Power transmission line galloping nonlinear simulation and prediction method, system and equipment based on microtopography multi-source data driving and medium

Abstract

The invention discloses a power transmission line galloping nonlinear simulation and prediction method, system and device based on microtopography multi-source data driving and a medium, and the method comprises the steps: analyzing a power transmission line GIM model and geographic elevation data, and constructing a three-dimensional digital twinborn model; secondly, introducing a microtopography correction factor to carry out downscaling correction on the macroscopic meteorological wind speed, and obtaining a local flow field of the conductor; then, based on the non-linear aerodynamic characteristics of the ice-coated conductor, establishing a 3-DOF coupling kinetic equation containing vertical, horizontal and torsional degrees of freedom; and finally, solving a conductor galloping track and amplitude through a time integration algorithm, and issuing risk early warning based on an inter-phase distance threshold. According to the method, the micro-topography wind field effect and the multi-degree-of-freedom coupling mechanism can be truly reflected, the prediction accuracy of the power transmission line galloping disaster is remarkably improved, and a scientific basis is provided for power grid disaster prevention.

Description

Technical Field

[0001] This invention relates to the field of transmission line simulation and prediction technology, and in particular to a method, system, equipment and medium for nonlinear simulation and prediction of transmission line galloping based on micro-topography multi-source data. Background Technology

[0002] The reliability of energy supply is directly related to the safe and stable operation of overhead transmission lines. However, in severe weather, icy transmission lines are prone to galloping under wind excitation, and if galloping continues, it will inevitably lead to serious accidents. Especially in my country's high-altitude mountainous areas, the terrain varies greatly, and the wind field has significant funneling effect and non-stationary characteristics. After being affected by local micro-topography, transmission lines will frequently gallop, and the galloping patterns will be more complex, making traditional anti-galloping control measures often ineffective.

[0003] Existing research on transmission line galloping, both domestically and internationally, primarily relies on wind tunnel testing and numerical simulation techniques. However, these techniques still have significant shortcomings in practical engineering applications. For example, existing engineering calculation methods often employ single-degree-of-freedom models, neglecting the strong coupling effect between the conductor's torsional motion and its vertical and horizontal movements. In practical applications, ignoring torsional coupling in asymmetric icing conductors leads to severely distorted prediction results. Furthermore, existing simulations are typically based on quasi-steady assumptions and use fixed aerodynamic coefficients. However, under complex wind fields with micro-topography, the large-amplitude movement of transmission lines causes drastic changes in instantaneous angle of attack, exhibiting significant nonlinear aerodynamic characteristics and wake interference effects. Traditional linear aerodynamic models cannot accurately describe this process.

[0004] Therefore, there is an urgent need to develop a nonlinear simulation and prediction method for transmission line galloping based on multi-source data driven by micro-topography, so as to improve the proactive defense capability of power grid disaster prevention and mitigation in complex environments. Summary of the Invention

[0005] In view of the aforementioned existing problems, the present invention is proposed.

[0006] Therefore, this invention provides a method, system, equipment, and medium for nonlinear simulation and prediction of transmission line galloping based on micro-topography multi-source data, which solves the problems in the prior art where the transmission line galloping simulation model does not fully consider micro-topography wind field correction, has insufficient multi-degree-of-freedom nonlinear coupling effect, and has low integration with the power grid information model, resulting in low accuracy of galloping prediction in complex mountainous environments.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides a nonlinear simulation and prediction method for transmission line galloping based on multi-source data driven by micro-topography, including: A three-dimensional digital twin model of the transmission line is constructed based on the acquired multi-source monitoring data of the transmission line; Identify the micro-topographic features of the transmission line, and use the micro-topographic correction factor to correct the macro wind speed in the multi-source monitoring data of the transmission line to obtain the local corrected wind speed vector; An aerodynamic coefficient model was constructed based on the cross-sectional characteristics of the icing conductor. A coupled dynamic equation for multi-span conductor-insulator strings considering geometric nonlinearity and torsional stiffness is established using Hamilton's principle. The locally modified wind speed vector is substituted into the coupled dynamic equation of the multi-span conductor-insulator string, and the time domain solution is performed in combination with the aerodynamic coefficient model to obtain the conductor galloping trajectory and amplitude. A risk assessment is then performed based on a preset safety threshold.

[0008] As a preferred embodiment of the nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data driven by the present invention, the construction of the three-dimensional digital twin model of the transmission line includes: Acquire multi-source monitoring data for transmission lines, including power grid information model data of transmission lines, high-precision digital elevation model data of transmission channels, and meteorological monitoring data; The spatial geometric parameters and physical attributes of the transmission line are extracted from the power grid information model data of the transmission line, and the physical attributes are corrected by combining the meteorological monitoring data. The correction includes at least calculating the total mass per unit length of the icing conductor, the total moment of inertia and the centroidal eccentricity of the icing based on the icing thickness and icing density. Based on the geometric parameters and the corrected physical properties, a structured finite element model of the transmission line is constructed in three-dimensional space. Based on the high-precision digital elevation model data, the elevation of the suspension point of the model is adapted to the terrain to form a three-dimensional digital twin model of the transmission line that reflects the real spatial form and mechanical properties.

