Three-dimensional power grid training simulation method based on virtual reality technology

Abstract

The invention discloses a three-dimensional power grid training simulation method based on a virtual reality technology, and relates to the technical field of power grid training simulation, and the method comprises the following steps: initializing a virtual reality environment, loading a mountainous area power grid three-dimensional model, and generating a power transmission line node; setting training environment parameters; calculating an effective wind speed at each line node according to the terrain gradient; calculating the line galloping amplitude in real time; dynamically rendering a line galloping effect in a VR environment, and visually displaying a dangerous section through color coding; students can deploy anti-galloping devices interactively, and the system updates the damping effect in real time and recalculates the galloping amplitude. The system continuously monitors the safety state, provides a real-time alarm and generates a training evaluation report. According to the invention, a terrain-adaptive galloping amplitude real-time calculation algorithm is introduced, and a virtual reality training system deeply fused with a real geographical environment is constructed, so that simulation and visualization of the galloping behavior of the high-voltage transmission line in a mountainous complex terrain can be realized.

Description

Technical Field

[0001] This invention belongs to the field of power grid training simulation technology, and in particular relates to a three-dimensional power grid training simulation method based on virtual reality technology. Background Technology

[0002] In transmission line operation and maintenance training, simulations of transmission line galloping under wind loads typically employ simplified physical models or pre-set animation sequences, failing to effectively integrate real-world terrain data of the line's route for dynamic and precise correction of wind field and galloping behavior. These methods often presuppose flat terrain or consider only a single wind speed condition, resulting in significant deviations between the simulated line vibration patterns, amplitudes, and distribution of hazardous sections and actual field conditions. This disconnects training content from real-world operating conditions, making it difficult for trainees to directly transfer the knowledge and operational experience gained in virtual environments to complex real-world operation and maintenance scenarios. It also fails to effectively cultivate their crucial skills in accurately identifying galloping risks, assessing their hazards, and developing effective prevention and control strategies in specific geographical environments. Therefore, the following solutions are proposed to address these issues. Summary of the Invention

[0003] The purpose of this invention is to provide a three-dimensional power grid training simulation method based on virtual reality technology. By introducing a terrain-adaptive real-time calculation algorithm for galloping amplitude and constructing a virtual reality training system that is deeply integrated with the real geographical environment, it is possible to simulate and visualize the galloping behavior of high-voltage transmission lines in complex mountainous terrain. This solves the problem that existing virtual reality training methods fail to effectively integrate terrain data, resulting in simulation results that are out of sync with real working conditions and failing to cultivate trainees' ability to accurately identify risks and make intervention decisions.

[0004] To solve the above-mentioned technical problems, the present invention is achieved through the following technical solution:

[0005] This invention relates to a three-dimensional power grid training simulation method based on virtual reality technology. The simulation method includes the following steps:

[0006] Step S1: Virtual Reality Environment Initialization: Initialize the virtual reality environment, load the 3D model of the mountain power grid, and generate transmission line nodes based on real terrain data;

[0007] Step S2, Environmental Parameter Settings: Set training environment parameters, allowing trainees to adjust meteorological conditions, including wind speed and wind direction, through a virtual control panel;

[0008] Step S3, Terrain-Adaptive Wind Field Calculation: Calculate the effective wind speed at each line node based on the terrain gradient to reflect the spatial variation characteristics of the wind field in mountainous areas;

[0009] Step S4, Galloping Amplitude Calculation: Taking into account the terrain slope and the physical characteristics of the line, the galloping amplitude of the line is calculated in real time;

[0010] Step S5, 3D visualization and dynamic rendering: Dynamically render the line dancing effect in a VR environment, and intuitively display dangerous sections through color coding;

[0011] Step S6, Training Interaction and Anti-Dance Device Deployment: Trainees can interactively deploy anti-dance devices, and the system updates the damping effect and recalculates the dance amplitude in real time;

[0012] Step S7, Assessment and Feedback Generation: The system continuously monitors the security status, provides real-time alerts, and generates training assessment reports.

