Online Early Warning Model of Windage Yaw Discharge on Transmission Lines Based on Monte Carlo Random Sampling.

Windage yaw discharge tripping is one of the main causes of power grid operation failure. Due to the high cost of windage yaw discharge prevention measures, the use of meteorological information for early warning of transmission line fault risk has become an important means to improve the reliability of power grid operation. Therefore, this paper proposes a windage yaw discharge early warning method for transmission lines based on weather forecast parameter wind direction and wind speed data. Firstly, according to the wind level and wind direction of the weather forecast, taking into account the error range of the forecast, the wind speed and wind direction values are randomly sampled by Monte Carlo, and then the wind deflection angle of the insulator string is calculated by the finite element method. The minimum air gap of the conductor tower is calculated according to the parameters of the transmission tower and the insulator string, and the minimum air gap is corrected by introducing the rainfall correction coefficient. Finally, the wind deflection tripping probability is calculated by repeatedly sampling the wind speed and wind direction data. Finally, the effectiveness of the proposed windage yaw discharge early warning method is verified by an example analysis.