[0009] As a preferred embodiment of the nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data described in this invention, the step of correcting the macroscopic wind speed in the multi-source monitoring data of the transmission line using a micro-topography correction factor includes: The terrain acceleration factor corresponding to the micro-terrain category is determined based on the micro-terrain features; The macroscopic reference wind speed is obtained from the monitoring, and the macroscopic wind speed in the multi-source monitoring data of the transmission line is jointly corrected by combining the wind profile height correction coefficient and the terrain acceleration factor. The local corrected wind speed vector acting on the conductor is calculated based on the joint correction results.

[0010] As a preferred embodiment of the nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data driven by the present invention, the aerodynamic coefficient model includes: Determine the initial angle of attack of the icing conductor cross-section; The instantaneous angle of attack is calculated based on the initial angle of attack and the motion state of the conductor; Based on the instantaneous wind angle of attack, an aerodynamic coefficient model is established by fitting a nonlinear function, wherein the aerodynamic coefficients include lift coefficient, drag coefficient, and torque coefficient.

[0011] The beneficial effects of this preferred technical solution are: it breaks through the limitation of traditional single-degree-of-freedom models that cannot reflect the torsional excitation galloping mechanism, and can more realistically simulate the complex galloping behavior of asymmetric icing conductors.

[0012] As a preferred embodiment of the nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data driven by the present invention, the method for establishing the coupled dynamic equations of multi-span conductor-insulator strings considering geometric nonlinearity and torsional stiffness using Hamilton's principle includes: The transmission line is discretized into multiple spatial beam elements, and the mass matrix, damping matrix and stiffness matrix of each spatial beam element are derived. Based on the mass matrix, damping matrix, and stiffness matrix, a coupled dynamic equation for a multi-span conductor-insulator string, including vertical displacement, horizontal displacement, and torsional angle, is established according to Hamilton's principle.

[0013] As a preferred embodiment of the nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data driven by the present invention, the time-domain solution includes: The instantaneous wind angle of attack and aerodynamic load vector are updated according to the current conductor motion state at each time step; The dynamic equations are solved iteratively using an incremental time integration algorithm to obtain the displacement, velocity, and acceleration of the conductor at each time step. Extract the galloping trajectory during the steady-state phase and calculate the maximum vertical and horizontal galloping amplitudes.

[0014] The beneficial effects of this preferred technical solution are: it can accurately quantify the amplitude of the dance, greatly improving the accuracy of disaster early warning in complex environments.

[0015] As a preferred embodiment of the nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data driven by the present invention, it further includes: Based on the conductor galloping trajectory and amplitude, a safety threshold is set in conjunction with the phase-to-phase distance of the transmission line; Determine whether the maximum vertical sway amplitude exceeds the safety threshold; if it does, generate a risk warning signal. Output the visualization results of the conductor galloping trajectory and the corresponding risk assessment conclusions.

[0016] Secondly, this invention provides a nonlinear simulation and prediction system for transmission line galloping based on multi-source data driven by micro-topography, comprising: The digital model building module is used to build a three-dimensional digital twin model of the transmission line based on the acquired multi-source monitoring data of the transmission line; The micro-topography wind field correction module is used to identify the micro-topography features where the transmission line is located, and to correct the macro wind speed in the multi-source monitoring data of the transmission line using the micro-topography correction factor to obtain the local corrected wind speed vector. The aerodynamic coefficient construction module is used to construct aerodynamic coefficient models for the cross-sectional characteristics of icing conductors. The dynamic equation construction module is used to establish coupled dynamic equations for multi-span conductor-insulator strings that take into account geometric nonlinearity and torsional stiffness using Hamilton's principle. The galloping prediction module is used to input the local modified wind speed vector into the coupled dynamic equation of the multi-span conductor-insulator string, combine it with the aerodynamic coefficient model to solve in the time domain, obtain the conductor galloping trajectory and amplitude, and conduct risk assessment based on a preset safety threshold.

[0017] Thirdly, the present invention provides an electronic device, including a memory and a processor; the memory is used to store computer-executable instructions, and the processor executes the computer-executable instructions to implement the steps of a nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data.

[0018] Fourthly, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of a nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data.

[0019] Compared with existing technologies, the beneficial effects of this invention are as follows: By introducing micro-topographic wind field correction and a nonlinear aerodynamic model, this invention effectively solves the problems of inaccurate wind field description and simplified aerodynamic calculation in complex mountainous environments by traditional models, significantly improving the prediction accuracy of galloping amplitude and trajectory. This invention, by establishing a 3-DOF dynamic model including torsional degrees of freedom, overcomes the limitation of traditional single-degree-of-freedom models in reflecting the torsional-induced galloping mechanism, enabling more realistic simulation of the complex galloping behavior of asymmetric icing conductors. This invention directly utilizes power grid information model data to drive simulation modeling, breaking down the barriers between design data and simulation analysis, and providing an efficient digital twin tool for the full life-cycle management and disaster prevention and mitigation of transmission lines. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of the overall process logic of a nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data provided in an embodiment of the present invention.

