Enhancement of hydroelectric generation scheduling using Ant Colony Systembased optimization approaches

In this paper, an Ant Colony System (ACS) based optimization approach is pr oposed for the enhancement of hydroelectric generation scheduling. To apply the method to solve this problem, the search space of multi-stage scheduli ng is first determined. Through a collection of cooperative agents called a nts, the near-optimal solution to the scheduling problem can be effectively achieved. In the algorithm, the state transition rule, local pheromone-upd ating rule, and global pheromone-updating rule are all added to facilitate the computation. Because this method can operate the population of agents s imultaneously, the process stagnation can be better prevented. The optimiza tion capability can be thus significantly enhanced. The proposed approach h as been tested on Taiwan Power System (Taipower) through the utility data. Test results demonstrated the feasibility and effectiveness of the method f or the application considered.