Application of the ant colony search algorithm to short-term generation scheduling problem of thermal units

Abstract

This paper presents a new cooperative agents approach, the ant colony search algorithm (ACSA), for solving a short-term generation scheduling problem of a thermal power system. One of the main goals of this paper is to investigate the applicability of an alternative intelligent search method in power system optimisation. The ACSA is derived from the theoretical biology on the topic of ant trail formation and foraging methods. In the ACSA, a set of co-operating agents called ants cooperate to find a good solution to the short-term generation scheduling problem of thermal units. The effectiveness of the proposed scheme has been demonstrated on the daily scheduling problem of a model power system and the results are compared with those obtained by a conventional scheduling method.