[0013] Furthermore, step S1, the virtual reality environment initialization, specifically includes the following steps:

[0014] Step S11: Initialize the 3D virtual environment using the VR headset and controllers;

[0015] Step S12: Load the 3D model of the power grid, including components such as transmission lines, towers, insulators, and foundations; the transmission lines are discretized into N nodes (N≥100, depending on the line length and accuracy requirements), and the nodes are connected by line segments. Each node i has 3D coordinates (x, y, z). i ,y i ,z i ), where i = 1, 2, ..., N, z i Generated based on high-precision digital elevation model (DEM) data, accurately reflecting the topographic relief of mountainous areas;

[0016] Step S13: Import the physical parameters of the line, including mass per unit length m, conductor diameter D, tension N, length L, and elastic modulus E. These parameters are preloaded from the power grid database and stored as a structured array.

[0017] Furthermore, step S2, setting the environmental parameters, specifically includes the following steps:

[0018] Step S21: Set environmental parameters on the virtual control panel using the VR controller: wind speed v wind Wind direction θ wind (Radians, relative to true north), air density ρ, temperature T; parameters can be adjusted in real time, such as wind speed v. wind The range was set to 0-30 m / s to simulate conditions ranging from calm to large-amplitude vibrations;

[0019] Step S22: The system automatically generates parameters based on preset scenarios (such as typical wind conditions in mountainous areas), or allows trainees to manually input parameters to explore other situations.

[0020] Furthermore, step S3, the terrain-adaptive wind field calculation, specifically includes the following steps:

[0021] Step S31: For each node i, extract the terrain height h(x) from the DEM data. i ,y i ), and calculate the terrain gradient. The gradient is calculated using the central difference method, and the specific formula is as follows:

[0022]

[0023] In the formula, is the gradient symbol, representing a vector; h is the terrain height function, representing the ground elevation at coordinates (x, y); i is the index of the discrete node of the transmission line; x i Let y be the horizontal coordinate of node i in 3D space; i x is the vertical coordinate of node i in three-dimensional space; i+1 ,x i-1 y and y' are the horizontal coordinates of the next and previous adjacent nodes of node i, respectively; i+1 ,y i-1 Δx and Δy are the vertical coordinates of the next and previous adjacent nodes of node i, respectively; Δx is the grid spacing or resolution of the digital elevation model (DEM) data in the x-direction; Δy is the grid spacing or resolution of the digital elevation model (DEM) data in the y-direction.

[0024] Step S32: Calculate the effective wind speed v at node i. eff (i), the formula is:

[0025]

[0026] In the formula, v eff (i) represents the effective wind speed calculated at node i after terrain correction; v wind The background wind speed is set by the user or generated by the system; k1 is the terrain influence constant. The terrain gradient vector at node i The modulus θ represents the steepness of the terrain at that point; wind θ is the ambient wind direction angle, set by the user or generated by the system. line (i) is the tangent direction angle of the transmission line at node i; when |θ wind -θ line (i)|>π / 2, then the cos value is 0, indicating that the wind has the greatest impact when it is perpendicular to the line.

[0027] Furthermore, step S4, the calculation of the dancing amplitude, specifically includes the following steps:

[0028] Step S41: Calculate the first natural frequency f1 of the line, which is used to characterize the main vibration mode of galloping. The calculation formula is:

[0029]

[0030] In the formula, f1 is the first natural frequency of the transmission line, l is the total length of the transmission line span, N is the tension borne by the transmission conductor, and m is the mass per unit length of the transmission conductor.

[0031] Step S42: For each node i, calculate the dancing amplitude A(i), the specific formula is as follows:

[0032]

[0033] In the formula, A(i) is the transmission line galloping amplitude calculated at node i; C0 is the baseline coefficient used to match the theoretical model with actual observation data; ρ is the air density; v eff (i) is the effective wind speed calculated at node i; D is the diameter of the transmission conductor; m is the mass per unit length of the transmission conductor; f1 is the first natural frequency of the transmission line; α is the slope correction factor, used to quantify the additional effect of the line's own slope on galloping. Let h be the absolute value of the directional derivative of the terrain height h along the arc length s of the transmission line at node i, i.e., the slope of the line along its direction.

