<title>Neural network approach to power system security</title>

Abstract

A neural network approach to power system's static security analysis Is presented. This security analysis includes both security assessment and enhancement. For security assessment, a three-layer feedlorward network has been developed for a small 5-bus system. This network represents the nonlinear nature of the power system accurately enough to identify severe security violations. The momentum method was used to train the network. For security control(enhancement) of power systems, a recurrent network approach Is proposed to replace the existing expert system technique. Given an insecure operating state, the proposed approach will produce the operating points which result in a secure operation of the system. The preliminary results Indicate that neural network approach (given neural network hardware availability) can be used for on-line security analysis in a power system's control center enviroment.