Mitigation of Line Losses in Distribution System using Optimized Placement of Distributed Generation

  • Muhammad Nouman Elahi
  • Safdar Raza NFC Institute of Engineering & Technology, Multan.
  • Faisal Maqsood NFC IET Multan
  • Muhammad Zeeshan NFC, IET, Multan
Keywords: Distributed Generation (DG), Voltage profile, Power loss, Improved Particle Swarm Optimization (IPSO), Genetic Algorithm (GA)

Abstract

Line losses are the most significant challenge faced by Pakistan's energy department. 6.5% of the country's GDP, a large figure of $1.8 billion is lost every year due to line losses in power generation, transmission, distribution and consumption. In distribution systems, researchers are attracted by the penetration of distributed generation (DG) nowadays. The performance of a distribution network is affected by the significant role of number, capacity and situation of DG units. This study will focus on the distributed generation of a centralized national grid and provide an algorithmic model that implements Improved Particle Swarm Optimization to reduce the system power loss and improve the voltage profiles via optimization of the locations and sizes of multip1le DG(s). The overall sensitive feature was determined and utilized efficiently to reduce research space for the algorithm. In the case of IEEE 33Bus test system, 10% of candidate buses are selected as possible DG situations. The IPSO methodology produced severe loss reduction and improve the voltage profiles in all the three types of DGs considered using the IEEE 33-Bus system. The percentage decrease in active power losses was reduced 68.10492%, 66.91669% and 58.89211% for DG type -1, DG type-2 and DG type-3 respectively. At the same time, reactive power losses were reduced 53.095%, 53.0922% and 50.4145% for DG type -1, DG type-2 and DG type-3 respectively.

Published
2020-09-17
How to Cite
[1]
M. N. Elahi, S. Raza, F. Maqsood, and M. Zeeshan, “Mitigation of Line Losses in Distribution System using Optimized Placement of Distributed Generation”, PakJET, vol. 3, no. 2, pp. 59-72, Sep. 2020.