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Optimum generation scheduling using an Improved Adaptive Shuffled Frog Leaping Algorithm

Economic dispatch is one of the optimization problems in the power system operation and planning in which the total cost of generation is minimized while supplying the demand and losses. The ED problem have cost functions which are non-smooth curves with equality and inequality constraints. Conventional methods have drawbacks of high convergence time and inherent sub optimality. So the researchers are looking for the alternate methods which will overcome the drawbacks of the conventional methods. In recent years optimization based on evolutionary approach is an upcoming one in which the social behavior of living organism is applied to get the solution. The objective of the paper is to present the solution to Economic dispatch problem using An Improved Adaptive Shuffled Frog Leaping Algorithm(IASFLA). IASFLA is an integer-coded algorithm which unites the benefits of both the social behavior based PSO and the genetic-based memetic algorithm (MA). In this paper, IASFLA is applied to find the optimum generation schedule considering losses and with valve point effect for thermal units. The validity of the proposed method is compared with the conventional Lagrange method, PSO, GA, Secant method and Shuffled Frog Leaping Algorithm. Four different cases have been considered for simulation study and the results obtained prove the superiority of the proposed work. It is observed from the result that the proposed method has produced best solution in terms of cost and convergence time.