Probabilistic Forecasting of Transmission Line Damage and Tower Collapse from Storm Disaster
A probability forecasting model of transmission line broken and collapsed from storm disaster based on the Extreme Learning Machine(ELM) and Generalized Extreme Value(GEV) distribution is proposed.Facing the extreme wind speed,the ELM is first used to forecast the variational real-time wind speed.Subsequently,considering the variational real-time wind loads are the extreme probability events,the GEV is then employed to fit the wind loads on both transmission lines and towers.Based on the proposed model,probabilities of transmission line damage and tower collapse can be calculated.The validity and accuracy of the proposed model is verified by comparing the numerical results given by the model to the historical data of a real transmission line.