A power transmission line failure risk assessment method and system for strong convective gales

Abstract

A method and system for assessing the failure risk of transmission lines in the face of severe convective winds includes: establishing a theoretical model of the wind field for severe convective winds based on measured data and wind field variation patterns; selecting an actual engineering project to establish a transmission line model; performing simulation analysis on the established theoretical model and transmission line model under different wind speed conditions to obtain the structural response of the transmission line model; applying horizontal thrust to the transmission line model to conduct nonlinear pushover analysis to obtain the structural capability of the transmission line model; fitting a vulnerability curve based on the structural response and structural capability; and conducting a risk assessment based on the vulnerability curve. This invention, by establishing a wind field model and a transmission line model, conducting disaster simulation, risk assessment, and fault prevention measures, provides key technical support for wind-resistant design, reveals the disaster mechanism and probabilistic risk of transmission lines induced by severe convective winds, and proposes preventive measures to address transmission line faults induced by severe convective winds.

Description

Technical Field

[0001] This invention relates to the field of transmission line safety performance assessment, specifically to a method and system for assessing transmission line failure risks in the face of strong convective winds. Background Technology

[0002] Transmission lines are a crucial component of modern power infrastructure. They are coupled systems of multiple transmission towers connected by power lines, capable of transmitting electricity over long distances from power plants to users, playing a vital role in the reliability and stability of the entire power grid. With the rapid growth in energy demand, transmission lines are developing towards larger capacity, longer distances, and higher efficiency, inevitably traversing various complex environments. Even though current transmission line structural designs generally consider the impact of wind loads, transmission line accidents such as line breaks, wind-induced flashovers, and even tower collapses are common throughout their service life. These accidents not only seriously threaten the safe and stable operation of the power grid but also have a significant negative impact on post-disaster relief and repair efforts. Therefore, proposing a reliable integrated disaster-risk-prevention design method for transmission lines is essential to ensuring their safety and functionality.

[0003] Severe convective winds are localized and extremely destructive, and are one of the main factors causing transmission line breaks, wind-induced flashovers, and even tower collapses. In recent years, the frequent occurrence of severe convective winds due to climate change has posed a significant threat to the safe and stable operation of transmission lines. Therefore, considering the localized and extreme nature of severe convective winds, conducting risk assessments of transmission lines under severe convective wind disasters plays a crucial supporting role in the design, assessment, and prevention of transmission lines in response to extreme wind disasters.

[0004] Extensive research has been conducted both domestically and internationally on the assessment of the wind resistance performance of transmission lines, providing guidance for wind-resistant design. However, many problems remain: 1) Existing wind resistance studies often use the 10-minute average wind speed of benign winds at a height of 10 meters for design, but wind profiles cannot accurately describe the wind field patterns of strong convective winds (such as tornadoes and downbursts); 2) Current wind resistance studies often use elastic static analysis methods, which cannot reasonably capture accidents such as nonlinear tower collapse and transient wind deflection of transmission lines; 3) There is a lack of preventive measures to deal with transmission line faults induced by strong convective winds, resulting in transmission lines being unable to effectively resist the threat of extreme disasters. Summary of the Invention

[0005] To address the problems in existing technologies, such as the inability of wind profiles to accurately describe the wind field patterns of strong convective winds, the inability to reasonably capture accidents such as nonlinear tower collapses and transient wind deflections of transmission lines, and the lack of preventive measures to deal with transmission line faults induced by strong convective winds, which result in transmission lines being unable to effectively resist the threat of extreme disasters, this invention provides a method and system for assessing the failure risk of transmission lines in the face of strong convective winds.

[0006] This invention provides a method for assessing the failure risk of transmission lines in the face of severe convective winds, comprising:

[0007] A theoretical model of strong convective wind field was established based on measured data and wind field variation patterns, and a transmission line model was established by selecting actual engineering projects.

[0008] Based on the established theoretical model of strong convective wind field and the transmission line model, the structural response of the transmission line model was obtained through simulation analysis under different wind speed conditions.

[0009] A horizontal thrust is applied to the transmission line model to conduct nonlinear pushover analysis and obtain the structural capability of the transmission line model. The vulnerability curve is then fitted based on the structural response and structural capability.

[0010] Risk assessment is conducted based on the fragility curve.

[0011] Preferably, the strong convective wind field theoretical model is established by taking the data corresponding to the wind field parameters as input and the wind load time history as output; the strong convective wind field theoretical model includes at least one or more of the following: downburst model or tornado model.

[0012] Preferably, the wind field parameters of the downburst model include at least one or more of the following: maximum wind speed in the vertical wind profile, maximum wind speed in the radial wind profile, and moving speed and distance; and the wind field parameters of the tornado model include at least one or more of the following: reference height, vortex core radius, vortex ratio, or maximum wind speed.

[0013] Preferably, the transmission line model is established by taking the wind load time history as input and the response of the transmission line in the wind field where the transmission line model is located as output.

[0014] Preferably, the structural response of the transmission line model obtained by simulation analysis based on the established strong convective wind field theoretical model and the transmission line model under different wind speed conditions includes:

[0015] The data corresponding to the key wind field parameters are input into the strong convective wind field theoretical model to obtain the wind load time history. The wind load time history is then input into the transmission line model to obtain the transmission line response in the wind field where the transmission line model is located.

[0016] Nonlinear tower collapse simulations were conducted based on the response of the transmission line model in the wind field to identify vulnerable components of the transmission line model and clarify the impact of vulnerable components on the stress in adjacent areas.

[0017] Based on the response of the transmission line in the wind field where the transmission line model is located and the influence of vulnerable components on the stress of adjacent areas, the wind speed is gradually increased to simulate the entire process of the transmission line from elastic deformation to failure. A disaster simulation is carried out to establish a wind resistance verification model for typical wind deflection faults and tower collapse accidents of transmission lines under strong convective winds.

