Evolutionary algorithms for the reconfiguration of radial distribution networks considering long interruption and voltage sag disruption costs

In this paper a computational implementation of an evolutionary algorithm (EA) is shown to tackle the problem of reconfiguring radial distribution systems under different load conditions. The developed module considers power quality indices such as long duration interruptions and customer process disruptions due to voltage sags, by using the Monte Carlo simulation method. Power quality costs are considered into the mathematical problem formulation, which are added to the cost of network losses. As for the EA codification proposed, a decimal representation is used. The EA operators, namely selection, recombination and mutation, which are considered for the reconfiguration algorithm, are herein analyzed. A number of selection procedures are considered, namely tournament, elitism and a mixed technique using both elitism and tournament. The recombination operator was developed by considering a chromosome structure representation that maps the network branches and system radiality, and another structure that considers the network topology and feasibility of network operation to exchange genetic material. The topologies regarding the initial population are randomly produced so as radial configurations are produced through Prim and Kruscal algorithms that rapidly build minimum spanning trees.