Challenges, advances and future trends in AC microgrid protection: With a focus on intelligent learning methods

Increasing power demand, aging distribution systems and concerns towards greenhouse gas emissions have resulted in the increased occurrence of distributed generation (DG) within distribution networks. The conven-tional protection methods designed for passive radial distribution networks may become redundant with large bidirectional power flow and dynamic network topology. Additionally, the anti-islanding protection currently employed limits the benefits of wide-scale DG installation and autonomous operation. The microgrid concept can solve these problems, but several challenges must be overcome before practical implementation. Besides bi-directional power flow, the vast variance between the fault current in grid-connected and autonomous mode and the arbitrary output impedance of the inverter-interfaced DG units in fault conditions and current limiting mode pose a challenge to the protection schemes that use traditional overcurrent protection devices. Many researchers have proposed various techniques, but a robust protection scheme capable of protecting microgrids against different faults for both modes of operation under dynamic network topologies and being financially viable is still to be developed. Hence, the main objective of this paper is to critically review various AC microgrid protection methods proposed in the literature, focusing on analysing the recent protection approaches using modern intelligent techniques. Open research problems and future research trends in AC microgrid protection are also presented in this research.

Automated summary

Increasing power demand, aging distribution systems, and concerns towards greenhouse gas emissions have led to the use of distributed generation (DG) in distribution networks. However, the conventional protection methods may not be suitable for bidirectional power flow and dynamic network topologies. The microgrid concept can address these issues, but challenges must be overcome before practical implementation.