Decentralized Frequency Control for an Isolated Microgrid using Nature Inspired Algorithms

This paper focuses on developing a decentralized control scheme for a microgrid (MG) to mitigate varying load perturbations. The proposed microgrid system consists of various independent generation systems, including solar, wind, a diesel engine generator, a fuel cell, a battery energy storage, an aqua electrolyzer, and a flywheel. A proportion-integral control scheme has been deployed for controlling each of the sources independently as all sources have different characteristics. The parameters (Kp and Ki) of each of the controller were tuned by three different nature-inspired algorithms. The advantage of having decentralized controller is to increase reliability and robustness of the system. Even if any controller fails to work, it may be ensured that frequency regulation is achieved by others. The algorithms used for optimizing controller parameters are genetic algorithm (GA), bacterial foraging (BF) and firefly algorithm (FA).