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This paper proposes the performance improvement of radial distribution network with distributed generation (DG) integration using extended particle swarm optimization (PSO) algorithm. High-performance distribution network is a network that has a low power loss, better voltage profile, and loading balance among feeders. The effort to improve the performance of the distribution network is network configuration optimization. The optimization has become an important issue with the presence of DG in distribution networks. In this study, network configuration optimization is based on an extended PSO algorithm. The methodology has been tested in two models of IEEE radial distribution networks. The results showed that the optimal configuration of the distribution network is able to reduce power loss and to improve the voltage profile of the network significantly.

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This paper proposes a reconfiguration methodology that aims for achieving the minimum active power loss of radial distribution networks with integration of distributed energy resources (DER) in order to improve the distribution system performance. The problems of power system operations and planning schemes will be arising due to the presence of DER to the distribution systems, such losses will rise and the increase of the voltage at which there are many DER. One of the popular efforts to improve the performance of the distribution system is network reconfiguration. In this study, reconfiguration method proposed is based on an extended fuzzy multi-objective approach. Multi-objective function are considered for minimization of the active power loss, deviation of bus voltage, and load balancing among the feeders, while subject to a radial network structure in which all loads must be energized. In this case, all objectives may be simultaneously weighted. The implementation of the extended fuzzy multi-objective for reconfiguration of distribution network with integration of DER on IEEE 77-bus distribution network and Yogyakarta 60-bus distribution network are described. The simulation results show that a 1.80% of efficiency improvement is achieved for IEEE 77-bus network, and a 0.11% of Yogyakarta 60-bus network efficiency improvement is achieved by the method.

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