A Novel LSTM for Predicting Transmission Line Faults Under Ice Disasters

During severe ice disasters, the excessive buildup of ice can cause transmission line failures, greatly undermining the reliability of the power system. This paper investigates the mechanism by which ice disasters affect transmission lines and proposes a prediction method for transmission line fault probability under ice disasters, referred to as MFFA-LSTM. This method plays a key role in addressing the resilience issues of power systems. Through two sets of simulation experiments, it has been verified that the proposed method offers faster computational speed compared to traditional model-driven approaches for calculating line fault rates, while also demonstrating superior prediction accuracy over other LSTM variants.