[0034] Step S43: Amplitude A(i) is refreshed according to a set period to ensure real-time performance (VR frame rate ≥ 90Hz, but amplitude calculation is performed asynchronously to avoid stuttering).

[0035] Furthermore, step S5, 3D visualization and dynamic rendering, specifically includes the following steps:

[0036] Step S51: In the VR environment, dynamically adjust the geometry of the line based on the calculated dancing amplitude A(i); for each node i, add an offset in the direction perpendicular to the line (defined by the line tangent and normal vector):

[0037] Offset = A(i) × sin(2πf1t);

[0038] In the formula, t is the system time;

[0039] Step S52: Use shader technology to achieve smooth deformation of the line and add vibration animation (such as wave propagation effect); at the same time, display real-time data in the VR interface: amplitude value of each node, safety threshold (for example, when A(i)>0.5 meters, the dangerous section is highlighted), and provide color coding (green for safe, red for dangerous).

[0040] Furthermore, step S6, training interaction and deployment of the anti-fighting device, specifically includes the following steps:

[0041] Step S61: The trainee interacts with the scene using the VR controller: grabbing and placing anti-dash devices (such as dampers or spacers); when a damper is deployed on a line segment, the system updates the damping ratio ζ of that segment; ζ is calculated based on the number and type of dampers.

[0042] ζ = ζ0 + n × Δζ;

[0043] In the formula, ζ0 is the basic damping ratio, n is the number of dampers, and Δζ is the contribution of a single damper.

[0044] Step S62: After deployment, recalculate the waving amplitude and modify the formula in step S42 as follows:

[0045]

[0046] Students observe the amplitude changes and learn the optimal placement of the damper (such as the high amplitude node).

[0047] Furthermore, step S7, evaluation and feedback generation, specifically includes the following steps:

[0048] Step S71: The system continuously monitors the amplitude of the dance. If A(i) exceeds the safety threshold (e.g., 1.0 meter), an auditory alarm (e.g., a buzzer) and a visual warning (flashing red light) are triggered.

[0049] Step S72: Record the response time of the trainee's operation and the effectiveness of the deployment device (amplitude reduction percentage); after the training, generate a report including the risk identification accuracy rate, operation efficiency score, and provide improvement suggestions (such as "deploying a damper at node X can reduce amplitude by 20%").

[0050] The present invention has the following beneficial effects:

[0051] 1. This invention integrates high-precision terrain data and introduces a terrain-adaptive wind field and galloping calculation model, which can dynamically adjust the intensity and direction of the wind field in real time according to the micro-terrain undulations of the route location, thereby generating a galloping phenomenon that highly matches the real geographical environment. This allows trainees to observe the line movement pattern, amplitude changes, and distribution of dangerous sections in a virtual reality environment. This simulation experience transforms training from an abstract demonstration of principles into a deep understanding of specific working conditions, enhancing trainees' understanding of the dynamic behavior of lines and their risks in complex environments.

[0052] 2. This invention transforms abstract physical quantities into intuitive visual and auditory signals through a built-in real-time calculation and visualization early warning mechanism. The system continuously calculates the amplitude of the dance in each line segment and compares it with preset safety thresholds. Once an over-limit situation is detected, a multimodal alarm is immediately triggered. This process allows trainees to clearly observe the formation, evolution, and spatial distribution of risks in a virtual space before the consequences of an accident occur, thereby shifting the training focus from passively recognizing the consequences of accidents to actively identifying risks. Through repeated training, trainees can systematically develop a keen insight into the early signs of dance and the ability to make rapid judgments based on dynamic risk situations.

[0053] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0054] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. 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.

