Optimal techno-economic energy management strategy for building's microgrids based bald eagle search optimization algorithm

This research proposes an effective energy management strategy (EMS) for the economic operation under standalone and grid-connected operating modes of integrated solar renewables microgrid. The proposed microgrid is composed of a photovoltaic generator (PV), a fuel cell system (FC), and a battery storage system. The random nature of the renewable and the load power imposed some stability problems and economic problems, including operating costs. The suggested technique was based on the bald eagle search optimization algorithm (BES), which was designed for a one-day scheduling horizon. The key objectives of this paper were to satisfy the load power with the lowest operating costs under a stable direct current (DC) bus voltage, enhance the overall system efficiency and protect the battery from deep discharge and overcharge. To demonstrate the effectiveness of the proposed strategy, the obtained results were compared with other optimizers, including particle swarm optimization (PSO), salp swarm algorithm (SSA), artificial eco-system optimizer (AEO), COOT optimizer, and political optimizer (PO). The comparison confirmed the superiority of the proposed strategy in terms of minimum operating energy cost (0.1577c€/kW), high efficiency (87.395%) and final SoC (33.268%).