Multi-objective Economic/Ecological Emissions Power Dispatch Using Fuzzified EMF Heuristic Algorithm

With the heightened interest over the preservation of environment, economic/ecological emissions dispatch (EELD) has devoted a great deal of notice. It remains virtually a multiobjective (MO) optimization issue that disparages twain the fuelling cost and ecological emissions concurrently in addition to the system constraints gratifications. This article bestows electromagnetic field (EMF) theories inspired metaheuristic algorithm to solve the MO-EELD problems with different generation units. EMF optimization (EMFO) is one of the modern metaheuristic algorithm global approaches which simulates the Coulomb's and Franklin's theories. In EMFO, the population comprises of objects made of point charges corresponding to generation units of EELD problem. In every generation, a new point charge is generated based on the attraction and repulsion between these EMFs. The MO-EELD concern is transferred to a sole-objective concern with weighted sum approach. Moreover, the fuzzy clustering mechanism is utilized to decide the best comprising solution from Pareto front solutions set. The competence of the suggested fuzzified EMFO (FEMFO) is ordained in comparison to the existing heuristic algorithms in the literature. This study resolutely exhibited that the FEMFO approach is adroit to discover more accurate solutions although it utilizes outnumbered function evaluation calls.