Solution of Economic Load Dispatch problem in Power System using Lambda Iteration and Back Propagation Neural Network Methods

Abstract

Economic load dispatch is the process of allocating the required load demand between the available generators in power system while satisfying all units and system equality and inequality constraints. Economic Load Dispatch solutions are found by solving the conventional methods such as lambda iteration, Gradient search method, Linear Programming and Dynamic Programming while at the same minimizing fuel costs, but convergence is too slow, so in order to get fast convergence and accurate results we are using artificial neural network. Artificial neural network is well-known in the area of power systems. It is a very powerful solution algorithm because of its rapid convergence near the solution. This property is especially useful for power system applications because an initial guess near the solution is easily attained. In this paper a three generator system is considered and by using lambda iteration method Economic Load Dispatch is determined and 150 patterns for different loads will be derived from same method to train neural network. As it is too slow method, we proposed a soft computing based approach i.e. Back Propagation Neural Network (BPNN) for determining the optimal flow. This method provides fast and accurate results when compared with the conventional method.