A compound objective reconfiguration of distribution networks using hierarchical encoded particle swarm optimization

Abstract

With the development of automation in smart grids, network reconfiguration is becoming a feasible approach for improving the operation of distribution systems. A novel reconfiguration strategy was presented to get the optimal configuration of improving economy of the system, and then identifying the important nodes. In this strategy, the objectives increase the node importance degree and decrease the active power loss subjected to operational constraints. A compound objective function with weight coefficients is formulated to balance the conflict of the objectives. Then a novel quantum particle swarm optimization based on loop switches hierarchical encoded was employed to address the compound objective reconfiguration problem. Its main contribution is the presentation of the hierarchical encoded scheme which is used to generate the population swarm particles of representing only radial connected solutions. Because the candidate solutions are feasible, the search efficiency would improve dramatically during the optimization process without tedious topology verification. To validate the proposed strategy, simulations are carried out on the test systems. The results are compared with other techniques in order to evaluate the performance of the proposed method.

Keywords

distribution network reconfiguration / node importance degree / compound objective function / hierarchical encoded

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