Ant Colony Optimization-Based Approach to Optimal Reactive Power Dispatch: A Comparison of Various Ant Systems

The optimal reactive power dispatch (ORPD) problem is formulated as a combinatorial optimization problem involving nonlinear objective function with multiple local minima. In this paper, as a new approach, different ant colony optimization (ACO) algorithms are applied to the reactive power dispatch problem. Ant system (AS), the firstly introduced ant colony optimization algorithm, and its direct successors, elitist ant system (EAS), rank-based ant system (AS_rank) and max-min ant system (MMAS), are employed to solve the reactive power dispatch problem. To analyze the efficiency and effectiveness of these modern search algorithms, the proposed methods are applied to the IEEE 30-bus system and the results are compared to those of conventional mathematical methods, genetic algorithm, evolutionary programming, and particle swarm optimization.