[0018] The data corresponding to the key wind field parameters are input into the wind resistance verification model of the strong convective wind field theoretical model under the typical wind deflection fault and tower collapse accident to obtain the structural response of the transmission line model.

[0019] The key wind field parameters are obtained by conducting sensitivity analysis of transmission lines under strong convective winds to identify key parameters.

[0020] Preferably, the step of applying a horizontal thrust to the transmission line model to conduct nonlinear pushover analysis to obtain the structural capability of the transmission line model, and fitting a vulnerability curve based on the structural response and structural capability, includes:

[0021] The structural capability of the transmission line model is obtained by applying a horizontal thrust to the model and conducting nonlinear pushover analysis.

[0022] By comparing the structural response of the transmission line with the structural capability of the transmission line model, the probability that the structural response of the transmission line exceeds the structural capability of the transmission line model is determined, and multiple discrete failure probability points are obtained.

[0023] The vulnerability curve is obtained by fitting a log-normal distribution to multiple discrete failure probability points.

[0024] Preferably, the risk assessment based on the fragility curve includes:

[0025] Based on the vulnerability curve, the risk of transmission line failure under strong convective winds is assessed for typical wind deflection faults and tower collapse accidents.

[0026] Preferably, after performing the risk assessment based on the fragility curve, the method further includes:

[0027] Based on the risk assessment results of typical transmission line wind deflection faults and tower collapse accidents in response to strong convective winds, echo radar is used to monitor wind field parameter changes in real time, and machine learning intelligent algorithms are used to fit historical data to predict future meteorological parameters.

[0028] Based on the monitoring of wind field parameter changes by echo radar and the use of future meteorological parameters by intelligent algorithms, early warnings can be given for typical tower collapse faults and typical wind deflection faults.

[0029] Based on the type of risk identified in early warnings, corresponding technical measures are implemented.

[0030] The risk types mentioned in the early warning include at least one or more of the following: typical tower collapse accidents or typical wind deflection accidents.

[0031] Preferably, the risk level of the typical wind deflection fault is divided into multiple target risk levels for tower collapse based on the tower top displacement or displacement angle. The risk levels include minor damage, moderate damage, and collapse.

[0032] Preferably, the risk level of the typical tower collapse fault is determined based on the minimum electrical clearance.

[0033] Based on the same inventive concept, this invention also provides a transmission line failure risk assessment system for strong convective winds, including: a model building module, a simulation analysis module, a vulnerability curve fitting module, and a risk assessment module.

[0034] Model building module: Based on measured data and wind field variation patterns, a theoretical model of strong convective wind field is established, and a transmission line model is established by selecting actual engineering projects;

[0035] Simulation analysis module: Based on the established theoretical model of strong convective wind field and transmission line model, simulation analysis is performed under different wind speed conditions to obtain the structural response of the transmission line model;

[0036] The vulnerability curve fitting module applies a horizontal thrust to the transmission line model to conduct nonlinear pushover analysis and obtain the structural capability of the transmission line model. Based on the structural response and structural capability, a vulnerability curve is fitted.

[0037] Risk assessment module: Conducts risk assessment based on fragility curve.

[0038] Preferably, the strong convective wind field theoretical model in the model building module is built by taking the data corresponding to the wind field parameters as input and the wind load time history as output; the strong convective wind field theoretical model includes at least one or more of the following: downburst model or tornado model.

[0039] Preferably, the wind field parameters of the downburst model in the model building module include at least one or more of the following: maximum wind speed in the vertical wind profile, maximum wind speed in the radial wind profile, and moving speed and distance; and the wind field parameters of the tornado model include at least one or more of the following: reference height, vortex core radius, vortex ratio, or maximum wind speed.

[0040] Preferably, the transmission line model in the model building module is built by taking the wind load time history as input and the response of the transmission line in the wind field where the transmission line model is located as output.

[0041] Preferably, the simulation analysis module is specifically used for:

[0042] The data corresponding to the key wind field parameters are input into the strong convective wind field theoretical model to obtain the wind load time history. The wind load time history is then input into the transmission line model to obtain the transmission line response in the wind field where the transmission line model is located.

[0043] Nonlinear tower collapse simulations were conducted based on the response of the transmission line model in the wind field to identify vulnerable components of the transmission line model and clarify the impact of vulnerable components on the stress in adjacent areas.

[0044] Based on the response of the transmission line in the wind field where the transmission line model is located and the influence of vulnerable components on the stress of adjacent areas, the wind speed is gradually increased to simulate the entire process of the transmission line from elastic deformation to failure. A disaster simulation is carried out to establish a wind resistance verification model for typical wind deflection faults and tower collapse accidents of transmission lines under strong convective winds.

[0045] The data corresponding to the key wind field parameters are input into the wind resistance verification model of the strong convective wind field theoretical model under the typical wind deflection fault and tower collapse accident to obtain the structural response of the transmission line model.

[0046] The key wind field parameters are obtained by conducting sensitivity analysis of transmission lines under strong convective winds to identify key parameters.

[0047] Preferably, the module for fitting the fragility curve is specifically used for:

[0048] The structural capability of the transmission line model is obtained by applying a horizontal thrust to the model and conducting nonlinear pushover analysis.

[0049] By comparing the structural response of the transmission line with the structural capability of the transmission line model, the probability that the structural response of the transmission line exceeds the structural capability of the transmission line model is determined, and multiple discrete failure probability points are obtained.

[0050] The vulnerability curve is obtained by fitting a log-normal distribution to multiple discrete failure probability points.

