Optimal Energy Management of Hybrid MicroGrid Using Storage System and Fuzzy-GA Method

Abstract

Due to the increase of the demand for electrical power and the gaining of momentum of decentralized electrical production, the importance of microgrids is increasing constantly. Therefore, it is pertinent to understand how microgrids work and develop efficient systems to supervise and manage the produced electrical power. This paper deals with an optimal energy management system (EMS) for multi-sources hybrid microgrid. The investigated hybrid system incorporating Diesel Engine (DE), Photovoltaic generator (PV), Wind farm, Fuel Cells (FCs) and Electrolyzers. The proposed strategy was based on a combined optimal Fuzzy Logic and Genetic Algorithm (GA). The GA have been employed to optimize the scaling factors of fuzzy logic to give better results. The power demand variation was considered as disturbance, where, the optimal Fuzzy-GA was implemented to ensure microgrid balance. The effectiveness of the proposed strategy was demonstrated througth various scenarios, and the behavior of the microgrid was analyzed without and with storage system. The obtained results were compared and the proposed strategy proves the validity as a strong optimization tool that can cope with load variation.