[0055] Figure 1 This is a flowchart illustrating a three-dimensional power grid training simulation method based on virtual reality technology according to the present invention. Detailed Implementation

[0056] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] Please see Figure 1 As shown, this invention is a three-dimensional power grid training simulation method based on virtual reality technology, comprising the following steps:

[0058] Step S1: Virtual Reality Environment Initialization: Initialize the virtual reality environment, load the 3D model of the mountain power grid, and generate transmission line nodes based on real terrain data;

[0059] Step S1, virtual reality environment initialization specifically includes the following steps:

[0060] Step S11: Initialize the 3D virtual environment using the VR headset and controllers;

[0061] Step S12: Load the 3D model of the power grid, including components such as transmission lines, towers, insulators, and foundations; the transmission lines are discretized into N nodes (N≥100, depending on the line length and accuracy requirements), and the nodes are connected by line segments. Each node i has 3D coordinates (x, y, z). i ,y i ,z i ), where i = 1, 2, ..., N, z i Generated based on high-precision digital elevation model (DEM) data, accurately reflecting the topographic relief of mountainous areas;

[0062] Step S13: Import the physical parameters of the line, including mass per unit length m, conductor diameter D, tension N, length L, and elastic modulus E. These parameters are preloaded from the power grid database and stored as a structured array.

[0063] Step S2, Environmental Parameter Settings: Set training environment parameters, allowing trainees to adjust meteorological conditions, including wind speed and wind direction, through a virtual control panel;

[0064] Step S2, setting environment parameters specifically includes the following steps:

[0065] Step S21: Set environmental parameters on the virtual control panel using the VR controller: wind speed v wind Wind direction θ wind (Radians, relative to true north), air density ρ, temperature T; parameters can be adjusted in real time, such as wind speed v. wind The range was set to 0-30 m / s to simulate conditions ranging from calm to large-amplitude vibrations;

[0066] Step S22: The system automatically generates parameters based on preset scenarios (such as typical wind conditions in mountainous areas), or allows trainees to manually input parameters to explore other situations.

[0067] Step S3, Terrain-Adaptive Wind Field Calculation: Calculate the effective wind speed at each line node based on the terrain gradient to reflect the spatial variation characteristics of the wind field in mountainous areas;

[0068] Step S3, terrain-adaptive wind field calculation, specifically includes the following steps:

[0069] Step S31: For each node i, extract the terrain height h(x) from the DEM data. i ,y i ), and calculate the terrain gradient. The gradient is calculated using the central difference method, and the specific formula is as follows:

[0070]

[0071] In the formula, is the gradient symbol, representing a vector; h is the terrain height function, representing the ground elevation at coordinates (x, y); i is the index of the discrete node of the transmission line; x i Let y be the horizontal coordinate of node i in 3D space; i x is the vertical coordinate of node i in three-dimensional space; i+1 ,x i-1 y and y' are the horizontal coordinates of the next and previous adjacent nodes of node i, respectively; i+1 ,y i-1 Δx and Δy are the vertical coordinates of the next and previous adjacent nodes of node i, respectively; Δx is the grid spacing or resolution of the digital elevation model (DEM) data in the x-direction; Δy is the grid spacing or resolution of the digital elevation model (DEM) data in the y-direction.

[0072] Step S32: Calculate the effective wind speed v at node i. eff (i), the formula is:

[0073]

[0074] In the formula, v eff (i) represents the effective wind speed calculated at node i after terrain correction; v wind The background wind speed is set by the user or generated by the system; k1 is the terrain influence constant. The terrain gradient vector at node i The modulus θ represents the steepness of the terrain at that point; wind θ is the ambient wind direction angle, set by the user or generated by the system. line (i) is the tangent direction angle of the transmission line at node i; when |θ wind -θ line (i)|>π / 2, then the cos value is 0, indicating that the wind has the greatest impact when it is perpendicular to the line.

[0075] Step S4, Galloping Amplitude Calculation: Taking into account the terrain slope and the physical characteristics of the line, the galloping amplitude of the line is calculated in real time;

[0076] Step S4, the calculation of the amplitude of the dance, specifically includes the following steps:

[0077] Step S41: Calculate the first natural frequency f1 of the line, which is used to characterize the main vibration mode of galloping. The calculation formula is:

[0078]

[0079] In the formula, f1 is the first natural frequency of the transmission line, L is the total length of the transmission line span, N is the tension borne by the transmission conductor, and m is the mass per unit length of the transmission conductor.

