Study of reactive power optimization based on Artificial Immune Ant Colony Algorithm

This paper presents an algorithm for optimizing reactive power using Artificial Immune Ant Colony Algorithm. This hybrid algorithm uses artificial immune algorithm (AIA) to give pheromone to distribute and makes use of Ant Colony Algorithm (ACA) to give the optimal solution. The ACA has been improved. The improved ACA uses the best and worst ant to update the pheromone trails and pseudorandom proportional rule. Local pheromone update mechanism, pheromone limitation and adaptive pheromone decay coefficient are increased. The objective function of the proposed algorithm is to minimize the system active power loss. This algorithm has been applied to practical IEEE 30-bus system and shows better results and convergence rate as compared to other optimal methods.