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A Binary Archimedes Optimization Algorithm and Weighted Sum Method for UFLS in Islanded Distribution Systems Considering the Stability Index and Load Priority

Author

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  • Hazwani Mohd Rosli

    (Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya (UM), Kuala Lumpur 50603, Malaysia
    School of Engineering, Asia Pacific University of Technology and Innovation (APU), Kuala Lumpur 57000, Malaysia)

  • Hazlie Mokhlis

    (Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya (UM), Kuala Lumpur 50603, Malaysia)

  • Nurulafiqah Nadzirah Mansor

    (Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya (UM), Kuala Lumpur 50603, Malaysia)

  • Norazliani Md Sapari

    (School of Electrical Engineering, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), Johor Bahru 81310, Malaysia)

  • Syahirah Abd Halim

    (Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Malaysia)

  • Li Wang

    (Department of Electrical Engineering, College of Electrical Engineering & Computer Science, National Cheng Kung University, Tainan City 70101, Taiwan)

  • Mohamad Fani Sulaima

    (Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Melaka 76100, Malaysia)

Abstract

This study proposes an under-frequency load-shedding (UFLS) scheme based on a binary Archimedes Optimization Algorithm (BAOA) and the Weighted Sum Method (WSM) to maintain the stability of an islanded distribution system. These methods consider stability indices and load priorities to ensure effective load shedding during frequency deviations. The BAOA determines the optimal load shedding based on the stability index and power mismatch that minimizes the impact on critical loads while maintaining system stability in an islanded distribution system. The WSM determines the rank of the load to be shed based on four criteria: the load priority, the load category, the stability index, and the load size. Each load is assigned a weight based on its priority. These weight variables determine the order in which loads are shed during frequency deviations. The effectiveness of the proposed UFLS was tested on an 11 kV Malaysian distribution network with two mini hydro distributed generation systems. A comparative study was conducted based on five result outputs, including the number of loads shed, the size of the loads shed, the frequency undershoot, the frequency overshoot, and the time taken to achieve a stable frequency in three cases: base load, peak load, and peak load with photovoltaics (PV). The proposed UFLS showed the best results for 11 of 15 outputs (73.3%) for islanding events and 9 of 15 outputs (60%) for overloading events. The voltage profile and stability index, also, were improved after the proposed UFLS was applied.

Suggested Citation

  • Hazwani Mohd Rosli & Hazlie Mokhlis & Nurulafiqah Nadzirah Mansor & Norazliani Md Sapari & Syahirah Abd Halim & Li Wang & Mohamad Fani Sulaima, 2023. "A Binary Archimedes Optimization Algorithm and Weighted Sum Method for UFLS in Islanded Distribution Systems Considering the Stability Index and Load Priority," Energies, MDPI, vol. 16(13), pages 1-21, July.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:13:p:5144-:d:1186129
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    References listed on IDEAS

    as
    1. Raja Masood Larik & Mohd Wazir Mustafa & Muhammad Naveed Aman & Touqeer Ahmed Jumani & Suhaib Sajid & Manoj Kumar Panjwani, 2018. "An Improved Algorithm for Optimal Load Shedding in Power Systems," Energies, MDPI, vol. 11(7), pages 1-16, July.
    2. Jafar Jallad & Saad Mekhilef & Hazlie Mokhlis & Javed Laghari & Ola Badran, 2018. "Application of Hybrid Meta-Heuristic Techniques for Optimal Load Shedding Planning and Operation in an Islanded Distribution Network Integrated with Distributed Generation," Energies, MDPI, vol. 11(5), pages 1-25, May.
    3. Talaat, M. & Hatata, A.Y. & Alsayyari, Abdulaziz S. & Alblawi, Adel, 2020. "A smart load management system based on the grasshopper optimization algorithm using the under-frequency load shedding approach," Energy, Elsevier, vol. 190(C).
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