[0080] Step S42: For each node i, calculate the dancing amplitude A(i), the specific formula is as follows:

[0081]

[0082] In the formula, A(i) is the transmission line galloping amplitude calculated at node i; C0 is the baseline coefficient used to match the theoretical model with actual observation data; ρ is the air density; v eff (i) is the effective wind speed calculated at node i; D is the diameter of the transmission conductor; m is the mass per unit length of the transmission conductor; f1 is the first natural frequency of the transmission line; α is the slope correction factor, used to quantify the additional effect of the line's own slope on galloping. Let h be the absolute value of the directional derivative of the terrain height h along the arc length s of the transmission line at node i, i.e., the slope of the line along its direction.

[0083] Step S43: Amplitude A(i) is refreshed according to a set period to ensure real-time performance (VR frame rate ≥ 90Hz, but amplitude calculation is performed asynchronously to avoid stuttering).

[0084] Step S5, 3D visualization and dynamic rendering: Dynamically render the line dancing effect in a VR environment, and intuitively display dangerous sections through color coding;

[0085] Step S5, 3D visualization and dynamic rendering specifically includes the following steps:

[0086] Step S51: In the VR environment, dynamically adjust the geometry of the line based on the calculated dancing amplitude A(i); for each node i, add an offset in the direction perpendicular to the line (defined by the line tangent and normal vector):

[0087] Offset = A(i) × sin(2πf1t);

[0088] In the formula, t is the system time;

[0089] Step S52: Use shader technology to achieve smooth deformation of the line and add vibration animation (such as wave propagation effect); at the same time, display real-time data in the VR interface: amplitude value of each node, safety threshold (for example, when A(i)>0.5 meters, the dangerous section is highlighted), and provide color coding (green for safe, red for dangerous).

[0090] Step S6, Training Interaction and Anti-Dance Device Deployment: Trainees can interactively deploy anti-dance devices, and the system updates the damping effect and recalculates the dance amplitude in real time;

[0091] Step S6, Training Interaction and Anti-Fighting Device Deployment, specifically includes the following steps:

[0092] Step S61: The trainee interacts with the scene using the VR controller: grabbing and placing anti-dash devices (such as dampers or spacers); when a damper is deployed on a line segment, the system updates the damping ratio ζ of that segment; ζ is calculated based on the number and type of dampers.

[0093] ζ = ζ0 + n × Δζ;

[0094] In the formula, ζ t The base damping ratio is given by n, the number of dampers is given by Δζ, and the contribution of a single damper is given by Δζ.

[0095] Step S62: After deployment, recalculate the waving amplitude and modify the formula in step S42 as follows:

[0096]

[0097] Students observe the amplitude changes and learn the optimal placement of the damper (such as the high amplitude node).

[0098] Step S7, Assessment and Feedback Generation: The system continuously monitors the security status, provides real-time alerts, and generates training assessment reports.

[0099] Step S7, Evaluation and Feedback Generation, specifically includes the following steps:

[0100] Step S71: The system continuously monitors the amplitude of the dance. If A(i) exceeds the safety threshold (e.g., 1.0 meter), an auditory alarm (e.g., a buzzer) and a visual warning (flashing red light) are triggered.

[0101] Step S72: Record the response time of the trainee's operation and the effectiveness of the deployment device (amplitude reduction percentage); after the training, generate a report including the risk identification accuracy rate, operation efficiency score, and provide improvement suggestions (such as "deploying a damper at node X can reduce amplitude by 20%").

