Multi-Objective Evolutionary Algorithm for Economic Energy and Emission Dispatch Consolidating Global Environmental Regulations

Abstract

To a great extent, most of the power generation systems are dependant on fossil fuels, and their rapid usage is not only declining the reserves but also producing the greenhouse gasses that pollutes the ecology of planet and causes significant long haul harms to the earth habitats. The continuous dependency of hydrocarbon deposit will also cause shortage of fuel, causing excessively costly generation in future. In this article, a soft computing framework named as whale optimization algorithm (WOA) is proposed for the solution of multi-objective optimization problem known as economic/environmental dispatch problem (EEDP) among the most vibrant problem in the power system control area. Our designed architecture provides fast convergence rate, optimal generation cost, and reduction in environmental pollutants while handling complex system constraints such as valve-point loading effect (VPLE) and prohibited zones. To demonstrate feasibility and effectiveness of provided scheme, three highly nonlinear case studies are computed on MATLAB while considering all system contingencies. The statistical results demonstrate significant reduction in fuel emission costs, and the superiority and performance of suggested technique is compared with the recently published approaches in the literature.