In this paper problem formulation and solution methodology of economic dispatch using ant colony optimization is presented. Ant colony optimization (ACO) is a meta-heuristic approach for solving hard combinatorial optimization problems. The procedure and implementation details of ant colony search algorithm (ACSA) for power system economic dispatch are presented. The problem solving process of ACO lies in the trail laying and following behaviour of real ants which use pheromones. The pheromone trails in ACO serve as distributed, numerical information which the ants use to probabilistically construct solutions to the problem being solved and which the ants adapt during the algorithm's execution to reflect their search experience. The suitability of the ant colony optimization algorithm for a typical hard problem like economic dispatch was carried out for two systems consisting of three and six generating units. It was later extended to standard IEEE 14, 30 and 57 bus systems. The suitability of ACO for economic load dispatch appears to be more effective for large scale systems.