An AIS-ACO Hybrid Approach for Multi-Objective Distribution System Reconfiguration


This work proposes a hybrid algorithm based on artificial immune systems and ant colony optimization for distribution system reconfiguration, which is formulated as a multi-objective optimization problem. The algorithm maintains a population of candidate solutions called antibodies. The search space is explored by means of the hypermutation operator that perturbs existing antibodies to produce new ones. A table of pheromones is used to reinforce better edges during hypermutation. An added innovation is the use of the pheromones to obtain quick solutions to restore the distribution system under contingency situations. The hybrid approach has been successfully implemented on two test networks. The results obtained demonstrate the efficacy of the algorithm.