Particle Swarm Optimisation Applied to Economic Load Dispatch Problem

Abstract

The economic load dispatch plays an important role in the operation of power system, and several models by using different techniques have been used to solve these problems. Several traditional approaches, like lambda-iteration and gradient method are utilized to find out the optimal solution of non-linear problem. More recently, the soft computing techniques have received more attention and were used in a number of successful and practical applications. The purpose of this work is to find out the advantages of application of the evolutionary computing technique and Particle Swarm Optimization (PSO) in particular to the economic load dispatch problem. Here, an attempt has been made to find out the minimum cost by using PSO using the data of three and six generating units.

In this work, data has been taken from the published work in which loss coefficients are also given with the max-min power limit and cost function. All the techniques are implemented in MATLAB environment. PSO is applied to find out the minimum cost for different power demand which is finally compared with both lambda- iteration method and GA technique. When the results are compared with the traditional technique and GA, PSO seems to give a better result with better convergence characteristic.