Multiobjective generation dispatch through a neuro-fuzzy technique

The multiobjective generation dispatch in electric power system treats economy and emission impact as competing objectives which requires some form of conflict resolution to arrive at a solution. This paper presents an integrated approach combining a fuzzy coordination method and a radial basis function ANN along with a heuristic rule based search algorithm to solve multiobjective generation dispatch problem. The algorithm developed is simple to use and can effectively obtain the well-coordinated optimal solution while allowing more flexibility in operation. Adaptability of the performance indices composed of fuel cost and emission level are measured by the membership functions. Combining the adaptability indices a fuzzy decision making (FDM) function is obtained and the two-objective optimization is then solved by maximizing the FDM function. Then, a radial basis function ANN is developed to reach a preliminary schedule. Since, some practical constraints may be violated in the preliminary schedule, a heuristic rule based search algorithm is developed to reach a feasible best compromising generation schedule which satisfies all practical constraints. The proposed neuro-fuzzy technique has been applied to IEEE-14-bus and 30-bus test systems and the results are presented to illustrate the performance and applicability of the technique.