Assessment and Application of Overhead Transmission Line De-icing Jumping Based on Key Parameters Prediction

Overhead transmission lines operating in heavy ice zones are prone to violent jumping during the de-icing process, which can lead to line breakage, short circuits, and other faults, posing a serious threat to the safety of the power grid. To assess the risk of de-icing jumping and improve the accuracy of prediction, this paper constructs a risk assessment model for overhead transmission line de-icing jumping based on a key parameters prediction method. First, the risk assessment model is established, and the key response parameters are determined, including the dynamic and static longitudinal unbalanced tensions of the conductor, as well as the maximum vertical ice jump heights h<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</inf>, h<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>, h<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</inf> and maximum lateral swing amplitudes s<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</inf>, s<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>, s<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</inf> at three locations on the line. Subsequently, a prediction model is established based on finite element simulation and BP neural network to accurately predict these key parameters. Finally, the effectiveness of the method is evaluated through a case study. The research results indicate that this method can accurately predict the key parameters of transmission line deicing jumping and effectively assess the risk level, providing theoretical support and engineering application references for power grid disaster prevention and mitigation.