[0051] Preferably, the risk assessment module is specifically used for:

[0052] Based on the vulnerability curve, the risk of transmission line failure under strong convective winds is assessed for typical wind deflection faults and tower collapse accidents.

[0053] Preferably, after the risk assessment module, a handling module is further included, the handling module being used for:

[0054] Based on the risk assessment results of typical transmission line wind deflection faults and tower collapse accidents in response to strong convective winds, echo radar is used to monitor wind field parameter changes in real time, and machine learning intelligent algorithms are used to fit historical data to predict future meteorological parameters.

[0055] Based on the monitoring of wind field parameter changes by echo radar and the use of future meteorological parameters by intelligent algorithms, early warnings can be given for typical tower collapse faults and typical wind deflection faults.

[0056] Based on the type of risk identified in early warnings, corresponding technical measures are implemented.

[0057] The risk types mentioned in the early warning include at least one or more of the following: typical tower collapse accidents or typical wind deflection accidents.

[0058] Preferably, in the risk assessment module, the risk level of typical wind deflection faults is divided into multi-objective risk levels of tower collapse based on tower top displacement or displacement angle. The risk levels include minor damage, moderate damage, and collapse.

[0059] Preferably, the risk level of typical tower collapse faults in the risk assessment module is based on the minimum electrical clearance.

[0060] Based on the same inventive concept, the present invention also provides a computer device, comprising: at least one processor and a memory; the memory and the processor are connected via a bus;

[0061] The memory is used to store one or more programs;

[0062] When the one or more programs are executed by the at least one processor, the above-described method for assessing the failure risk of transmission lines in the face of strong convective winds is implemented.

[0063] Based on the same inventive concept, the present invention also provides a computer-readable storage medium having an executable program stored thereon, which, when executed, implements the above-described method for assessing the failure risk of transmission lines in the face of strong convective winds.

[0064] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0065] This invention provides a method and system for assessing the failure risk of transmission lines in the face of severe convective winds. The method includes: establishing a theoretical model of the wind field for severe convective winds based on measured data and wind field variation patterns; selecting an actual engineering project to establish a transmission line model; performing simulation analysis on the established theoretical model and transmission line model under different wind speed conditions to obtain the structural response of the transmission line model; applying horizontal thrust to the transmission line model to conduct nonlinear pushover analysis to obtain the structural capability of the transmission line model; fitting a vulnerability curve based on the structural response and structural capability; and conducting a risk assessment based on the vulnerability curve. This invention, by establishing a wind field model and a transmission line model, conducting disaster simulation, risk assessment, and fault prevention measures, provides key technical support for wind-resistant design, reveals the disaster mechanism and probabilistic risk of transmission lines induced by severe convective winds, and proposes preventive measures to address transmission line faults induced by severe convective winds. Attached Figure Description

[0066] Figure 1 This is a flowchart of the transmission line failure risk assessment method for strong convective winds according to the present invention;

[0067] Figure 2 This is a schematic diagram of the transmission line failure risk assessment system for strong convective winds according to the present invention.

[0068] Figure 3 This is a schematic diagram of the computer equipment for assessing the failure risk of power transmission lines in the face of strong convective winds, as described in this invention.

[0069] Figure 4 This is a basic flowchart of the transmission line failure risk assessment method for strong convective winds of the present invention.

[0070] Figure 5 A diagram of the downburst wind speed simulation platform used in the present invention for assessing the failure risk of transmission lines in the face of strong convective winds;

[0071] Figure 6 A diagram of a tornado wind speed simulation platform used in the present invention to assess the failure risk of transmission lines in the face of strong convective winds;

[0072] Figure 7 The numerical model diagram of the transmission line is a schematic diagram of the transmission line failure risk assessment method for strong convective winds according to the present invention.

[0073] Figure 8 This is a schematic diagram of the wind load application point of a transmission line model, illustrating the transmission line failure risk assessment method for strong convective winds according to the present invention.

[0074] Figure 9 This is a schematic diagram of the downburst-induced tower collapse process of the transmission line in the transmission line failure risk assessment method for strong convective winds of the present invention.

[0075] Figure 10 This is a schematic diagram of the tornado-induced tower collapse process of the transmission line failure risk assessment method for strong convective winds according to the present invention.

[0076] Figure 11 This invention presents a curve illustrating the wind resistance capability of a transmission line tower collapse fault under a downburst current, based on the transmission line failure risk assessment method for strong convective winds.

[0077] Figure 12 This invention presents a curve illustrating the wind resistance capability of a transmission line under a downburst fault due to wind deflection, based on the transmission line failure risk assessment method for strong convective winds.

[0078] Figure 13This invention presents a method for assessing the failure risk of transmission lines under severe convective winds, including a graph illustrating the wind resistance capability of transmission line tower collapse faults during tornadoes.

[0079] Figure 14 This invention presents a method for assessing the failure risk of transmission lines under severe convective winds, including a wind resistance curve for transmission lines under tornado-induced wind deflection faults.

[0080] Figure 15 This is a graph showing the significant parameters of the sensitivity of transmission lines under downburst current in the transmission line failure risk assessment method for strong convective winds of this invention.

[0081] Figure 16 The diagram shows the significant parameters of transmission line sensitivity under tornadoes in the transmission line failure risk assessment method for strong convective winds according to the present invention.

[0082] Figure 17 This invention presents a risk level diagram of transmission tower collapse under downburst current in the transmission line failure risk assessment method for strong convective winds.

[0083] Figure 18 This is a diagram illustrating the risk level of transmission tower wind deflection under a downburst current in the transmission line failure risk assessment method for strong convective winds of this invention.

[0084] Figure 19 This invention presents a method for assessing the failure risk of transmission lines in the face of strong convective winds, along with a risk level diagram of transmission tower collapse under tornadoes.

