Multi-objective optimization of hybrid power system using magnetotactic bacteria moment migration optimization algorithm

Abstract

Alternative energy sources are more attractive now a day because of the vanishing of conventional sources in the next few decades, energy crisis and environmental effects. Solar PV and wind are the two emerging sources among the existing renewable energy sources. However intermittent nature and system cost are the two main limitations of renewable sources. Therefore hybridization of photovoltaic, wind with battery can overcome this drawback and improves the reliability as well as efficiency to some extent. The objectives considered in this work are to minimize the hybrid system cost and maximize the energy generation from PV and Wind with a new constraint of Grid Dependency Ratio (GDR). A new multi-objective optimization method is suggested in this work to achieve the aforementioned objectives. The proposed algorithm shows the quick convergence, improved accuracy and minimum processing time compared to the Particle Swarm Optimization algorithm.