A novel framework for optimal sizing of hybrid stand-alone renewable energy system: A gray wolf optimizer

Abstract

Hybrid photovoltaic (PV), wind turbine (WT) diesel generator (DG) systems with battery bank have been suggested as a green and reliable power system for electrification of rural locations. There is a continues enhance in usage of green system and successively sizing optimization is the important problem for having the most cost-effective system. This study evaluates the performance of various heuristic algorithms for sizing optimization of a PV/WT//DG/battery hybrid system to continuously satisfy the electrical consumption of ten residual building located in khalkhal, Ardabil, Iran and the same block located in Rafsanjan, Kerman, Iran to have the lowest total annual cost. For this purpose, the mathematical model of each of system components are expressed and a fitness function is introduced based on the total annual cost. As well as in the problem of optimization, the maximum admissible loss of power supply probability (LPSP) is considered to have a dependable system, and three famous evolutionary algorithms, namely, particle swarm optimization (PSO), genetic algorithm(GA), salp swarm algorithm (SSA) and gray wolf optimizer algorithm (GWO), are used for the system and the results are compared in terms of the minimum total annual cost. So we can conclude that the results obtained by GWO shows that the PV/WT/DG/battery system is more economically than those of the other algorithms.