A Novel EP Approach for Power Economic Dispatch with Valve-Point Effects and Multiple Fuel Options

This paper presents a novel approach to economic dispatch problems with valve point effects and multiple fuel options using a hybrid evolutionary programming method. Determination of global optimum solution for the practical economic dispatch problem having non smooth cost functions is difficult by using conventional mathematical approaches. Hence several evolutionary algorithm methods were proposed to solve this problem. In this paper, EP-LMO (Evolutionary Programming with Levenberg-Marquardt Optimization) technique is proposed to solve economic dispatch problems with valve point effects and multiple fuel options. The EP-LMO is developed in such a way that a simple evolutionary programming (EP) is applied as a base level search to find the direction of the optimal global region. And Levenberg-Marquardt Optimization (LMO) method is used as a fine tuning to determine the optimal solution. To illustrate the efficiency and effectiveness of the proposed approach, two bench mark problems are considered. First test problem considers multiple fuel options and next problem addresses both valve-point effects and multi-fuel options. To validate the obtained results, the proposed method is compared with the results of conventional numerical methods, Modified Hop-field Neural network, Evolutionary Programming approaches, Modified PSO, Improved PSO and Improved Genetic Algorithm with multiplier updating (IGA_MU)method.