Using Crow Algorithm for Optimizing Size of Wind Power Plant/Hybrid PV in Libya

Abstract

To design an efficient, sustainable and feasible hybrid system sizing optimization should be applied. In this study, a hybrid power plant, which consists of an off-grid PV and wind energy system to supply the demand of solar energy research center in Libya, was designed. Crow search technique was applied to decrease the installation cost and operating cost by sizing each part of hybrid system. We optimized the number of PV modules, powers of wind turbines and capacities batteries. After offering the design of hybrid system, we compared performance of crow algorithm with particle swarm optimization algorithm performance. Regarding the comparison, crow algorithm results sign a better performance for sizing a lower cost hybrid power plant consists of PV and wind systems.