Study of Multi-objective Optimization and Multi-attribute Decision-making for Economic and Environmental Power Dispatch


Environmental awareness and the recent environmental policies have forced many electric utilities to restructure their practices to account for their emission impacts. One way to accomplish this is by reformulating the traditional economic dispatch problem such that emission effects are included in the mathematical model. The economic/environmental dispatch problem is a multi-objective non-linear optimization problem with constraints. This study presents a hybrid approach to solve the combined economic-emission dispatch problem (CEED). In the first stage,a non-dominated sorting genetic algorithm II (NSGA II) is employed to approximate the set of Pareto solution through an evolutionary optimization process. in the subsequent stage, a multi-attribute decision-making (MADM) approach is adopted to rank these solutions from best to worst and to determinate the best solution in a deterministic environment with a single decision maker. This hybrid approach is tested on a six-unit system to illustrate the analysis process in present analysis. Pareto, frontiers are obtained and the ranking of Pareto solutions is based on entropy weight and TOPSIS method. Results obtained show that the hybrid approach has a great potential in handling multi-objective optimization problem.