Ant Colony System Algorithm For Distribution Network Reconfiguration

Distribution system reconfiguration is a complicated combinatorial optimization problem, which is characterized by multi-constrains, non-linearity and discreteness. Because of NP-hard, we cannot find the polynomial algorithm which can achieve the best solution to the reconfiguration problem. For satisfying the requirements of the time and space, it is reasonable and natural to compute certain sub-optimal feasible solution, and heuristic methods are designed based on such an idea.The traditional optimal methods usually only compute the local optimal best solutions to the distribution reconfiguration problem. In recent years, the modern heuristic and intelligent methods can efficiently solve such complicated discrete problem, and these algorithms are characterized by global optimization and generalization. This paper employs a new type of simulated evolutionary algorithm, Ant Colony Algorithm (ACA), to solve the distribution reconfiguration problem. Many combinatorial optimization problems have been efficiently solved by ACA. In the algorithm, in order to make the ant colony show an intelligent behavior, the ants cooperate by exchanging the pheromone. Through changing the pheromone of the feeders, the algorithm gradually achieves the better solutions.But most of these algorithms have not find a good method to represent the solution of distribution reconfiguration problem ,so that many unfeasible solutions are searched during computation process. According to the radial of distribution system, a new representation of the solution is suggested. This paper uses the spanning tree of Graph Theory to represent the solution so that radial checking procedure is avoided. In addition, because this kind of solution representation makes the searching process confined to only feasible solutions, the computational efficiency of this algorithm is greatly improved. The example systems demonstrate the effectivity and the practicality of the proposed method.