Research on transmission line simulation wind protection technology based on data analysis and artificial intelligence

Frequent convective weather and typhoons in China's coastal areas often lead to faults and trip events in transmission lines due to strong winds. However, there is a lack of precise measurement methods to reflect the electrical and geometric distance of transmission lines under wind conditions. This paper proposes a simulation wind protection technology method based on data analysis and artificial intelligence. First, LiDAR technology and Arc sag calculation models are used to design a 3D scene of transmission lines. In wind protection studies, a dynamic mechanical balance algorithm is used to simulate the wind deviation calibration of insulator strings in simple environments. For complex environments, a Particle Swarm Optimization-Convolutional Neural Network (PSO-CNN) model is used to predict wind deviation angles under various conditions, resulting in more accurate wind deviation risk assessment. This approach aims to reduce manual workload, lower industry design costs, and enhance the intelligence and standardization level of wind deviation risk assessment, providing strong support for the construction of smart grids.