Minimizing Energy Losses in Unbalanced Distribution Networks via the Optimal Integration of PV Sources and D-STATCOMs

This document presents the results of a master-slave methodology developed to address the issue of reducing energy losses in electrical distribution systems by locating and sizing photovoltaic generators and distribution static compensators. The master phase utilizes several optimization techniques, including the vortex search algorithm, the particle swarm optimization, the Chu & Beasley genetic algorithm, and the generalized normal distribution optimizer, to determine the optimal location and size of each component. In contrast, the slave stage uses the three-phase version of the successive approximations method to evaluate the objective function. To validate the efficacy of this approach, it was tested on both a 25-node and a 37-node system. The study demonstrates a novel approach that minimizes energy losses by integrating two elements into the distribution power system simultaneously. The findings indicate that vortex search outperforms the other three optimization methods in reducing energy losses, reducing losses by 56.3301 % for the 25-node system and 44.1870 % for the 37-node system. Using its programming environment, all the numerical validations were carried out in the MATLAB software version 2024a.