[0102] One specific application of this embodiment is:

[0103] Scene setup:

[0104] Training location: Towers 23-24 of a 500kV double-circuit transmission line in a mountainous area;

[0105] Line parameters: Line length: L = 350m; Conductor type: LGJ-500 / 45; Mass per unit length: m = 2.05kg / m; Conductor diameter: D = 0.032m; Operating tension: T = 65000N; Elastic modulus: E = 73GPa;

[0106] Topographic features: This section of the route crosses a V-shaped valley with an elevation difference of 85 meters, and the DEM data resolution is 10 meters;

[0107] Meteorological conditions: Simulating strong winter winds, wind speed v wind =18m / s, wind direction θ wind =π / 4 (Northeast wind).

[0108] Implementation steps:

[0109] Step S1: Virtual Reality Environment Initialization

[0110] The training environment was initialized using the HTC Vive Pro 2 VR system, and the 3D model of tower section 23-24 was loaded; the 350-meter line was discretized into N=140 nodes, with a node spacing Δs=2.5 meters;

[0111] The three-dimensional coordinates of each node i are generated based on actual survey data: x i y is the arc length coordinate along the route; i The lateral offset of the line centerline; z i =h(x i ,y i The elevation is the terrain height obtained by interpolation from 10-meter resolution DEM data.

[0112] Mark key feature points in the VR scene: Elevation of Tower Base #23 (z) 23 =1245 meters, elevation of tower base z (24#) 24 = 1160 meters.

[0113] Step S2, Environment Parameter Settings

[0114] Students set parameters using VR controllers on a virtual console:

[0115] Wind speed: v wind =18m / s; Wind direction: θ wind =π / 4 = 0.785 rad; Air density: ρ = 1.18 kg / m³ 3 (Corresponding to an altitude of 1,200 meters and a temperature of -5℃); Time step: Δt = 0.05s (for real-time updates); The system automatically records the parameter setting timestamp for subsequent training and evaluation.

[0116] Step S3: Terrain-Adaptive Wind Field Calculation

[0117] For node i = 70 (located near the lowest point of the valley), calculate the terrain gradient:

[0118] Extracting the elevation of adjacent nodes: z 69 = 1178.3 meters, z 71 = 1181.6 meters;

[0119] Calculate gradient components:

[0120]

[0121] Gradient magnitude:

[0122] Calculate the line direction at node 70:

[0123] Node 69 coordinates: (x 69 ,y 69 = (172.5, -3.2);

[0124] Node 71 coordinates: (x 71 ,y 71 = (177.5, -2.8);

[0125] Line direction angle:

[0126]

[0127] Calculate the effective wind speed:

[0128] v eff (70)=18×(1+0.2×0.74)×cos(0.7850.0797)=18×1.148×cos(0.7053)=20.664×0.761=15.725m / s;

[0129] Step S4: Calculation of the amplitude of the dance

[0130] Calculate the first natural frequency of the line:

[0131]

[0132] Calculate the gradient along the arc length at node 70:

[0133] Elevation of adjacent nodes: z 69 = 1178.3 meters, z 71 = 1181.6 meters;

[0134] Planar distance: rice;

[0135] slope:

[0136] Calculate the amplitude of the dance (C0 = 0.1, α = 0.5):

[0137] rice.

[0138] Step S5: 3D Visualization and Dynamic Rendering

[0139] In the VR scene, the wire at node 70 experiences periodic offset in the direction perpendicular to the line:

[0140] Offset = 0.238 × sin(2π × 0.254 × t) meters, where t is the system time;

[0141] Vibration frequency: 0.254 Hz, period approximately 3.94 seconds;

[0142] Visual presentation: The conductor is orange (amplitude 0.238 meters, approaching the warning threshold of 0.25 meters); Real-time display panel: Node 70 amplitude 0.238 meters, frequency 0.254 Hz; The vibration animation uses a sine wave superimposed with attenuation effect to simulate a real dancing form.

[0143] Step S6: Training Interaction and Deployment of Anti-Fighting Devices

[0144] Trainees use VR controllers to grab the anti-dance damper (8kg, damping coefficient c=150N·s / m).

[0145] Deploy the damper at node 70:

[0146] Basic damping ratio: ζ0 = 0.01; contribution of a single damper: Δζ = 0.008; updated damping ratio: ζ = 0.01 + 1 × 0.008 = 0.018;

[0147] Recalculate the dancing amplitude of node 70:

[0148]

[0149] Amplitude reduction: ΔA = 0.238 + 0.234 = 0.004 meters (reduction of 1.68%).