[0022] Figure 2 This is a schematic diagram illustrating the wind field correction principle considering micro-topographic features in a nonlinear simulation and prediction method for transmission line galloping based on multi-source data driven by micro-topography, provided as an embodiment of the present invention.

[0023] Figure 3 The nonlinear curve of the aerodynamic coefficient of the icing conductor as a function of the wind angle of attack is provided in an embodiment of the present invention for a nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data.

[0024] Figure 4 This is a schematic diagram of the mechanical model of a three-degree-of-freedom (3-DOF) transmission line unit, which is provided as an embodiment of the present invention for a nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data.

[0025] Figure 5 The image shows a typical conductor galloping phase plane trajectory obtained from the calculation of a nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data provided in an embodiment of the present invention.

[0026] Figure 6 This is a functional module structure diagram of a nonlinear simulation and prediction system for transmission line galloping based on micro-topography multi-source data provided in an embodiment of the present invention. Detailed Implementation

[0027] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0028] Example 1, referring to Figures 1-4 As one embodiment of the present invention, a nonlinear simulation and prediction method for transmission line galloping based on multi-source data driven by micro-topography is provided, such as... Figure 1 The specific steps shown are as follows: S100: Construct a three-dimensional digital twin model of the transmission line based on the acquired multi-source monitoring data of the transmission line; S200: Identify the micro-topographic features of the transmission line and use the micro-topographic correction factor to correct the macro wind speed in the multi-source monitoring data of the transmission line to obtain the local corrected wind speed vector. S300: Constructing an aerodynamic coefficient model based on the cross-sectional characteristics of icing conductors; S400: Establish the coupled dynamic equations of multi-span conductor-insulator strings considering geometric nonlinearity and torsional stiffness using Hamilton's principle; S500: The locally modified wind speed vector is substituted into the coupled dynamic equation of the multi-span conductor-insulator string, and the time domain solution is performed in combination with the aerodynamic coefficient model to obtain the conductor galloping trajectory and amplitude, and a risk assessment is performed based on the preset safety threshold.

[0029] It should be noted that, to address the problems of insufficient micro-topographic wind field correction, inadequate multi-degree-of-freedom nonlinear coupling effects, and low integration with power grid information models in existing transmission line galloping simulation models, leading to low prediction accuracy in complex mountainous environments, this invention introduces micro-topographic wind field correction and a nonlinear aerodynamic model. This effectively solves the problems of inaccurate wind field description and simplified aerodynamic calculations in complex mountainous environments using traditional models, significantly improving the prediction accuracy of galloping amplitude and trajectory. This invention establishes a 3-DOF dynamic model including torsional degrees of freedom, overcoming the limitation of traditional single-degree-of-freedom models in reflecting torsional-induced galloping mechanisms, and can more realistically simulate the complex galloping behavior of asymmetric icing conductors. This invention directly utilizes power grid information model data to drive simulation modeling, breaking down the barriers between design data and simulation analysis, and providing an efficient digital twin tool for the full life-cycle management and disaster prevention and mitigation of transmission lines.

[0030] In this embodiment of the invention, step S100, which involves constructing a three-dimensional digital twin model of the transmission line based on the acquired multi-source monitoring data of the transmission line, includes: Acquire multi-source monitoring data for transmission lines, including power grid information model data of transmission lines, high-precision digital elevation model data of transmission channels, and meteorological monitoring data; Extract the spatial geometric parameters and physical attributes of the transmission line from the power grid information model data, and correct the physical attributes by combining meteorological monitoring data. The correction includes at least calculating the total mass per unit length of the icing conductor, the total moment of inertia, and the centroidal eccentricity of the icing based on the icing thickness and icing density. Based on geometric parameters and corrected physical properties, a structured finite element model of the transmission line is constructed in three-dimensional space. The elevation of the suspension point of the model is then adapted to the terrain based on high-precision digital elevation model data, forming a three-dimensional digital twin model of the transmission line that reflects the real spatial form and mechanical properties.

[0031] Specifically, conductor spans are extracted from the power grid information model data of transmission lines. Wire diameter Mass per unit length Tensile stiffness Torsional stiffness and initial tension Meanwhile, considering the changes in the physical properties of the line caused by icing, the physical properties are corrected based on meteorological monitoring data. This correction includes at least calculating the total mass per unit length (m), total moment of inertia (J), and centroidal eccentricity of the iced conductor based on the icing thickness and density; the formula is expressed as: in,, The mass of ice accretion per unit length. and Let be the moments of inertia of the conductor and the icing about their respective centroids. This is the eccentricity of the ice-covered centroid relative to the conductor axis.

[0032] In an optional embodiment, the construction of a three-dimensional digital twin model of a transmission line can also adopt a semantic modeling method based on the deep integration of BIM and GIS. By parsing the power grid information model data containing semantic information, the functional attributes and spatial relationships of components such as towers, conductors, and insulators are automatically identified and associated. A high-precision oblique photogrammetry real-scene model is integrated to construct a visualized digital twin with multi-level semantic information and real-scene fusion.

