Solving Multi-Pollutant Emission Dispatch Problem Using Computational Intelligence Technique

Economic dispatch is a crucial process conducted by the utilities to correctly determine the satisfying amount of power to be generated and distributed to the consumers. During the process, the utilities also consider pollutant emission as the consequences of fossil-fuel consumption. Fossil-fuel includes petroleum, coal, and natural gas; each has its unique chemical composition of pollutants i.e. sulphur oxides (SOX), nitrogen oxides (NOX) and carbon oxides (COX). This paper presents multi-pollutant emission dispatch problem using computational intelligence technique. In this study, a novel emission dispatch technique is formulated to determine the amount of the pollutant level. It utilizes a pre-developed optimization technique termed as differential evolution immunized ant colony optimization (DEIANT) for the emission dispatch problem. The optimization results indicated high level of COX level, regardless of any type of fossil fuel consumed.