AN EFFICIENT IMPROVED ANT COLONY OPTIMIZATION TECHNIQUE TO SOLVE COMBINED ECONOMIC AND EMISSION DISPATCH PROBLEM

Abstract

Power systems have become vast and their analysis has become a complicated problem in recent years. Providing a best solution for meeting the varying demand for electricity is one of the major issues of the electric power generating organizations. The aim of power system optimization problem is to effectively schedule the generating units over a given scheduling period while meeting the projected load demand, satisfying various operating constraints and meeting certain objectives. The objective of the power system optimization can be expressed by taking both the fuel cost and total emission into account with specified constraints. The Combined Economic and Emission Dispatch problem (CEED) is defined to minimize the fuel cost of generation and the emission of green house gases of the thermal generating stations satisfying all the system constraints which makes the problem multi-objective. The multi-objective problem is converted into single objective problem by introducing price penalty factor to maintain an acceptable system performance. There are various techniques developed by a number of researchers to solve CEED problem based on optimization techniques. But still some problems like slower convergence and higher computational complexity exists in using the optimization techniques like GA for solving CEED problem. This paper proposes an efficient and reliable technique for combined fuel cost economic optimization and emission dispatch using the Improved Ant Colony Optimizat