Fault Detection and Classification to Design a Protection Scheme for Utility Grid with High Penetration of Solar Energy – Review

Abstract

The speed of deployment of solar PV (PV) systems into the modern utility grid has altered the operational nature of electrical power systems, and added new challenges to protection engineering. The effectiveness of traditional protection schemes is affected by utility grid with high solar energy penetration, which has bidirectional power flow, low fault current contribution of the inverter, intermittent generation, and dynamically changing operating conditions. Therefore, the development of the intelligent fault detection and fault classification techniques is becoming indispensable for reliable, selective and safe grid operation. In this review, a detailed study of the current fault detection techniques, utility grid protection methods, and artificial intelligence based fault classification methods for high solar penetration utility grid is presented. The conventional relay protection methods are reviewed and compared with advanced signal processing methods, adaptive protection methods, communication based protection methods and the method of machine learning and deep learning. The review shows that intelligent, adaptive, and communication assisted protection architectures offer much greater improvement in fault detection accuracy, relay coordination, and system reliability, making them suitable for next generation renewable integrated utility grids.