A genetic algorithm based on the edge window decoder technique to optimize power distribution systems reconfiguration

This paper describes a genetic algorithm developed for power distribution system reconfiguration with minimal losses. The reconfiguration problem consists in identifying a new network topology with minimal power losses, while all the electrical system constraints are satisfied like radial topology, lines and substations power flow below capacity limits, node voltage magnitude within limits and all nodes connected. This is a combinatorial optimization problem where the aim is to determine the final status, open/closed, of all switches in a large scale distribution system. The genetic algorithm developed uses the edge window decoder encoding technique for network representation and building up spanning trees, as well as efficient genetic operators in order to explore the search space. Using two representative distribution system configurations, the results obtained with the developed methodology are compared with those obtained with other heuristic and metaheuristic techniques. The numerical results presented show the usefulness and effectiveness of the proposed algorithm.

► New genetic algorithm for power distribution system reconfiguration and loss reduction.
► Based in an efficient encoding strategy (EWD) suitable for building up spanning tree.
► A sensitivity study about the impact of genetic operators on the solution was carried out.
► The algorithm was successfully tested against other heuristic and meta-heuristic techniques.