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Investigation and Minimization of Power Loss in Radial Distribution Network Using Gray Wolf Optimization

Author

Listed:
  • Mohammed Alqahtani

    (Department of Industrial Engineering, King Khalid University, Abha 62529, Saudi Arabia)

  • Ponnusamy Marimuthu

    (Department of Electrical and Electronics Engineering, Malla Reddy Engineering College, Secunderabad 500100, India)

  • Veerasamy Moorthy

    (Department of Electrical and Electronics Engineering, KKR & KSR Institute of Technology and Sciences, Guntur 522017, India)

  • B. Pangedaiah

    (Department of Electrical and Electronics Engineering, Lakireddy Bali Reddy College of Engineering, Mylavaram 521230, India)

  • Ch. Rami Reddy

    (Department of Electrical and Electronics Engineering, Joginpally B. R. Engineering College, Hyderabad 500075, India)

  • M. Kiran Kumar

    (Department of Electrical and Electronics Engineering, Koneru Lakshmaiah Education Foundation, Guntur 522302, India)

  • Muhammad Khalid

    (Electrical Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Saudi Arabia
    IRC for Renewable Energy and Power Systems (IRC-REPS), King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Saudi Arabia
    SDAIA-KFUPM Joint Research Center for Artificial Intelligence, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Saudi Arabia)

Abstract

This paper describes a computational procedure to establish the optimal distribution of network reconfiguration by means of a novel gray wolf optimization (GWO) algorithm. The procedure aimed to diminish the system’s power loss and produce a better voltage profile while fulfilling the operating constraints described by different operating conditions. Under practical restrictions, the distribution network reconfiguration (DNR) problem is classified as multimodal and highly nonlinear. Constraint breaches were appropriately handled to produce stable convergence characteristics, and high-quality solutions were obtained in a shorter execution time. The 33-bus and 69-bus systems were used to obtain the optimal reconfiguration by incorporating the method developed in this work. The simulation results obtained were collated and compared with the outcomes of other well-known optimization techniques, confirming the efficacy of the GWO algorithm in solving the DNR problem.

Suggested Citation

  • Mohammed Alqahtani & Ponnusamy Marimuthu & Veerasamy Moorthy & B. Pangedaiah & Ch. Rami Reddy & M. Kiran Kumar & Muhammad Khalid, 2023. "Investigation and Minimization of Power Loss in Radial Distribution Network Using Gray Wolf Optimization," Energies, MDPI, vol. 16(12), pages 1-15, June.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:12:p:4571-:d:1166053
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    References listed on IDEAS

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    1. Josephy Dias Santos & Frederico Marques & Lina Paola Garcés Negrete & Gelson A. Andrêa Brigatto & Jesús M. López-Lezama & Nicolás Muñoz-Galeano, 2022. "A Novel Solution Method for the Distribution Network Reconfiguration Problem Based on a Search Mechanism Enhancement of the Improved Harmony Search Algorithm," Energies, MDPI, vol. 15(6), pages 1-15, March.
    2. Dhivya Swaminathan & Arul Rajagopalan & Oscar Danilo Montoya & Savitha Arul & Luis Fernando Grisales-Noreña, 2023. "Distribution Network Reconfiguration Based on Hybrid Golden Flower Algorithm for Smart Cities Evolution," Energies, MDPI, vol. 16(5), pages 1-24, March.
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    Cited by:

    1. Hui Jia & Xueling Zhu & Wensi Cao, 2024. "Distribution Network Reconfiguration Based on an Improved Arithmetic Optimization Algorithm," Energies, MDPI, vol. 17(8), pages 1-15, April.

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