A Prediction Method of Electric Power Damage by Typhoons in Kagoshima via the Second-order Polynomial Model and NN

Kagoshima Prefecture has been suffering from natural disasters by typhoons repeatedly. They hit power systems very badly and sometimes cut off electricity. To ensure the rapid restoration of electricity supply, one needs to predict the amount of damage by typhoon accurately. This paper proposes its prediction method by using the GA (Genetic Algorithm), a polynomial regression model, and NN (Neural Networks). The track of typhoon is evaluated from Gaussian function made by the GA. A predictor consists of the second-order polynomial regressor at the first stage and the NN at the second stage. This method enables us to predict the number of damaged distribution poles and lines from weather forecasts of typhoon. Effectiveness of the method is assured by applying it to the actual data.