[0150] Step S7: Evaluation and Feedback Generation

[0151] The system monitored the amplitude change after deployment: initial amplitude: 0.238 meters; amplitude after deployment: 0.234 meters; reduction rate: 1.68%;

[0152] Training report generated: Risk identification: Trainee correctly identified high-risk galloping area (node ​​70); Operation evaluation: Deployment location was accurate, but the effect of a single damper was limited; Improvement suggestion: "Deploy 3-4 dampers in the node 68-72 interval, which is expected to further reduce the amplitude by 15-20%"; Safety score: 85 / 100 (Accurate identification but solution needs optimization).

[0153] In summary, this embodiment demonstrates the complete process of applying the terrain-adaptive dancing algorithm under specific mountainous route conditions. Through terrain data integration and physical parameter calculation, dancing simulation was achieved, providing trainees with a targeted training experience.

[0154] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0155] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A three-dimensional power grid training simulation method based on virtual reality technology, characterized in that, The simulation method specifically comprises the following steps: Step S1, virtual reality environment initialization: initialize the virtual reality environment, load the three-dimensional model of the mountainous power grid, and generate the power transmission line nodes according to the real terrain data; Step S2, environment parameter setting: set the training environment parameters, and allow the trainees to adjust the meteorological conditions including wind speed and wind direction through a virtual control panel; Step S3, terrain adaptive wind field calculation: calculate the effective wind speed at each line node according to the terrain gradient, and reflect the spatial variation characteristics of the mountainous wind field; Step S4, calculation of dance amplitude: comprehensively consider the terrain slope and the physical characteristics of the line, and calculate the line dance amplitude in real time; Step S5, three-dimensional visualization and dynamic rendering: dynamically render the line dance effect in the VR environment, and intuitively display the dangerous section through color coding; Step S6, training interaction and anti-dance device deployment: the trainees can interactively deploy the anti-dance device, and the system updates the damping effect in real time and recalculates the dance amplitude; Step S7, evaluation and feedback generation: the system continuously monitors the safety state, provides real-time alarms, and generates a training evaluation report. 2.The three-dimensional electric network training simulation method based on virtual reality technology according to claim 1, characterized in that, The step S1, virtual reality environment initialization specifically comprises the following steps: Step S11: initialize the three-dimensional virtual environment using a VR headset and a handle controller; Step S12: load the power grid three-dimensional model, including components such as transmission lines, towers, insulators, and foundations; the transmission lines are discretized into N nodes, connected by line segments between nodes, each node i has three-dimensional coordinates (x i ,y i ,z i ), where i = 1, 2,..., N, z i Based on high-precision digital elevation model DEM data generation, accurately reflects the ups and downs of the terrain in mountainous areas; Step S13: import the physical parameters of the line, including the unit length mass m, the wire diameter D, the tension N, the length L, and the elastic modulus E, which are preloaded from the power grid database and stored as a structured array. 3.The three-dimensional electric network training simulation method based on virtual reality technology according to claim 1, characterized in that, The step S2, environment parameter setting specifically comprises the following steps: Step S21: Set the environmental parameters: wind speed v wind , wind direction θ wind , air density p, temperature T on the virtual control panel through the VR handle; simulate conditions from calm to large amplitude vibration by adjusting the parameters in real time; Step S22: the system automatically generates parameters according to the preset scene, or allows the trainees to manually input to explore other conditions.

