Abstract
Hybrid energy systems (HES) that combine Photovoltaic (PV) arrays with Wind turbines (WTs) are excellent options for powering rural locations. The optimal design of HESs with distributed generations (DGs) (i.e., PV, WT) is still a hot topic due to the uncertainties in solar irradiance and wind speed. Based on a long-term cost analysis, this paper formulates an application of grasshopper optimization algorithm (GOA) in the field of HES design problem. GOA's efficacy is studied, and its performance is compared to that of the genetic algorithm (GA), butterfly optimization algorithm (BOA), and big-bang-big-crunch (BBBC) algorithm. The GOA outperformed the other seven metaheuristic algorithms where it attained the optimal solution of the HES with the lowest ASC. It can be revealed that the GOA has acceptable performance in terms of the global solution capture with less oscillations and the convergence rate.