Dynamic Economic Emission Dispatch Using Evolutionary Programming and Fuzzy Satisfying Method

Dynamic economic emission dispatch is an extension of the conventional economic emission dispatch problem that takes into consideration the ramp rate limits of the generators. Evolutionary programming based fuzzy satisfying method has been proposed to determine the optimal noninferior generation schedule. This paper treats economy and emission as competing objectives for optimal dispatch, which requires some form of conflict resolution to arrive at a solution. The multi-objective problem is configured as a minimax problem under the assumption that the decision-maker has fuzzy goals for each of the objective functions. The present algorithm employs evolutionary programming technique in solving this problem. The solution methodology can offer a global or near-global noninferior solution for the decision-maker. Numerical results of a sample test system have been presented to demonstrate the performance and applicability of the proposed method. Results obtained from the proposed method are compared to those obtained by fuzzy satisfying method based on simulated annealing technique.