Abstract
Wind deflection flashover is one of the important factors affecting the normal operation of transmission lines. It is important to study the risk assessment of wind deflection flashes on transmission lines for the stable operation of power systems. In this paper, we considered the influence of wind speed, wind direction, span and height difference on the wind deflection flashes of transmission lines in a given interval. The rigid straight bar method was initially used to establish the wind deflection angle calculation model of transmission lines. Also, the wind deflection angle under various working conditions was calculated as the data base, followed by predicting the wind deflection angle based on BP neural network algorithm, making super-reference adjustment and optimizing the accuracy of the algorithm. Meanwhile, considering the climatic conditions such as rainfall, humidity and terrain, an analytic hierarchy process(AHP)-entropy combination method was used to calculate the wind deflection discharge probability, assessing the line safety level according to the risk occurrence rate. Finally, a risk level assessment and early warning model was established.
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