エネルギー関数を用いたニューラルネットワークによる電力系統過渡安定度推定

Abstract

Estimation of power system transient stability is more difficult and great importance because the power system becomes larger and larger. Therefore, fast stability to contingency faults is demanded in power system operation. In this paper the neural networks technique is applied for fast classification of system dynamic security status. A suitable topology for the neural network is developed, and the appropriate training method and input and output signals are selected. The procedure developed is successfully applied to the IEEE 10-generator 39-bus test system. Data obtained by Energy Functions are used for training the neural network.