Optimal Distribution Network Reconfiguration through Integration of Cycle-Break and Genetic Algorithms

This paper presents novel cycle-break (spanning tree generation) algorithms which can be used to find the optimal distribution network topology. These algorithms (adjacency matrix/top-down/bottom-up cycle break) represent a novel way of obtaining radial network topology by cycle regrouping using adjacency matrix or elementary cycle information. Proposed methods assure connected radial network topology and can be used in combination with genetic algorithms to obtain optimal distribution network structure under minimum active power loss or network loading index framework. The cycle-break algorithms are used in initial population generation, crossover and mutation process to enhance the performance of the genetic algorithms in terms of convergence rate. These modifications make the proposed approach suitable for the use on realistic distribution networks without concern of its complexity. The algorithms are tested on a several standard test networks and the results are compared with the other existing approaches.