Solving multi-objective economic emission dispatch of a renewable integrated microgrid using latest bio-inspired algorithms

Abstract

The concept of a microgrid system, when put in simple words, is a small scale generation and deployment of power to a small geographical area in order to avoid transmission losses and maintain an uninterrupted power supply. It has been a mandatory protocol to implement the available renewable energy sources (RES) in order to minimize the emission of harmful pollutants to the atmosphere from the combustion of the fossil fuels. Economic load dispatch (ELD) deals with the optimal sizing of the distributed energy resources (DERs) by minimizing the fuel costs. Emission dispatch does the optimal sizing of the DERs sources by minimizing the amount of pollutants released in the atmosphere. A multi-objective Combined Economic-Emission Dispatch (CEED) does the optimal DER sizing providing a compromised solution of minimizing both the fuel costs and pollutants emission. This paper performs all ELD, emission dispatch and CEED on an islanded and renewable-integrated microgrid separately using a recently developed novel Whale optimization Algorithm (WOA). Four various scenarios of load sharing among the DERs are studied. The results are then compared with other recently developed bio inspired algorithms to corroborate the effectiveness of the proposed technique. Further statistical analysis such as ANOVA test and Wilcoxon signed rank test are performed to prove the superiority of the proposed approach over the various other optimization techniques used. Keywords: Combined economic emission dispatch, Penalty factor, Microgrid, Symbiotic organisms search, Grey wolf optimization, Particle swarm optimization, Differential evolution, Whale optimization algorithm