Network Reconfiguration and Distributed Generation Placement for Multi-Goal Function Based on Improved Moth Swarm Algorithm

This paper demonstrates an effective method of performing network reconfiguration (NR) and distributed generation placement (DGP) simultaneously called NR-DGP for the multi-goal function of reducing power loss and voltage deviation as well as enhancing load balance and feeder balance with the least number of changing switches. These membership goals are combined by the fuzzy decision-making relied on the max-min technique. The results for the NR and NR-DGP on two test system including of 33 and 84 nodes are gained by the improved moth swarm algorithm (IMSA). Wherein, IMSA is developed based on the original moth swarm algorithm (MSA) with improvement of the exploration mechanism using Levy distribution. The calculated results show that NR-DGP method has gained the better improvement of the test systems' technical indicators than the NR only. The obtained results also show that IMSA has better performance for the NR and NR-DGP problems than the MSA in term the quality of the obtained optimal solution. Thus, IMSA can be an effective approach for determining the optimal solution of the NR and NR-DGP problems.