[0085] Figure 20 This invention presents a method for assessing the failure risk of transmission lines in the face of strong convective winds, including a diagram illustrating the wind deflection risk level of transmission towers under tornadoes.

[0086] Figure 21 This is a schematic diagram illustrating the early prediction of meteorological parameters in a certain area using echo radar technology, which is part of the transmission line failure risk assessment method for strong convective winds according to the present invention.

[0087] Figure 22 This invention presents a method for assessing the failure risk of transmission lines in the face of strong convective winds, and a visualization assessment platform for the risk of transmission lines in the face of strong convective winds. Detailed Implementation

[0088] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings:

[0089] Example 1

[0090] This invention provides a method for assessing the failure risk of transmission lines in the face of strong convective winds, as shown in the flowchart below. Figure 1 As shown, it includes:

[0091] S1. Based on measured data and wind field variation patterns, establish a theoretical model of strong convective wind field, and select actual engineering projects to establish transmission line models;

[0092] S2. Based on the established theoretical model of strong convective wind field and the transmission line model, simulation analysis was conducted under different wind speed conditions to obtain the structural response of the transmission line model;

[0093] S3. Apply horizontal thrust to the transmission line model and conduct nonlinear pushover analysis to obtain the structural capability of the transmission line model. Fit the vulnerability curve based on the structural response and structural capability.

[0094] S4. Conduct a risk assessment based on the fragility curve.

[0095] Step S1 specifically includes:

[0096] Establishment of simulation of strong convective wind field and numerical simulation of transmission lines:

[0097] (1) Establish a theoretical model of strong convective wind field, such as storm surge and tornado. The modeling process takes into account the randomness and pulsation of wind speed and compile a strong convective wind simulation and analysis platform.

[0098] (2) Select typical actual projects and use finite element software to establish a refined numerical model of important transmission lines. The model includes at least one transmission tower and two spans of transmission lines to fully consider the influence of tower-line coupling effect on the wind vibration response of the transmission tower. Use the shape finding method to iteratively adjust the sag of the conductor and ground wire so that the tension and shape in the transmission line are the same as in reality.

[0099] (3) Divide the transmission tower and transmission line into different sections and segments respectively. The height of the section of the transmission tower shall not exceed 10m and the length of the transmission line segment shall not exceed 8m. Calculate the wind load time history of different sections and segments based on the current regulations and apply it in the form of concentrated force.

[0100] Step S2 specifically includes:

[0101] Simulation of power transmission line disaster induced by strong convective winds:

[0102] (4) Based on the design wind speed definition of the transmission line, under different wind speed conditions of storm surge and tornado, and considering the cumulative damage of transmission tower components under wind load, nonlinear dynamic analysis of the transmission line under strong convective wind is carried out.

[0103] (5) Conduct a simulation of transmission line tower collapse under strong convective winds to identify vulnerable components, and conduct a simulation of transient wind deflection of insulator strings to obtain the wind deflection mechanism.

[0104] (6) The wind speed is gradually increased to calculate the entire process of the transmission line from elasticity to failure, and a wind resistance verification model for typical faults of transmission line tower collapse and wind deflection under strong convective wind is established.

[0105] Step S3 specifically includes:

[0106] (7) Conduct nonlinear pushover analysis and classify the multi-objective risk level of tower collapse based on the tower top displacement or displacement angle, including minor damage, moderate damage and collapse; classify the wind deflection risk level based on the minimum electrical clearance.

[0107] (8) Select the uncertainty parameters of the strong convective wind field. Downbursts include the maximum wind speed, moving speed and distance of the vertical and radial wind profiles; tornadoes include the reference height, vortex core radius, vortex ratio and maximum wind speed; carry out sensitivity analysis of transmission lines under strong convective winds to identify key parameters.

[0108] (9) Calculate multiple discrete failure probability points, select failure probability points for fitting, obtain vulnerability curves, and assess the risk of transmission line failure under strong convective winds.

[0109] After step S4, the following also includes:

[0110] (10) Use echo radar to monitor wind field parameter changes in real time, and use machine learning intelligent algorithms (such as long short-term memory artificial neural networks) to fit historical data to predict future meteorological parameters.

[0111] (11) Based on the early prediction results of intelligent algorithms and the monitoring of wind field parameter changes by echo radar, a transmission line risk visualization assessment platform integrating multiple parameters and multiple targets is developed, and early warning of typical faults such as tower collapse and wind deflection is proposed.

[0112] (12) In response to tower collapse accidents, non-destructive reinforcement methods for transmission tower components, energy-consuming and vibration-damping technologies, and the addition of transverse diaphragms can be proposed; in response to wind deflection accidents, conductor grounding devices, wind deflection blocking technologies, and wind deflection suppression devices can be proposed to enhance the ability of transmission lines to cope with extreme disasters.

[0113] Example 2

[0114] Based on the same inventive concept, this invention also provides a transmission line failure risk assessment system for strong convective winds, such as... Figure 2 As shown, it includes: a model building module, a simulation analysis module, a vulnerability curve fitting module, and a risk assessment module;

[0115] Model building module: Based on measured data and wind field variation patterns, a theoretical model of strong convective wind field is established, and a transmission line model is established by selecting actual engineering projects;

[0116] Simulation analysis module: Based on the established theoretical model of strong convective wind field and transmission line model, simulation analysis is performed under different wind speed conditions to obtain the structural response of the transmission line model;

[0117] The vulnerability curve fitting module applies a horizontal thrust to the transmission line model to conduct nonlinear pushover analysis and obtain the structural capability of the transmission line model. Based on the structural response and structural capability, a vulnerability curve is fitted.

