Optimal sizing of a stand-alone hybrid PV-WT-BT system using artificial intelligence based technique

Abstract

Nowadays, conventional energy system is being replaced by renewable energy system. Especially, PV systems and wind energy systems are gaining much attention due to their future sustainability and eco-friendly nature. However, for these types of systems, optimization and control is a challenging task because of their unpredictable nature. In this paper, an artificial intelligence (AI) based method named as multidimensional particle swarm optimization with weights induced fitness function (MDPSO-WIFF) approach is proposed for achieving the best combination size between the hybrid photovoltaic, wind turbine and battery storage (PV-WT-BT) system. The AI algorithm handles multiobjective optimization and gives minimum cost and maximum reliability along with the minimization of unutilized surplus power. The algorithm is then justified by comparing its results with iterative-pareto-fuzzy technique. The findings show that the proposed approach is faster and capable of obtaining better quality solution in terms of total cost and reliability with trade-off to dump load.