes on power transmission lines of a hydropower station according to claim 5, wherein: Real-time overvoltage monitoring data is used to optimize risk assessment model parameters and generate risk assessment results, including: Set parameter optimization weights according to the operating status of the lightning suppressor; Use real-time overvoltage waveform data to correct lightning current waveform characteristics; The model parameters are iteratively optimized through the gradient descent algorithm to generate quantitative results of risk levels.

7. The method for assessing the risk of lightning strikes on power transmission lines of a hydropower station according to any one of claims 1 to 6, wherein: The protection range parameters are modified based on the feedback of lightning strike events during the operation of the lightning suppressor, and the risk assessment model is iteratively updated based on the historical operation data of the lightning suppressor, including: When the lightning suppressor records a lightning strike event, it locates the tower base coordinates of the event and reversely deduces the protection blind area; Narrow the radius estimation of protection range parameters according to the distribution of protection blind areas; The parameters of the long-term risk prediction model are modified based on the annual interception times of lightning suppressors.

8. The hydropower station transmission line lightning risk assessment system is characterized by: The method for assessing the risk of lightning strikes on hydropower station transmission lines according to any one of claims 1 to 7 is adopted, wherein the system comprises: The scenario classification module is configured to classify lightning strike types based on the tower type and location information of the transmission line and the preset height threshold, and mark high-risk candidate towers according to the protection range parameters of the lightning suppressor; The data fusion module is configured to collect the operating parameters and overvoltage monitoring data of the lightning suppressor in real time and integrate the environmental factors and tower base insulation configuration differences to build a tower base correlation model; a vulnerability assessment module configured to perform a vulnerability assessment on the high-risk candidate tower foundation based on the tower foundation association model and using a tower foundation type correction coefficient; a risk assessment module configured to construct a lightning strike risk assessment model for tower foundations exceeding a preset height threshold based on vulnerability assessment results, and to optimize risk assessment model parameters using real-time overvoltage monitoring data to generate risk assessment results; The closed-loop update module is configured to modify the protection range parameters based on the feedback of lightning events during the operation of the lightning suppressor, and iteratively update the risk assessment model in combination with the lightning suppressor operation data.

9. An electronic device, characterized in that: The electronic device includes: a processor and a memory communicatively connected to the processor; wherein the memory stores instructions executable by the processor, and the instructions are executed by the processor so that the processor can execute the steps of the method for assessing the lightning strike risk of a hydropower station transmission line as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a program for implementing a method for assessing the risk of lightning strikes on hydropower station transmission lines. The program for implementing a method for assessing the risk of lightning strikes on hydropower station transmission lines is executed by a processor to implement the steps of the method for assessing the risk of lightning strikes on hydropower station transmission lines according to any one of claims 1 to 7.

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