The Distribution Network Loss Minimization by Incorporating DG Using Particle Swarm Optimization (PSO) Technique

Authors

  • Kazi Abdul Kader American International University Bangladesh
  • Md. Abdul Mannan American International University Bangladesh (AIUB)
  • Md. Rifat Hazari American International University Bangladesh (AIUB)

DOI:

https://doi.org/10.53799/ajse.v23i3.780

Keywords:

DG allocation, Distribution Network, PSO, BIBC, BCBV, RND, Loss minimization, Network reconfiguration.

Abstract

This research is based on the power system optimal planning and operation segment. This study presents a methodology for reducing power losses in distribution power systems through the incorporation of both fixed and uncertain photovoltaic (PV) generation, utilizing the Particle Swarm Optimization (PSO) technique. The proposed approach aims to address the unpredictability of PV generation and optimize the placement and size of Distributed Generation (DG) units to minimize I2R loss in the distribution network. The main focus is on how to minimize the existing losses occurring in the distribution system. In the distribution system the I2R loss amount is higher compared to the transmission system. The reason behind the high amount of I2R loss in the distribution system is due to the high ratio, high current and low voltage. To reduce these losses, several researchers provide solutions, such as network reconfiguration, capacitor allocation, DG allocation, and DSTATCOM allocation. In this research I have focused on DG allocation solution for reducing the I2R loss. I have determined the most suitable photovoltaic generation capacity and location to minimize power loss in the system using the PSO algorithm. The PSO techniques can accurately determine the optimal locations for PV generation in the IEEE-33 bus and IEEE-69 bus radial feeder, which preserves power quality for consumers and reduces energy loss during distribution. To conduct this study, three simulation scenarios were employed, namely: a) the base case, b) without accounting for the uncertainty of solar irradiance and load demand, and c) considering the uncertainty of solar irradiance and load demand. The comparison between the three scenario results will also be shown in the results section for both the IEEE-33 and IEEE-69 bus systems. MATLAB R2021a was utilized to evaluate the algorithm's effectiveness in the IEEE-33 and IEEE-69 bus systems

Author Biographies

  • Kazi Abdul Kader, American International University Bangladesh

    Kazi Abdul Kader received B.Sc. in Electrical and Electronic Engineering from American International University Bangladesh (AIUB) in 2021. Currently, he is completing his M.Sc. degree from American International University Bangladesh (AIUB). His research interest in power system and Renewable Energy. He currently works as an Application Engineer at Iconic Engineering Limited.

  • Md. Abdul Mannan, American International University Bangladesh (AIUB)

    Mohammad Abdul Mannan was born in Laxmipur, Bangladesh on January 01, 1975. He received his B. Sc. Eng. Degree from Rajshahi University of Engineering and Technology (RUET former BITR), Bangladesh, in 1998, and Masters of Eng. and Dr. of Eng. degrees from Kitami Institute of Technology, Japan, in 2003 and 2006 respectively, all in electrical engineering. He then joined in the American International University Bangladesh (AIUB) as an Assistant professor in May 2006. He served in AIUB as an Associate Professor from December 2013 to November 2016. Now he is working as a Professor and Director of Faculty of Engineering in AIUB. His research interests include electric motor drive, power electronics, power system, wind generation system and control of electric motor, power electronic converters, power system, and wind generation system. Prof. Dr. Mannan is a member of the IEB and IEEE.

  • Md. Rifat Hazari, American International University Bangladesh (AIUB)

    Md. Rifat Hazari received his B.Sc. Engg. and M.Sc. Engg. Degrees in Electrical and Electronic Engineering from
    American International University-Bangladesh (AIUB) in August 2013 and December 2014, respectively and Ph.D. Degree in Energy Engineering from Kitami Institute of Technology (KIT), Japan, in March 2019. He served as a Lecturer in Electrical and Electronic Engineering department at AIUB. Currently, he is working as an Assistant Professor in the Electrical and Electronic Engineering department at AIUB. He received the MINT (Academic Excellence) Award 2017 from KIT for the outstanding research of 2017 academic year, Best Paper Award in the Australasian Universities Power Engineering Conference 2017, Melbourne, Victoria, Australia and Best Presentation Award in the IEEJ Branch Convention 2017, Hakodate, Japan. His research interests are
    renewable energy systems (especially wind power & photovoltaic power systems), power system stability and
    control, microgrid and hybrid power systems, HVDC system, analysis and control of rotating electrical machines. Dr. Hazari is a member of IEEE.

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Published

12/31/2024

Issue

Vol. 23 No. 3 (2025): AJSE Volume 23 Issue 3

Section

Articles

License

AJSE contents are under the terms of the Creative Commons Attribution License. This permits anyone to copy, distribute, transmit and adapt the work non-commercially provided the original work and source is appropriately cited.

How to Cite

[1]
“The Distribution Network Loss Minimization by Incorporating DG Using Particle Swarm Optimization (PSO) Technique”, AJSE, vol. 23, no. 3, pp. 200–208, Dec. 2024, doi: 10.53799/ajse.v23i3.780.