Optimal design of an off-grid multi-energy microgrid based on corona virus search optimizer

This paper focuses on the optimal design of off-grid multi-energy microgrids (MEM). Optimizing such microgrids is paramount because they can provide sustainable and reliable energy solutions in remote or emergency scenarios. Thus, this study investigates the economic planning of an off-grid MEM composed of wind turbines (WT), photovoltaic (PV), electric vehicles (EV), batteries energy storage (BES), combined heat and power (CHP) systems, and thermal energy storage (TES). The optimization objective considered in this problem includes capital investment, maintenance, and operational costs. By modeling the operation of resources and storage system, priority is given to supplying electrical loads through wind turbines, solar panels, and combined heat and power systems. The electrical and thermal storage devices also play a role in matching supply and demand. This study employs the Corona Virus Search Optimizer (CVSO), an optimization algorithm inspired by virus behavior. The simulation results demonstrate the enhanced efficiency and performance of the CVSO algorithm in optimizing the design of off-grid multi-energy microgrid systems. Furthermore, this system’s optimal design has successfully provided electrical and thermal loads with minimized costs.