Grey wolf optimizer for optimal design of hybrid renewable energy system PV-Diesel Generator-Battery: Application to the case of Djanet city of Algeria

Abstract

The optimal sizing of a hybrid system of renewable electricity is an important phase in its design. As long as the cost of the capital equipment is the major component in the price of renewable electricity. This paper presents the application of one of the latest swarm intelligence algorithms, namely Grey Wolf Optimizer (GWO) which is inspired from grey wolves. The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. The proposed strategy is applied for optimal design and minimizes the total cost of the hybrid power generation system in isolated rural village in south Algeria named “Djanet”. A power system consisting of a photovoltaic array panel, diesel generator, Battery banks and load is considered for tested the proposed approach. The results obtained by this new method are compared with Particle Swarm Optimization (PSO) algorithm; there are shows that the proposed methodology finds the optimal number of PV panels, diesel generators and battery banks easily with fast convergence, lower cost and the superior capabilities of this proposed method are demonstrated.