Reconfiguration of Radial Distribution Systems with Variable Demands Using the Clonal Selection Algorithm and the Specialized Genetoic Algorithm of Chu-Beasley

Abstract

This paper presents two new approaches to solvethe reconfiguration problem of electrical distribution systems(EDSs) with variable demands, using the CLONALG and theSGACB algorithms. The CLONALG is a combinatorial optimization technique inspired by biological immune systems,which aims at reproducing the main properties and functions of the system. The SGACB is an optimization algorithminspired by natural selection and the evolution of species. Thereconfiguration problem with variable demands is a complex combinatorial problem that aims at identifying the bestradial topology for an EDS, while satisfying all technicalconstraints at every demand level and minimizing the cost ofenergy losses in a given operation period. Both algorithmswere implemented in C++ and test systems with 33, 84, and136 nodes, as well as a real system with 417 nodes, in orderto validate the proposed methods. The obtained results werecompared with results available in the literature in order toverify the efficiency of the proposed approaches.