[0033] In an optional embodiment, the construction of a three-dimensional digital twin model of a transmission line can also adopt an automated modeling method driven by point cloud data and parametric templates. Point cloud data of the transmission corridor is obtained by using LiDAR scanning, and the catenary shape and tower position of the conductor are extracted by point cloud segmentation and recognition technology. Then, a three-dimensional model with accurate geometric shape and connection relationship is automatically generated by combining a parametric component library, so as to realize the rapid reconstruction from measured data to the twin model.

[0034] In this embodiment of the invention, step S200 identifies the micro-topographic features of the transmission line and uses a micro-topographic correction factor to correct the macroscopic wind speed in the multi-source monitoring data of the transmission line to obtain a locally corrected wind speed vector, including: The terrain acceleration factor for the corresponding micro-topography category is determined based on the micro-topography characteristics; The macroscopic reference wind speed is obtained from the monitoring, and the macroscopic wind speed in the multi-source monitoring data of the transmission line is jointly corrected by the wind profile height correction coefficient and the terrain acceleration factor. The local corrected wind speed vector acting on the conductor is calculated based on the joint correction results.

[0035] It should be noted that, as Figure 2 As shown, for complex mountainous areas such as Guizhou with their mountain passes and canyons, macroscopic meteorological wind speeds cannot be directly used for conductor stress calculations. This embodiment introduces a micro-topography correction model to downscale the macroscopic wind speed, obtaining a locally corrected wind speed vector.

[0036] Specifically, in this embodiment, the wind speed vector is locally corrected. The calculation is as follows: in, The macroscopic reference wind speed measured by the weather station; The wind profile height correction factor is typically calculated using an exponential law: ,in The average height of the conductor. It is the surface roughness index; This is the topographic acceleration factor, used to characterize the funnel effect or mountaintop acceleration effect. For typical mountain pass terrain, the topographic acceleration factor is... This information can be obtained by consulting CFD pre-computation databases or relevant standards.

[0037] In an alternative embodiment, macroscopic wind speed can also be corrected by using a dynamic correction model based on machine learning and CFD coupling. This model uses high-precision DEM data to drive CFD to pre-calculate wind fields in typical micro-topography, generating a nonlinear mapping dataset of local and macroscopic wind speeds. Subsequently, a neural network model is trained to directly predict the local corrected wind speed at the guide based on real-time meteorological data and terrain type.

[0038] In an optional embodiment, the macro wind speed can also be corrected using a statistical regression correction method based on field measurement data. This involves setting up miniature weather stations or laser wind radars in typical micro-topographic areas to obtain local wind speed measurement data, establishing a statistical regression relationship with the macro wind speeds of surrounding standard weather stations, and introducing covariates to construct a piecewise regression model, thereby achieving an empirical correction of the macro wind speed.

[0039] In this embodiment of the invention, step S300, which involves constructing an aerodynamic coefficient model for the cross-sectional characteristics of an icing conductor, includes: Determine the initial angle of attack of the icing conductor cross-section; Calculate the instantaneous angle of attack based on the initial angle of attack and the motion state of the conductor; Based on the instantaneous wind angle of attack, an aerodynamic coefficient model is established by fitting a nonlinear function, where the aerodynamic coefficients include lift coefficient, drag coefficient, and torque coefficient.

[0040] Specifically, such as Figure 3 The aerodynamic coefficients of the icing conductor shown exhibit strong nonlinearity. This embodiment, for a typical asymmetric icing cross-section, constructs a coefficient that varies with the instantaneous angle of attack. A changing aerodynamic model.

[0041] Specifically, the instantaneous angle of attack used in calculating aerodynamic forces. It depends not only on the initial angle of attack and conductor twist angle It is also related to the relative wind speed caused by the movement of the conductor (i.e., the aerodynamic damping effect), which can be expressed by the formula: in, The vertical velocity of the conductor. The horizontal velocity, For the torsional angular velocity, Let be the radius of the conductor.

[0042] Specifically, based on the instantaneous wind angle of attack, an aerodynamic coefficient model is established through nonlinear function fitting, where the aerodynamic coefficients include the lift coefficient. drag coefficient and torque coefficient The formula is expressed as: in, , , represents the fitting constant, and N represents the highest order of the fitting polynomial, used to control the nonlinear fitting accuracy of the aerodynamic coefficient model; Indicates instantaneous angle of attack The k-th power.

[0043] In an optional embodiment, the aerodynamic coefficient model can also be constructed by obtaining aerodynamic coefficient datasets under different icing shapes and angles of attack through wind tunnel tests or high-precision CFD simulations. By using deep neural networks to learn the complex nonlinear mapping relationship between the angle of attack and the aerodynamic coefficients, the model can more flexibly capture the high-order nonlinear characteristics of aerodynamics and wake interference effects.

[0044] In an optional embodiment, the aerodynamic coefficient model can also be constructed using a hybrid modeling method that combines an aerodynamic coefficient database with spline interpolation. A high-precision aerodynamic coefficient lookup table covering typical icing sections and a wide angle of attack range is pre-established, and continuous and smooth aerodynamic coefficient values ​​are obtained in real time in actual simulations based on the instantaneous angle of attack through cubic spline interpolation.