[0118] Risk assessment module: Conducts risk assessment based on fragility curve.

[0119] Preferably, the strong convective wind field theoretical model in the model building module is built by taking the data corresponding to the wind field parameters as input and the wind load time history as output; the strong convective wind field theoretical model includes at least one or more of the following: downburst model or tornado model.

[0120] Preferably, the wind field parameters of the downburst model in the model building module include at least one or more of the following: maximum wind speed in the vertical wind profile, maximum wind speed in the radial wind profile, and moving speed and distance; and the wind field parameters of the tornado model include at least one or more of the following: reference height, vortex core radius, vortex ratio, or maximum wind speed.

[0121] Preferably, the transmission line model in the model building module is built by taking the wind load time history as input and the response of the transmission line in the wind field where the transmission line model is located as output.

[0122] Preferably, the simulation analysis module is specifically used for:

[0123] The data corresponding to the key wind field parameters are input into the strong convective wind field theoretical model to obtain the wind load time history. The wind load time history is then input into the transmission line model to obtain the transmission line response in the wind field where the transmission line model is located.

[0124] Nonlinear tower collapse simulations were conducted based on the response of the transmission line model in the wind field to identify vulnerable components of the transmission line model and clarify the impact of vulnerable components on the stress in adjacent areas.

[0125] Based on the response of the transmission line in the wind field where the transmission line model is located and the influence of vulnerable components on the stress of adjacent areas, the wind speed is gradually increased to simulate the entire process of the transmission line from elastic deformation to failure. A disaster simulation is carried out to establish a wind resistance verification model for typical wind deflection faults and tower collapse accidents of transmission lines under strong convective winds.

[0126] The data corresponding to the key wind field parameters are input into the wind resistance verification model of the strong convective wind field theoretical model under the typical wind deflection fault and tower collapse accident to obtain the structural response of the transmission line model.

[0127] The key wind field parameters are obtained by conducting sensitivity analysis of transmission lines under strong convective winds to identify key parameters.

[0128] Preferably, the module for fitting the fragility curve is specifically used for:

[0129] The structural capability of the transmission line model is obtained by applying a horizontal thrust to the model and conducting nonlinear pushover analysis.

[0130] By comparing the structural response of the transmission line with the structural capability of the transmission line model, the probability that the structural response of the transmission line exceeds the structural capability of the transmission line model is determined, and multiple discrete failure probability points are obtained.

[0131] The vulnerability curve is obtained by fitting a log-normal distribution to multiple discrete failure probability points.

[0132] Preferably, the risk assessment module is specifically used for:

[0133] Based on the vulnerability curve, the risk of transmission line failure under strong convective winds is assessed for typical wind deflection faults and tower collapse accidents.

[0134] Preferably, after the risk assessment module, a handling module is further included, the handling module being used for:

[0135] Based on the risk assessment results of typical transmission line wind deflection faults and tower collapse accidents in response to strong convective winds, echo radar is used to monitor wind field parameter changes in real time, and machine learning intelligent algorithms are used to fit historical data to predict future meteorological parameters.

[0136] Based on the monitoring of wind field parameter changes by echo radar and the use of future meteorological parameters by intelligent algorithms, early warnings can be given for typical tower collapse faults and typical wind deflection faults.

[0137] Based on the type of risk identified in early warnings, corresponding technical measures are implemented.

[0138] The risk types mentioned in the early warning include at least one or more of the following: typical tower collapse accidents or typical wind deflection accidents.

[0139] Preferably, in the risk assessment module, the risk level of typical wind deflection faults is divided into multi-objective risk levels of tower collapse based on tower top displacement or displacement angle. The risk levels include minor damage, moderate damage, and collapse.

[0140] Preferably, the risk level of typical tower collapse faults in the risk assessment module is based on the minimum electrical clearance.

[0141] Example 3

[0142] like Figure 3As shown, the present invention also provides a computer device, which may be a computer device, a microcontroller device, a smart mobile device, etc. The computer device in this embodiment may include a processor, a memory, a transceiver component, etc. The memory, processor, and transceiver component are connected via a bus; the memory can be used to store executable programs, and an exemplary executable program may include instructions; the processor is used to execute the instructions stored in the memory. The memory can also be used to store data, which can be accessed and / or modified when instructions are executed.

[0143] The processor may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, and it is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the storage medium to realize the corresponding method flow or corresponding function, so as to realize the steps of the transmission line failure risk assessment method for strong convective winds in the above embodiments.

[0144] Example 4

[0145] Based on the same inventive concept, this invention also provides a readable storage medium, specifically a computer device readable storage medium (Memory). This readable storage medium is a memory device within a computer device used to store programs and data. It is understood that the storage medium here can include both the built-in storage medium of the computer device and extended storage media supported by the computer device. The storage medium provides storage space, which stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more executable programs (including program code). It should be noted that the storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. Loading and executing one or more instructions stored in the storage medium by the processor can implement the steps of the transmission line failure risk assessment method for strong convective winds described in the above embodiments.

[0146] Example 5

[0147] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0148] The overall concept proposed in this invention is as follows: Figure 4 As shown, the specific implementation method is as follows:

[0149] Step 1: Establishment of numerical simulation of strong convective wind field and transmission line

[0150] (1) Based on measured data and wind field variation patterns, a theoretical model of strong convective wind field was established, and a simulation and analysis platform for strong convective wind was developed, such as... Figure 5 , Figure 6 As shown, the wind profiles of downbursts and tornadoes in different directions can be represented as follows:

[0151] V(z) = 1.55(z / δ) 1 / 6 [1-erf(0.7z / δ)]×V max

[0152]

[0153] In the formula, V r,max V represents the maximum radial wind speed of the downburst. max The maximum wind speed of the downburst; V(z) and V r (r) represents the vertical and radial wind speed profiles of the downburst, respectively; δ is the reference height; erf is the fault tolerance function; R r The radial dimension; r max χ represents the distance between the point of maximum wind speed and the center of the impact wind; U(r,z), W(r,z), and V(r,z) are the normalized radial, vertical, and tangential wind speed profiles of the tornado, respectively; r and z are the normalized radius and height of the tornado, respectively; and χ is a size constant.

