Distribution Systems Reconfiguration Using PSO based on Co-Simulation of PowerFactory and Python

This paper proposes power loss reduction and voltage profile improvement in the distribution system using feeder reconfiguration. There are many methods to reduce power loss and improve voltage profile in the distribution system. Feeder reconfiguration is one of the most efficient ways that consume less investment cost. However, obtaining the optimal solution is somewhat complex and challenging since many related variables exist. A modified particle swarm optimization (MPSO) is applied to solve this complicated problem. This method has an operating pattern that mimics searching for the food of the swarm by exchanging experiences and communicating data to observe the excellent result of the problem. Therefore, this paper proposes feeder reconfiguration in the distribution system by using a modified particle swarm optimization to find the appropriate network topology of the distribution system that causes minimum loss and improves voltage profile to acceptable criteria. The proposed method was tested on a radial IEEE69-Bus distribution system in the case of balanced loads and unbalanced loads by simulating on DIgSILENT Simulation Language (DSL) of the DIgSILENT PowerFactory software using Python programming language to write MPSO scripts to analyze the system. The result shows that the power loss of the distribution system decreased to 76 % after feeder reconfiguration, which is satisfactory and indicates that the distribution system has high efficiency compared with the conventional one.