A Comparative Analysis of Multi-objective Optimization Algorithms for Stand-Alone Hybrid Renewable Energy System

Energy scarcity is one of the greatest challenges faced by the developing countries like India. Researches are now heading towards developing non-conventional energy sources that are both economical and available naturally in large quantities. In this regard, an urgent requirement has been posed to reduce our dependency on fossil fuels for generating sustainable energy. Standalone systems plays a crucial role in promoting rural electrification. Previous studies have focused single objective optimization or weighted sum approach for multi-objective optimization. We have introduced multi-objective optimization approach in this paper which provides a range of solutions for different objectives. The paper proposes a standalone system consisting of renewable energy sources, namely PV and wind combined with battery and diesel generator to fulfill the demand of housing loads in a village of Gujarat. Component sizing have been done by three multi-objective optimization algorithms namely NSGA II, NSGA III and MOPSO to minimize LPSP, COE and maximize RF. Also we have performed some studies to compare the results of multi-objective optimizations.