Power loss minimization and voltage profile improvement by distributed generation(DG) sizing and placement

Abstract

In order to reduce power losses in a power system and to improve voltage profile, researchers have examined and studied optimizing Photovoltaic Power distributed generation (DG) which is location and size in a power system, but the results have some drawbacks. Several approaches developed to make this important issue more efficient, including coming up with new algorithms and improving those already in existence. Many of the proposed algorithms are only concerned with the real power loss, however. Voltage stability control is a critical factor in modern power systems, which makes incorporating reactive power losses in optimizing DG allocation for voltage profile improvement necessary. The goal of this work is to solve this issue by combining Genetic Algorithm and Improved Particle Swarm optimization to optimize DG size and location by considering both real and reactive power losses. Power loss sensitivity factors and real and reactive power flow factors used in identifying which buses will receive DGs. A MATLAB-based program was developed and tested on a test system using distributed generators, considering the proposed method. As compared to Genetic Algorithm, Particle Swarm optimization and Improved Particle Swarm optimization methods, the Hybrid Genetic Algorithm Improved Particle Swarm optimization method is better for reducing both real and reactive power losses.