Large-Scale Economic Dispatch by Artificial Ant Colony Search Algorithms

Abstract

This paper presents a new cooperative agent search approach for solving power economic dispatch problems. One of the main objectives of this paper is to investigate the applicability of an alternative agent search method in power system optimization. The proposed Artificial Ant Colony Search Algorithm (ACSA) is based on the results of real ant trail formation and foraging obtainedfrom theoretical biology science. A new encoding technique is proposed to overcome the difficulties of applying ACSA in a continuous search space, such as economic dispatch problems. An object-oriented ACSA system is developed and programmed. The effectiveness of the proposed technique has been demonstrated on a number of systems, which include an actual utility system of up to 40 units. Comparison with conventional genetic algorithms is presented. The outcome of the study shows that an emergent collective search ability resulted from the massive parallel fashion and positive feedback of ant colony is particularly attractive in addressing some difficult engineering problems; however, it should be observed that current research of Ant Colony Search Algorithm in power system is relatively new and still at a feasibility stage. More potentially beneficial work remains to be done.