Comparison of multi-objective optimization approaches for distribution system reconfiguration

Distribution network optimization has been classically formulated by considering a single objective function. More recently, a number of approaches have been formulated to address the presence of multiple objectives, in particular exploiting multi-objective tools to deal with conflicting objectives. This paper provides an analysis of the requirements that have to be satisfied by meta-heuristic tools in order to be efficiently used in multi-objective distribution system reconfiguration, mainly referring to maintaining the network radial and to treat the equality and inequality constraints. Comparisons of the multi-objective versions of a genetic algorithm and of a particle swarm optimization tool are shown on the basis of the results obtained on a classical test system.