[0154] (2) Select typical actual projects and establish a refined numerical model of important transmission lines using finite element software. This model includes at least one transmission tower and two spans of transmission lines to fully consider the influence of tower-line coupling effect on the wind vibration response of the transmission tower. The example transmission tower can be composed of angle steel components, steel pipe components, or a combination of angle steel and steel pipe components. Taking the finite element software ABAQUS as an example, the transmission tower members can be simulated using beam elements, and the transmission lines and insulator strings can be simulated using pole elements. Divide the transmission line into multiple segments and use the form-finding method to iteratively adjust the sag of the conductors and ground wires multiple times. Figure 7 The numerical model of the transmission line is illustrated.

[0155] (3) Divide the transmission tower and transmission line into different sections and segments, calculate the wind load time history of different sections and segments based on current regulations, and apply it in the form of concentrated forces. Figure 7 The diagram illustrates the point where strong convective wind loads are applied in the numerical model of the transmission line.

[0156] Step 2: Simulation of Transmission Line Disasters Induced by Strong Convective Winds

[0157] (4) The design wind speed of the schematic transmission tower is 27 m / s. Based on this definition, different wind speed conditions such as storm surges and tornadoes are considered. Considering the cumulative damage effect of the transmission tower components under wind load, a wind vibration response analysis of the transmission line under strong convective winds is carried out based on the nonlinear dynamic analysis method. It should be noted that the cumulative damage effect can comprehensively consider the maximum plastic deformation, cumulative plastic strain, energy accumulation, etc. of the components; the damage index considering the maximum plastic deformation and cumulative plastic strain can be expressed as:

[0158]

[0159] E D =E(1-ξ1Da)

[0160]

[0161] In the formula, Da represents the cumulative damage value; This represents the strain corresponding to the yield strength; Indicates the maximum plastic strain; Indicates the plastic strain of steel; Represents the ultimate plastic strain; β is the weighting coefficient; N is the number of half-cycles; E and σ s E represents the elastic modulus and yield strength under undamaged conditions, respectively. D and ξ1 and ξ2 are the elastic modulus and yield strength after damage, respectively; ξ1 and ξ2 are material parameters.

[0162] (5) Conduct nonlinear tower collapse simulation of transmission lines under strong convective winds, with wind load application points as follows: Figure 8 As shown, the weak sections and locations of the transmission tower are identified, and the vulnerable components of the transmission tower and their impact on the stress of adjacent components are determined. Figure 9 , Figure 10 As shown, transient wind deflection simulation of transmission lines under strong convective winds was carried out to obtain the wind deflection mechanism caused by strong convective winds.

[0163] (6) By gradually increasing the wind speed, the entire process from elasticity to failure of the transmission line is obtained through simulation calculations, and a wind resistance verification model for typical faults such as tower collapse and wind deflection of transmission lines under strong convective winds is established. Figure 11 , Figure 12 , Figure 13 , Figure 14 As shown, the wind resistance curves for typical faults of transmission line tower collapse and wind deflection described in the embodiments of the present invention are given respectively.

[0164] Step 3: Probabilistic Risk Assessment of Transmission Lines under Severe Convective Winds

[0165] (7) Conduct nonlinear pushover analysis and classify the multi-objective risk level of tower collapse based on the tower top displacement or displacement angle as indicators, including minor damage, moderate damage and collapse, with corresponding limits of 50%, 75% and 100% of the collapse threshold; classify the wind deflection risk level based on the minimum electrical clearance, such as the minimum electrical clearance H of the dual circuit can be 2.7m, and the three-stage risk levels can be 1.5×H, 1.25×H and 1.0×H.

[0166] (8) Select the uncertainty parameters of the strong convective wind field. Downbursts include the maximum wind speed, moving speed and distance of the vertical and radial wind profiles; tornadoes include the reference height, vortex core radius, vortex ratio and maximum wind speed; carry out sensitivity analysis of transmission lines under strong convective winds to identify key parameters. Figure 15 and Figure 16 The figures show the distribution of significant parameters affecting the sensitivity of transmission lines to wind-induced vibration response under the influence of downbursts and tornadoes. V t It is the movement speed of Downward Strike Burst; d o denoted as , and e as , which is the horizontal distance from the center of the downburst.

[0167] (9) Multiple discrete failure probability points are calculated, and the structural response is fitted in logarithmic space. Based on the obtained disaster demand model, the vulnerability curve is obtained to assess the transmission line fault risk under strong convective winds. The failure probability point fitting formula can be calculated as follows:

[0168]

[0169] p r =P(D>C)

[0170] In the formula, P(·) represents probability; a, b, and c are regression parameters; S D Indicates the median structural seismic demand; IM is the seismic intensity index; p r denoted as the risk probability; D and C represent the wind vibration response and structural capacity of the transmission line, respectively. Figure 17 , Figure 18 , Figure 19 and Figure 20 The risk level of transmission lines under strong convective winds.

