Real-time critical clearing time estimation by considering contingency conditions

Abstract

This paper presents an approach called adaptive neuro-fuzzy inference system for the transient stability assessment by considering contingency conditions of networks. The contingency condition herein means a case of transmission outage and network configuration change. In addition, in this study all significant dynamic parameters of a power system (e.g. machine models, excitation systems, turbine governors, and load characteristic etc.) are considered for the estimation. We use the critical clearing time for the transient stability index. The 9-bus IEEE is applied for the power dynamic simulation. Finally, this study shows that the adaptive neuro-fuzzy inference system can be applied with the real-time critical clearing time estimation subject to contingency conditions and some parameters affecting the system's dynamic behavior are taken into account.