ニューラルネットワークに基づく電力系統の過渡安定度推定

Abstract

The estimation of power system transient stability is more difficult and great importance because the power system becomes larger and larger. Therefore, the fast stability estimation to contingency faults is demanded in the power system operation. In this paper, the neural network technique is applied for the fast classification of system dynamic security status. A suitable topology for the neural network is developed, and the appropriate training system method and input and output signals are selected. The procedure developed is successfully applied to the IEEJ WEST10-generator system and EAST10-generator system. The data obtained by the energy functions are used for training the neural network.