[0171] Step 4: Typical Fault Prevention Technologies and Measures for Transmission Lines Facing Strong Convective Winds

[0172] (10) In order to take countermeasures before extreme winds occur, echo radar is used to monitor changes in local wind field parameters in real time. Figure 21This illustrates the use of echo radar technology for early prediction of meteorological parameters in a certain area. Furthermore, machine learning algorithms (such as Long Short-Term Memory artificial neural networks) can be used to fit historical data to predict future meteorological parameters. The data input and parameter updates for the Long Short-Term Memory artificial neural network can be expressed using the following formula:

[0173]

[0174] In the formula, LSTM(·) represents the computation method using the LSTM model; x t For input samples; and Output values ​​forward and backward respectively; and These output the values ​​forward and backward from the previous time step, respectively. and These are the forward and backward weight matrices, respectively; b y For the paranoia matrix; y t Output the value at this moment.

[0175] (11) Based on the monitoring of wind field parameter changes by echo radar, intelligent algorithms are used to obtain early prediction results. A multi-parameter and multi-target fusion transmission line risk visualization assessment platform is developed, which can provide early warning for typical faults such as tower collapse and wind deflection. Figure 22 This is the power transmission line risk visualization assessment platform described in the embodiments of the present invention.

[0176] (12) In response to tower collapse accidents, non-destructive reinforcement methods for transmission tower components, energy-consuming and vibration-damping technologies, and the addition of transverse diaphragms can be proposed; in response to wind deflection accidents, conductor grounding devices, wind deflection blocking technologies, and wind deflection suppression devices can be proposed to enhance the ability of transmission lines to cope with extreme disasters.

[0177] In summary, this invention provides a method and system for assessing the failure risk of transmission lines in the face of severe convective winds, comprising:

[0178] Based on measured data and wind field variation patterns, a theoretical model of a strong convective wind field is established, and a transmission line model is established using an actual engineering project. Simulation analysis is conducted on the established strong convective wind field theoretical model and the transmission line model under different wind speed conditions to obtain the structural response of the transmission line model. A horizontal thrust is applied to the transmission line model to conduct nonlinear pushover analysis to obtain its structural capability. A vulnerability curve is fitted based on the structural response and structural capability. Risk assessment is then performed based on the vulnerability curve. This invention, by establishing a wind field model and a transmission line model, conducting disaster simulation, risk assessment, and fault prevention measures, provides key technical support for wind-resistant design, reveals the disaster mechanism and probabilistic risk of transmission lines induced by strong convective winds, and proposes preventive measures to address transmission line faults induced by strong convective winds.

[0179] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0180] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0181] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0182] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0183] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.

Claims

1. A method for assessing the failure risk of transmission lines in the face of severe convective winds, characterized in that, include: A theoretical model of strong convective wind field was established based on measured data and wind field variation patterns, and a transmission line model was established by selecting actual engineering projects. Based on the established theoretical model of strong convective wind field and the transmission line model, the structural response of the transmission line model was obtained through simulation analysis under different wind speed conditions. A horizontal thrust is applied to the transmission line model to conduct nonlinear pushover analysis to obtain the structural capability of the transmission line model. Based on the structural response and structural capability, a vulnerability curve is fitted. Risk assessment is conducted based on the fragility curve; The theoretical model of the strong convective wind field is established by taking the data corresponding to the wind field parameters as input and the wind load time history as output; the theoretical model of the strong convective wind field includes at least one or more of the following: downburst model or tornado model. The wind field parameters of the downburst model include at least one or more of the following: maximum wind speed in the vertical wind profile, maximum wind speed in the radial wind profile, and moving speed and distance. The wind field parameters of the tornado model include at least one or more of the following: reference height, vortex core radius, vortex ratio, or maximum wind speed. The structural response of the transmission line model was obtained through simulation analysis based on the established strong convective wind field theoretical model and the transmission line model under different wind speed conditions, including: The data corresponding to the key wind field parameters are input into the strong convective wind field theoretical model to obtain the wind load time history. The wind load time history is then input into the transmission line model to obtain the transmission line response in the wind field where the transmission line model is located. Nonlinear tower collapse simulations were conducted based on the response of the transmission line model in the wind field to identify vulnerable components of the transmission line model and clarify the impact of vulnerable components on the stress in adjacent areas. Based on the response of the transmission line in the wind field where the transmission line model is located and the influence of vulnerable components on the stress of adjacent areas, the wind speed is gradually increased to simulate the entire process of the transmission line from elastic deformation to failure. A disaster simulation is carried out to establish a wind resistance verification model for typical wind deflection faults and tower collapse faults of transmission lines under strong convective winds. The data corresponding to the key wind field parameters are input into the wind resistance verification model of the strong convective wind field theoretical model under the typical faults of wind deflection and tower collapse to obtain the structural response of the transmission line model. The key wind field parameters are obtained by conducting sensitivity analysis of transmission lines under strong convective winds to identify key parameters. The process of applying a horizontal thrust to the transmission line model and conducting nonlinear pushover analysis yields the structural capability of the transmission line model. Based on the structural response and structural capability, a vulnerability curve is fitted, including: The structural capability of the transmission line model is obtained by applying a horizontal thrust to the model and conducting nonlinear pushover analysis. By comparing the structural response of the transmission line with the structural capability of the transmission line model, the probability that the structural response of the transmission line exceeds the structural capability of the transmission line model is determined, and multiple discrete failure probability points are obtained. The vulnerability curve is obtained by fitting a log-normal distribution to multiple discrete failure probability points.

2. The method as described in claim 1, characterized in that, The transmission line model is established by taking the wind load time history as input and the response of the transmission line in the wind field where the transmission line model is located as output.

3. The method as described in claim 1, characterized in that, The risk assessment based on the fragility curve includes: Based on the vulnerability curve, the risk of transmission line failure under strong convective winds is assessed for typical wind deflection faults and tower collapse faults.

