Artificial neural networks in power system restoration

Abstract

Power system restoration (PSR) has been a subject of study for many years. Many techniques were proposed to solve the limitations of the predetermined restoration guidelines and procedures used by a majority of system operators to restore a system following the occurrence of a wide area disturbance. This paper discusses limitations encountered in some currently used PSR techniques and a proposed improvement based on artificial neural networks (ANNs). The proposed scheme is tested on a 162-bus transmission system and compared with a breadth-search restoration scheme. The results indicate that the use of ANN in power system restoration is a feasible option that should be considered for real-time applications.