Energy Management Control Strategy for Renewable Energy System Based on Spotted Hyena Optimizer

Hydrocarbons, carbon monoxide and other pollutants from the transportation sector harm human health in many ways. Fuel cell (FC) has been evolving rapidly over the past two decades due to its efficient mechanism to transform the chemical energy in hydrogen-rich compounds into electrical energy. The main drawback of the standalone FC is its slow dynamic response and its inability to supply rapid variations in the load demand. Therefore, adding energy storage systems is necessary. However, to manage and distribute the power-sharing among the hybrid proton exchange membrane (PEM) fuel cell (FC), battery storage (BS), and supercapacitor (SC), an energy management strategy (EMS) is essential. In this research work, an optimal EMS based on a spotted hyena optimizer (SHO) for hybrid PEM fuel cell/BS/SC is proposed. The main goal of an EMS is to improve the performance of hybrid FC/BS/SC and to reduce the amount of hydrogen consumption. To prove the superiority of the SHO method, the obtained results are compared with the chimp optimizer (CO), the artificial ecosystem-based optimizer (AEO), the seagull optimization algorithm (SOA), the sooty tern optimization algorithm (STOA), and the coyote optimization algorithm (COA). Two main metrics are used as a benchmark for the comparison: the minimum consumed hydrogen and the efficiency of the system. The main findings confirm that the minimum amount of hydrogen consumption and maximum efficiency are achieved by the proposed SHO based EMS.