4. The three-dimensional electric network training simulation method based on virtual reality technology according to claim 1, characterized in that, The step S3, terrain adaptive wind field calculation specifically comprises the following steps: Step S31: For each node i, extract the terrain height h(x i ,y i ) from the DEM data and calculate the terrain gradient The gradient is calculated using the central difference method, with the specific formula being: In the formula, is the gradient symbol, representing a vector; h is the terrain height function, representing the ground elevation at coordinates (x, y); i is the index of the discrete node of the transmission line; x i Let y be the horizontal coordinate of node i in 3D space; i x is the vertical coordinate of node i in three-dimensional space; i+1 ,x i-1 y and y' are the horizontal coordinates of the next and previous adjacent nodes of node i, respectively; i+1 ,y i-1 Δx and Δy are the vertical coordinates of the next and previous adjacent nodes of node i, respectively; Δx is the grid spacing or resolution of the digital elevation model data in the x-direction; Δy is the grid spacing or resolution of the digital elevation model data in the y-direction. Step S32: Calculate the effective wind speed v at the computing node i eff (i) with the formula: where v eff (i) is the terrain-corrected effective wind speed at node i; v wind is the background wind speed set by user or generated by system; k1 is terrain influence constant; is the terrain gradient vector at node i , indicating the steepness of the terrain at the point; θ wind is the background wind direction angle set by user or generated by system; θ line (i) is the tangent direction angle of the transmission line at node i; when |θ wind -θ line (i)|>π / 2, the cos value is 0, indicating that the wind is perpendicular to the line when the impact is the largest.

5. The three-dimensional electric network training simulation method based on virtual reality technology according to claim 1, characterized in that, The step S4, dance amplitude calculation specifically comprises the following steps: Step S41: calculate the first natural frequency f1 of the line, which is used to represent the main vibration mode of the dance, and the calculation formula is: In the formula, f1 is the first order natural frequency of the transmission line, L is the total length of the transmission line span, N is the tension borne by the transmission conductor, and m is the mass per unit length of the transmission conductor; Step S42: for each node i, calculate the dance amplitude A(i), and the specific formula is: where A(i) is the calculated galloping amplitude of the transmission line at node i; Co is a reference coefficient to match the theoretical model with the actual observation data; p is the air density; v eff (i) is the calculated effective wind speed at node i; D is the diameter of the transmission conductor; m is the mass per unit length of the transmission conductor; f1 is the first order natural frequency of the transmission line; a is a slope correction coefficient to quantify the additional influence of the line's own slope on galloping; is the absolute value of the derivative of the terrain height h with respect to the arc length s of the transmission line at node i, i.e., the slope of the line along the strike. Step S43: the amplitude A(i) is refreshed at a set period to ensure real-time performance.

6. The three-dimensional electric network training simulation method based on virtual reality technology according to claim 1, characterized in that, The step S5, three-dimensional visualization and dynamic rendering specifically comprises the following steps: Step S51: in the VR environment, dynamically adjust the geometry of the line according to the calculated dance amplitude A(i); for each node i, add an offset in the direction perpendicular to the line: Offset = A(i) x sin(2πf1t); In the formula, t is the system time; Step S52: use the shader technology to realize the smooth deformation of the line, and add the vibration animation; at the same time, display the real-time data in the VR interface: the amplitude value of each node, the safety threshold, and provide color coding.

7. The three-dimensional electric network training simulation method based on virtual reality technology according to claim 1, characterized in that, The step S6, training interaction and anti-dance device deployment specifically comprises the following steps: Step S61 : The student uses the VR handle to interact with the scene: grab and place the anti-dancing device; when the damper is deployed on the segment, the system updates the damping ratio ζ of the segment; the calculation of ζ is based on the number and type of dampers: ζ = ζ0 + n x Δζ; where ζ t is the base damping ratio, n is the number of dampers, and Δζ is the contribution of an individual damper. Step S62: After deployment, recalculate the dance amplitude, modify the formula in step S42: The student observes the amplitude change and learns the optimal placement of the damper. 8.The three-dimensional electric network training simulation method based on virtual reality technology of claim 1, wherein, The step S7, the evaluation and feedback generation specifically comprises the following steps: Step S71 : The system continuously monitors the dance amplitude, and if A(i) exceeds the safety threshold, an audible alarm and visual warning are triggered; Step S72: Record the response time of the student's operation, the effectiveness of the device deployment; generate a report after the training, including risk identification accuracy, operation efficiency score, and provide improvement suggestions.

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