Comparison of Heuristic Approach in Renewable Power Optimization and Environmental Analyses

Abstract

Optimal power generation (OPG) through reliable and clean technologies is nowadays of high concern. Meta-heuristic algorithms are attractive for robust and adaptable solutions to OPG problems. However, no algorithm can result in the most desirable solution to OPG problems. In the present work, two novel methods, namely improved colliding body optimization and tuned genetic algorithm have been proposed for electric power production through combination of renewable and non-conventional energy resources. Solar photovoltaic module and biomass gasification systems have been used to deliver power reliably for a real-time load data in an Indian scenario, with battery used for energy storage. Two case studies have been conducted considering different loading scenarios. To quantify the environmental impact, carbon footprint and carbon tax have been computed for the defined case studies. ICBO has been found to provide more consistent result, in generating optimal renewable power as well as computing carbon tax.