Application of modified NSGA-II algorithm to Combined Economic and Emission Dispatch problem
This paper presents a modified NSGA-II algorithm for economic and emission dispatch problem. The available NSGA-II has the drawbacks such as, lack of uniform diversity in obtained non-dominated solutions and absence of a lateral diversity-preserving operator among the currently-best non-dominated solutions. These two drawbacks have been overcome by introducing dynamic crowding distance (DCD) and controlled elitism (CE) into the NSGA-II. The developed algorithm MNSGA-II has been applied to a standard IEEE 14-, 30-, 57- and 118-bus systems to check its applicability. The results authenticate the potential and effectiveness of MNSGA-II algorithm for CEED problem. Moreover in order to certify the results arrived, four different performance metrics gamma, delta, minimum spacing and Inverted Generational Distance (IGD) were used. These metrics will be supportive for evaluating the closeness to the reference pareto-optimal front. An approach based on Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) is used to decide the choice of a solution from all pareto-optimal solutions, as the best compromise solution.
modified nsga-ii combined economic and emission dispatch dynamic crowding distance performance metrics topsis real coded genetic algorithm