[0045] In this embodiment of the invention, step S400, which utilizes Hamilton's principle to establish the coupled dynamic equations of a multi-span conductor-insulator string considering geometric nonlinearity and torsional stiffness, includes the following sub-steps A1 and A2: In A1: The transmission line is discretized into multiple spatial beam elements, and the mass matrix, damping matrix and stiffness matrix of each spatial beam element are derived. Specifically, the specific structure of each matrix is ​​as follows: mass matrix It includes not only the translational mass and rotational inertia on the diagonal, but also the inertial coupling term caused by the eccentricity of the ice covering, which is the term that leads to the mutual excitation of vertical and torsional motion. Stiffness matrix From the elastic stiffness matrix and geometric stiffness matrix composition: .in Related to conductor tension, it is used to describe nonlinear restoring force under large deformation; Damping matrix Constructed using the Rayleigh damping model: To simulate energy dissipation within the structure, where, and This represents the weighting coefficient.

[0046] In A2: Based on the mass matrix, damping matrix, and stiffness matrix, the coupled dynamic equations of multi-span conductor-insulator strings, which include vertical displacement, horizontal displacement, and torsional angle, are established according to Hamilton's principle.

[0047] Specifically, such as Figure 4 The diagram illustrates a system based on Hamilton's principle, incorporating vertical displacement. Horizontal displacement and twist angle The three-degree-of-freedom coupled motion equations, namely the coupled dynamic equations of multi-span conductor-insulator string, are expressed as follows: in, It is a generalized displacement vector.

[0048] In this embodiment of the invention, step S500 involves substituting the locally modified wind speed vector into the coupled dynamic equation of the multi-span conductor-insulator string, solving it in the time domain using an aerodynamic coefficient model, obtaining the conductor galloping trajectory and amplitude, and conducting a risk assessment based on a preset safety threshold, including: In this embodiment of the invention, substituting the locally modified wind speed vector into the coupled dynamic equations of the multi-span conductor-insulator string, and performing time-domain solutions in conjunction with the aerodynamic coefficient model, includes: The instantaneous wind angle of attack and aerodynamic load vector are updated according to the current conductor motion state at each time step; The dynamic equations are solved iteratively using an incremental time integration algorithm to obtain the displacement, velocity, and acceleration of the conductor at each time step. Extract the galloping trajectory during the steady-state phase and calculate the maximum vertical and horizontal galloping amplitudes.

[0049] Specifically, due to aerodynamics and geometric stiffness All these dynamics change over time, and the coupling dynamics equations of multi-span conductor-insulator strings are highly nonlinear. This embodiment uses the incremental Newmark-β time integration method for solution.

[0050] At each time step Inside, execute the following loop: Update the instantaneous angle of attack based on the motion state at the previous moment. and aerodynamic load vector ; Update tangent stiffness matrix ; Solve the dynamic equilibrium equations to obtain the displacement increment at the current moment. ; Update the system's displacement, velocity, and acceleration.

[0051] Specifically, through continuous calculation, the galloping trajectory of the output conductor in the time domain is obtained, the limit cycle characteristics of the trajectory after reaching a steady state are extracted, and the maximum vertical galloping amplitude is calculated. .

[0052] In an optional embodiment, the time-domain solution step can also adopt an implicit time integration strategy based on the generalized-α method. By adjusting the numerical damping parameters, high-frequency numerical noise can be effectively filtered out while ensuring computational stability. This approach is suitable for cases where the stiffness matrix changes drastically in strongly nonlinear, large-deformation galloping simulations, and can better maintain the energy balance and long-term integral stability of the system.

[0053] In an optional embodiment, the time-domain solution step can also adopt a coupled solution method based on explicit central difference method and local time step acceleration. The explicit scheme avoids iterative solution of nonlinear equations, and an adaptive time step is used for conductor segments with different motion states. This significantly improves the computational efficiency of large-scale, multi-span line galloping simulation while ensuring accuracy.

[0054] In this embodiment of the invention, risk assessment based on a preset security threshold includes: Based on the conductor galloping trajectory and amplitude, and combined with the phase-to-phase distance of the transmission line, a safety threshold is set. ; Determine whether the maximum vertical sway amplitude exceeds the safety threshold, i.e., determine... If the value exceeds the limit, it is determined that there is a risk of phase-to-phase flashover, and the system will automatically generate a risk warning signal. The visualization results of the output conductor's galloping trajectory and the corresponding risk assessment conclusions are presented.

[0055] It should be noted that the safety threshold setting is mainly based on the principles of electrical safety distance and engineering margin of transmission lines, with the core basis being the dynamic relationship between phase-to-phase distance and galloping amplitude. Typically, the safety threshold η is set between 0.7 and 0.8, comprehensively considering the swing space of the insulator string, the phase difference of asynchronous galloping of different phase conductors, the electrical strength of the air gap, and the safety margin specified in the operating procedures. Specific values ​​can be dynamically adjusted based on the line voltage level, insulation configuration, historical fault data, and field operating experience to ensure that the minimum distance between conductors during galloping can still withstand system switching overvoltages and lightning impulse voltages, avoiding phase-to-phase flashover or air gap breakdown.

