A novel short-term generation scheduling technique of thermal units using ant colony search algorithms

This paper presents a novel co-operative agents approach, ant colony search algorithm (ACSA)-based scheme, for solving a short-term generation scheduling problem of thermal power systems. The main purpose of this paper is to investigate the applicability of an alternative intelligent search method in power system optimisation, particularly in short-term generation scheduling problems. The ACSA is derived from the theoretical biology of the topic of ant trail formation and foraging methods. A set of co-operating agents, ants, cooperate to find a good solution for the short-term generation scheduling problem of thermal units. In the ACSA, the state transition rule, global and local updating rules are also introduced to ensure the optimal solution. Once all the ants have completed their tours, a global pheromone-updating rule is then applied and the process is iterated until the stop condition is satisfied. The effectiveness of the proposed scheme has been demonstrated on the daily generation scheduling problem of model power systems.