Multi-objective optimal design of hybrid renewable energy systems using evolutionary algorithms

On the design of a hybrid renewable energy system multiple objectives are in general required to be optimized simultaneously. This study presents a general multi-objective combinatorial model for optimizing the hybrid PV-wind-diesel-battery system configuration. The model considers four objectives, i.e., minimizing the lifetime system cost, lifetime CO₂ and SO₂ emissions and maximizing the system output power. The multi-objective evolutionary algorithm based on decomposition (MOEA/D) approach is employed to obtain a set of Pareto optimal solutions to the problem. Each solution corresponds to a non-inferior design, i.e., a good combination of PV, wind, diesel and battery. By further considering the practical situation, a satisfied design could be selected.