A prediction method of electric power damage by typhoons in Kagoshima via GMDH and NN

Author

Takata, Hitoshi ; Yanase, Mitsnshi ; Waki, Toshihiko ; Hachino, Tomohiro

Author_Institution

Dept. of Electr. & Electron. Eng., Kagoshima Univ., Japan

Volume

4

fYear

2002

fDate

5-7 Aug. 2002

Firstpage

2424

Abstract

Kagoshima Prefecture has suffered 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 GMDH and NN (neural networks). 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.

Keywords

disasters; forecasting theory; neural nets; power system analysis computing; power system restoration; storms; GMDH; Japan; Kagoshima Prefecture; NN; distribution lines; distribution poles; electricity supply restoration; natural disasters; neural networks; power systems; typhoons; weather forecasts; Meteorology; Neural networks; Power engineering and energy; Power system restoration; Prediction methods; Storms; Tropical cyclones; Typhoons; Weather forecasting; Wind speed;

fLanguage

English

Publisher

ieee

Conference_Titel

SICE 2002. Proceedings of the 41st SICE Annual Conference

Print_ISBN

0-7803-7631-5

Type

conf

DOI

10.1109/SICE.2002.1195790

Filename

1195790