Reconfiguration of Distribution Networks with Distributed Generation Using a Dual Hybrid Particle Swarm Optimization Algorithm

This paper proposes a reconfiguration strategy of distribution network with distribution generation (DG) based on dual hybrid particle swarm optimization algorithm. By the network structure simplification and branches grouping, network loss was selected as objective function, an improved binary particle swarm optimization algorithm (IBPSO) was used in branch group search, and the proposed group binary particle swarm optimization search algorithm was used in searching within the group to improve search efficiency and avoid early maturing. The proposed algorithm was tested on the IEEE 33-bus distribution power system and compared with other existing literature methods. The influence on the power flow of distribution network by DG position and capacity was studied. Simulation results illustrate that the proposed algorithm can get the optimal configuration results and significantly reduce system energy losses with fast convergence rate. In order to control the smart grid, using a dual hybrid particle swarm optimization algorithm to reconstruct a model, the result of simulation verifies the validity of the model. At the same time, the distributed power grid after reconstruction after optimization can effectively reduce the network loss and improve power supply quality.