4. The method as described in claim 1, characterized in that, Following the risk assessment based on the fragility curve, the process also includes: Based on the risk assessment results of typical transmission line wind deflection faults and tower collapse faults in response to strong convective winds, echo radar is used to monitor wind field parameter changes in real time, and machine learning intelligent algorithms are used to fit historical data to predict future meteorological parameters. Based on the monitoring of wind field parameter changes by echo radar and the use of future meteorological parameters by intelligent algorithms, early warnings can be given for typical tower collapse faults and typical wind deflection faults. Based on the type of risk identified in early warnings, corresponding technical measures are implemented. The risk types mentioned in the early warning include at least one or more of the following: typical tower collapse failure or typical wind deflection failure.

5. The method as described in claim 4, characterized in that, The risk level of the typical wind deflection fault is divided into multiple risk levels of tower collapse based on the tower top displacement or displacement angle. The risk levels include minor damage, moderate damage and collapse.

6. The method as described in claim 4, characterized in that, The risk level of the typical tower collapse fault is classified based on the minimum electrical clearance.

7. A transmission line failure risk assessment system for strong convective winds, characterized in that, include: Establish a model module, a simulation analysis module, a vulnerability curve fitting module, and a risk assessment module; Model building module: Based on measured data and wind field variation patterns, a theoretical model of strong convective wind field is established, and a transmission line model is established by selecting actual engineering projects; Simulation analysis module: Based on the established theoretical model of strong convective wind field and transmission line model, simulation analysis is performed under different wind speed conditions to obtain the structural response of the transmission line model; The vulnerability curve fitting module applies a horizontal thrust to the transmission line model to conduct nonlinear pushover analysis and obtain the structural capability of the transmission line model. Based on the structural response and structural capability, a vulnerability curve is fitted. Risk assessment module: Performs risk assessment based on fragility curve; The theoretical model of the strong convective wind field in the model building module is established by taking the data corresponding to the wind field parameters as input and the wind load time history as output; the theoretical model of the strong convective wind field includes at least one or more of the following: downburst model or tornado model. The wind field parameters of the downburst model in the model building module include at least one or more of the following: maximum wind speed in the vertical wind profile, maximum wind speed in the radial wind profile, and moving speed and distance. The wind field parameters of the tornado model include at least one or more of the following: reference height, vortex core radius, vortex ratio, or maximum wind speed. The simulation analysis module is specifically used for: The data corresponding to the key wind field parameters are input into the strong convective wind field theoretical model to obtain the wind load time history. The wind load time history is then input into the transmission line model to obtain the transmission line response in the wind field where the transmission line model is located. Nonlinear tower collapse simulations were conducted based on the response of the transmission line model in the wind field to identify vulnerable components of the transmission line model and clarify the impact of vulnerable components on the stress in adjacent areas. Based on the response of the transmission line in the wind field where the transmission line model is located and the influence of vulnerable components on the stress of adjacent areas, the wind speed is gradually increased to simulate the entire process of the transmission line from elastic deformation to failure. A disaster simulation is carried out to establish a wind resistance verification model for typical wind deflection faults and tower collapse faults of transmission lines under strong convective winds. The data corresponding to the key wind field parameters are input into the wind resistance verification model of the strong convective wind field theoretical model under the typical faults of wind deflection and tower collapse to obtain the structural response of the transmission line model. The key wind field parameters are obtained by conducting sensitivity analysis of transmission lines under strong convective winds to identify key parameters. The module for fitting the vulnerability curve is specifically used for: The structural capability of the transmission line model is obtained by applying a horizontal thrust to the model and conducting nonlinear pushover analysis. By comparing the structural response of the transmission line with the structural capability of the transmission line model, the probability that the structural response of the transmission line exceeds the structural capability of the transmission line model is determined, and multiple discrete failure probability points are obtained. The vulnerability curve is obtained by fitting a log-normal distribution to multiple discrete failure probability points.

8. The system as described in claim 7, characterized in that, The transmission line model in the model building module is built by taking the wind load time history as input and the response of the transmission line in the wind field where the transmission line model is located as output.

9. The system as described in claim 7, characterized in that, The risk assessment module is specifically used for: Based on the vulnerability curve, the risk of transmission line failure under strong convective winds is assessed for typical wind deflection faults and tower collapse faults.

10. The system as described in claim 7, characterized in that, Following the risk assessment module, a handling module is also included, which is used for: Based on the risk assessment results of typical transmission line wind deflection faults and tower collapse faults in response to strong convective winds, echo radar is used to monitor wind field parameter changes in real time, and machine learning intelligent algorithms are used to fit historical data to predict future meteorological parameters. Based on the monitoring of wind field parameter changes by echo radar and the use of future meteorological parameters by intelligent algorithms, early warnings can be given for typical tower collapse faults and typical wind deflection faults. Based on the type of risk identified in early warnings, corresponding technical measures are implemented. The risk types mentioned in the early warning include at least one or more of the following: typical tower collapse failure or typical wind deflection failure.

11. The system as described in claim 9, characterized in that, In the risk assessment module, the risk level of typical wind-induced deviation faults is divided into multi-objective risk levels for tower collapse based on tower top displacement or displacement angle. The risk levels include minor damage, moderate damage, and collapse.

12. The system as described in claim 9, characterized in that, The risk level of typical tower collapse faults in the risk assessment module is based on the minimum electrical clearance.

13. A computer device, characterized in that, include: At least one processor and memory; The memory and processor are connected via a bus; The memory is used to store one or more programs; When the one or more programs are executed by the at least one processor, a method for assessing the failure risk of transmission lines in the face of strong convective winds as described in any one of claims 1 to 6 is implemented.

14. A computer-readable storage medium, characterized in that, It contains an execution program, which, when executed, implements a method for assessing the failure risk of transmission lines in the face of strong convective winds as described in any one of claims 1 to 6.

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