[0056] Example 2, refer to Figure 5 Based on the previous embodiment, this embodiment provides an application example of a nonlinear simulation and prediction method for transmission line galloping driven by micro-topography multi-source data, to verify and illustrate the technical effects of the method.

[0057] This embodiment selects a 220kV transmission line in a typical ice-covered galloping area of ​​the Guizhou power grid as the simulation object to conduct specific galloping simulation and risk assessment. The span section of towers 12-13 crossing a "mountain pass" micro-topography is selected. By analyzing the GIM model of this line, the following parameters are obtained: ① Conductor type: LGJ-400 / 35 (steel-cored aluminum stranded wire); ② Span length. 350m; ③ Conductor diameter 26.8 mm; ④ Unit mass 1.35 kg / m; ⑤ Design phase spacing 6.5m. Icing conditions were set as if the line encountered freezing rain. Icing data was obtained through online monitoring devices: the icing shape was crescent-shaped, the icing thickness was 12mm, and the icing density was 900kg / m³. 3 Initial angle of attack At 40°, the aerodynamic instability characteristics of crescent-shaped icing are most pronounced.

[0058] In the micro-topographic wind field correction calculation, the guide line is located at the pass between two mountains, and the macro background wind speed measured by the meteorological station is... The wind direction is perpendicular to the line. Based on the micro-topography correction model of this invention, the average suspension height of the conductor is 30m, and the surface roughness category is B. The height correction coefficient is calculated accordingly. Based on the DEM elevation data of the mountain pass, and by consulting micro-topographic wind field databases or referring to relevant standards, the topographic acceleration factor at this location is determined. The locally corrected wind speed was calculated to be... It should be noted that if micro-topography correction is not performed and calculations are performed directly using 10 m / s, the dancing motion will often fail to be triggered, leading to the risk of missed detections.

[0059] During the dynamic simulation, the corrected wind speed will be used. Substitute the aerodynamic coefficients of crescent-shaped icing into the three-degree-of-freedom coupled dynamic equations. Set the time step. The total simulation time was 200 seconds. A small random displacement perturbation was applied during the initial phase of the simulation (0-5 seconds) to induce system instability. The simulation output results are as follows: Figure 5 As shown, the transient initiation process occurs from 0 to 60 seconds, during which the conductor absorbs wind energy, and the amplitude gradually increases in a spiral pattern. After t > 100 seconds, the system enters a steady-state limit cycle vibration, at which point the trajectory of the conductor cross-section appears as an ellipse with its major axis tilted. The maximum amplitude is extracted from the steady-state trajectory to obtain the maximum vertical amplitude. Maximum horizontal amplitude Torsion angle amplitude Simulation results show that, under the 3-DOF model, the torsional motion frequency of the conductor is approximately 0.58 Hz, which is very close to the vertical motion frequency of 0.56 Hz, resulting in typical frequency overlap. This leads to the torsional mode exciting a large-amplitude vertical gallop.

[0060] This embodiment sets a safety threshold coefficient for interphase flashover. To account for the swaying of insulator strings and the asynchronous movement of conductors in different phases, the safety distance threshold is determined. Due to the calculated maximum vertical amplitude The system determined that the conductor in question had an extremely high risk of phase-to-phase flashover and immediately issued a red warning signal, advising operators to take emergency measures.

[0061] As can be seen from this embodiment, the method provided by the present invention can combine specific micro-topographic features and multi-source data to accurately quantify the amplitude of the dance, which greatly improves the accuracy of disaster early warning in complex environments compared with traditional uncorrected models.

[0062] Example 3: This example provides a nonlinear simulation and prediction system for transmission line galloping based on micro-topographic multi-source data, including: The digital model building module is used to build a three-dimensional digital twin model of the transmission line based on the acquired multi-source monitoring data of the transmission line; The micro-topography wind field correction module is used to identify the micro-topography features of the transmission line and use the micro-topography correction factor to correct the macro wind speed in the multi-source monitoring data of the transmission line to obtain the local corrected wind speed vector. The aerodynamic coefficient construction module is used to construct aerodynamic coefficient models for the cross-sectional characteristics of icing conductors. The dynamic equation construction module is used to establish coupled dynamic equations for multi-span conductor-insulator strings that take into account geometric nonlinearity and torsional stiffness using Hamilton's principle. The galloping prediction module is used to input the locally modified wind speed vector into the coupled dynamic equation of the multi-span conductor-insulator string, and solve it in the time domain by combining the aerodynamic coefficient model to obtain the conductor galloping trajectory and amplitude, and to conduct risk assessment based on the preset safety threshold.

[0063] It should be noted that the technical solution of the transmission line galloping nonlinear simulation and prediction system driven by micro-topography multi-source data is based on the same concept as the above-mentioned transmission line galloping nonlinear simulation and prediction method driven by micro-topography multi-source data. For details not described in detail in the technical solution of the transmission line galloping nonlinear simulation and prediction system driven by micro-topography multi-source data in this embodiment, please refer to the description of the above-mentioned transmission line galloping nonlinear simulation and prediction method driven by micro-topography multi-source data.

[0064] It should be noted that, as Figure 6 The transmission line galloping nonlinear simulation and prediction system based on micro-topography multi-source data, as shown, adopts a layered modular architecture design, including: multi-source data access layer, modeling and correction layer, core computing engine layer, and application and evaluation layer.

[0065] The multi-source data access layer serves as the system's data entry point, responsible for acquiring heterogeneous data required for simulation from external databases or interfaces. This layer includes a GIM model data module, used to parse GIM files of transmission lines and extract static physical parameters such as tower coordinates, conductor splits, span length, insulator string length and type; a DEM elevation data module, used to load a high-precision digital elevation model of the transmission corridor to obtain topographic and geomorphological feature data along the line; a meteorological monitoring data module, which communicates with micro-weather stations or meteorological bureaus to obtain real-time monitoring values ​​of macroscopic wind speed, wind direction, temperature, and icing thickness in the area where the line is located; and a real-time operating parameter module, which accesses SCADA system data to obtain current operating tension, current load, and other status parameters of the conductors.

[0066] The modeling and correction layer is responsible for transforming the raw data into a computationally achievable physical model and environmental boundary conditions. This layer includes a 3D digital twin modeling module, which automatically generates finite element node and element information for transmission lines and insulator strings based on GIM analysis results, constructing a 3D digital twin model that incorporates geometric nonlinearities. The micro-topography wind field correction module has a built-in topography acceleration factor database, identifies the types of micro-topography crossed by the line based on DEM data, and combines meteorological monitoring data with correction formulas. The local corrected wind speed vector acting on specific traverse units was calculated, solving the problem of inaccurate wind field input under complex terrain.

[0067] The core computing engine layer is the heart of the system, responsible for performing fluid-structure interaction (FSI) calculations. This layer includes a nonlinear aerodynamic calculation module with a built-in database of aerodynamic coefficients for various typical icing sections. Within each time step, it calculates the instantaneous angle of attack based on the instantaneous motion state of the conductor and uses this information to query or interpolate nonlinear lift, drag, and torque. The 3-DOF nonlinear dynamics solution module uses the Newmark-β time integration algorithm to solve the three-degree-of-freedom coupled motion equations involving vertical, horizontal, and torsional directions. This module interacts bidirectionally with the aerodynamic calculation module to achieve iterative solutions for FSI in the time domain.

[0068] The application and evaluation layer is responsible for transforming the calculation results into visualized engineering application indicators. This layer includes a galloping trajectory visualization module, which renders the simulated time-series displacement data into a phase plane trajectory diagram of the conductor cross-section and a three-dimensional spatial galloping morphology diagram, intuitively displaying the vibration initiation process and steady-state limit cycle; a mechanical state inversion module, which utilizes the high-precision characteristics of the simulation model to support inversion functions, that is, based on the displacement or tension data of a small number of monitoring points, it can infer the maximum stress distribution and the location of dangerous points of the entire conductor span, meeting the project's requirements for mechanical state assessment and inversion; and a risk warning release module, which monitors the calculated galloping amplitude in real time. When the predicted vertical or horizontal amplitude causes the phase-to-phase distance to be less than the set safety threshold, it automatically generates alarm signals of different levels and pushes them to the maintenance personnel's terminals.

[0069] This system can be deployed on high-performance computing workstations or cloud servers and supports remote access via a web terminal. The system software architecture uses C++ or Python to develop the core algorithm library and utilizes OpenGL or WebGL technologies to achieve real-time rendering and display of 3D models and motion trajectories.

[0070] The above-mentioned unit modules can be embedded in the processor of the electronic device in hardware form or independent of it, or they can be stored in the memory of the electronic device in software form, so that the processor can call and execute the corresponding operations of the above modules.

[0071] This embodiment also provides an electronic device, which includes a processor, a memory, a communication interface, a display screen, and an input device connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data. The display screen can be a liquid crystal display (LCD) or an e-ink display. The input device can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the device's casing, or an external keyboard, touchpad, or mouse.

[0072] This embodiment also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method proposed in the above embodiments.

[0073] The storage medium proposed in this embodiment belongs to the same inventive concept as the method proposed in the above embodiments. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0074] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory, random access memory, flash memory, hard disk, or optical disk, and includes several instructions to cause an electronic device (which may be a personal computer, server, or network device, etc.) to execute the method of the embodiments of the present invention.

[0075] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A nonlinear simulation and prediction method for transmission line galloping based on multi-source data driven by micro-topography, characterized in that, include: A three-dimensional digital twin model of the transmission line is constructed based on the acquired multi-source monitoring data of the transmission line; Identify the micro-topographic features of the transmission line and use a micro-topographic correction factor to correct the macro-wind speed in the multi-source monitoring data of the transmission line to obtain a locally corrected wind speed vector. An aerodynamic coefficient model was constructed based on the cross-sectional characteristics of the icing conductor. A coupled dynamic equation for multi-span conductor-insulator strings considering geometric nonlinearity and torsional stiffness is established using Hamilton's principle. The locally modified wind speed vector is substituted into the coupled dynamic equation of the multi-span conductor-insulator string, and the time domain solution is performed in combination with the aerodynamic coefficient model to obtain the conductor galloping trajectory and amplitude. A risk assessment is then performed based on a preset safety threshold.

2. The nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data as described in claim 1, characterized in that, The construction of the three-dimensional digital twin model of the transmission line includes: Acquire multi-source monitoring data for transmission lines, including power grid information model data of transmission lines, high-precision digital elevation model data of transmission channels, and meteorological monitoring data; The spatial geometric parameters and physical attributes of the transmission line are extracted from the power grid information model data of the transmission line, and the physical attributes are corrected by combining the meteorological monitoring data. The correction includes at least calculating the total mass per unit length of the icing conductor, the total moment of inertia and the centroidal eccentricity of the icing based on the icing thickness and icing density. Based on the geometric parameters and the corrected physical properties, a structured finite element model of the transmission line is constructed in three-dimensional space. Based on the high-precision digital elevation model data, the elevation of the suspension point of the model is adapted to the terrain to form a three-dimensional digital twin model of the transmission line that reflects the real spatial form and mechanical properties.

3. The nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data as described in claim 2, characterized in that, The method of correcting the macroscopic wind speed in the multi-source monitoring data of the transmission line using a micro-topography correction factor includes: The terrain acceleration factor corresponding to the micro-topography category is determined based on the micro-topography features; The macroscopic reference wind speed is obtained from the monitoring, and the macroscopic wind speed in the multi-source monitoring data of the transmission line is jointly corrected by combining the wind profile height correction coefficient and the terrain acceleration factor. The local corrected wind speed vector acting on the conductor is calculated based on the joint correction results.

4. The nonlinear simulation and prediction method for transmission line galloping based on multi-source data driven by micro-topography as described in claim 3, characterized in that, The construction of the aerodynamic coefficient model includes: Determine the initial angle of attack of the icing conductor cross-section; The instantaneous angle of attack is calculated based on the initial angle of attack and the motion state of the conductor; Based on the instantaneous wind angle of attack, an aerodynamic coefficient model is established by fitting a nonlinear function, wherein the aerodynamic coefficients include lift coefficient, drag coefficient and torque coefficient.

5. The nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data as described in claim 4, characterized in that, The establishment of the coupled dynamic equations for multi-span conductor-insulator strings, considering geometric nonlinearity and torsional stiffness, using Hamilton's principle includes: The transmission line is discretized into multiple spatial beam elements, and the mass matrix, damping matrix and stiffness matrix of each spatial beam element are derived. Based on the aforementioned mass matrix, damping matrix, and stiffness matrix, a coupled dynamic equation for a multi-span conductor-insulator string, including vertical displacement, horizontal displacement, and torsional angle, is established according to Hamilton's principle.

6. The nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data as described in claim 5, characterized in that, The time-domain solution includes: The instantaneous wind angle of attack and aerodynamic load vector are updated according to the current conductor motion state at each time step; The dynamic equations are solved iteratively using an incremental time integration algorithm to obtain the displacement, velocity, and acceleration of the conductor at each time step. Extract the galloping trajectory during the steady-state phase and calculate the maximum vertical and horizontal galloping amplitudes.

7. The nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data as described in claim 6, characterized in that, Also includes: Based on the conductor galloping trajectory and amplitude, a safety threshold is set in conjunction with the phase-to-phase distance of the transmission line; Determine whether the maximum vertical sway amplitude exceeds the safety threshold; if it does, generate a risk warning signal. Output the visualization results of the conductor galloping trajectory and the corresponding risk assessment conclusion.

8. A nonlinear simulation and prediction system for transmission line galloping based on micro-topography multi-source data, employing the nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data as described in any one of claims 1 to 7, characterized in that, include: The digital model building module is used to build a three-dimensional digital twin model of the transmission line based on the acquired multi-source monitoring data of the transmission line; The micro-topography wind field correction module is used to identify the micro-topography features where the transmission line is located, and to correct the macro wind speed in the multi-source monitoring data of the transmission line using the micro-topography correction factor to obtain the local corrected wind speed vector. The aerodynamic coefficient construction module is used to construct aerodynamic coefficient models for the cross-sectional characteristics of icing conductors. The dynamic equation construction module is used to establish coupled dynamic equations for multi-span conductor-insulator strings that take into account geometric nonlinearity and torsional stiffness using Hamilton's principle. The galloping prediction module is used to input the local modified wind speed vector into the coupled dynamic equation of the multi-span conductor-insulator string, combine it with the aerodynamic coefficient model to solve in the time domain, obtain the conductor galloping trajectory and amplitude, and conduct risk assessment based on a preset safety threshold.

9. An electronic device comprising a memory and a processor, characterized in that: The memory is used to store computer-executable instructions, and when the processor executes the computer-executable instructions, it implements the steps of the nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data as described in any one of claims 1 to 7.

10. A computer-readable storage medium having computer-executable instructions stored thereon, characterized in that: When the computer-executable instructions are executed by the processor, they implement the steps of the nonlinear simulation and prediction method for transmission line galloping based on micro-topography multi-source data as described in any one of claims 1 to 7.

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