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Application of Hybrid Meta-Heuristic Techniques for Optimal Load Shedding Planning and Operation in an Islanded Distribution Network Integrated with Distributed Generation

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  • Jafar Jallad

    (Power Electronics and Renewable Energy Research Laboratory (PEARL), Department of Electrical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia
    Department of Electrical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia)

  • Saad Mekhilef

    (Power Electronics and Renewable Energy Research Laboratory (PEARL), Department of Electrical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia)

  • Hazlie Mokhlis

    (Department of Electrical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia)

  • Javed Laghari

    (Department of electrical engineering, Quaid-e-Awam University of Engineering Science and Technology, QUEST, Nawabshah, Sindh 67450, Pakistan)

  • Ola Badran

    (Power Electronics and Renewable Energy Research Laboratory (PEARL), Department of Electrical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia
    Department of Electrical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia)

Abstract

In a radial distribution network integrated with distributed generation (DG), frequency and voltage instability could occur due to grid disconnection, which would result in an islanded network. This paper proposes an optimal load shedding scheme to balance the electricity demand and the generated power of DGs. The integration of the Firefly Algorithm and Particle Swarm Optimization (FAPSO) is proposed for the application of the planned load shedding and under frequency load shedding (UFLS) scheme. In planning mode, the hybrid optimization maximizes the amount of load remaining and improves the voltage profile of load buses within allowable limits. Moreover, the hybrid optimization can be used in UFLS scheme to identify the optimal combination of loads that need to be shed from a network in operation mode. In order to assess the capabilities of the hybrid optimization, the IEEE 33-bus radial distribution system and part of the Malaysian distribution network with different types of DGs were used. The response of the proposed optimization method in planning and operation were compared with other optimization techniques. The simulation results confirmed the effectiveness of the proposed hybrid optimization in planning mode and demonstrated that the proposed UFLS scheme is quick enough to restore the system frequency without overshooting in less execution time.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:5:p:1134-:d:144389
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    References listed on IDEAS

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    1. 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.
    2. Robert Małkowski & Janusz Nieznański, 2020. "Underfrequency Load Shedding: An Innovative Algorithm Based on Fuzzy Logic," Energies, MDPI, vol. 13(6), pages 1-16, March.
    3. Kuihua Wu & Kun Li & Rong Liang & Runze Ma & Yuxuan Zhao & Jian Wang & Lujie Qi & Shengyuan Liu & Chang Han & Li Yang & Minxiang Huang, 2018. "A Joint Planning Method for Substations and Lines in Distribution Systems Based on the Parallel Bird Swarm Algorithm," Energies, MDPI, vol. 11(10), pages 1-14, October.
    4. Florin-Constantin Baiceanu & Ovidiu Ivanov & Razvan-Constantin Beniuga & Bogdan-Constantin Neagu & Ciprian-Mircea Nemes, 2023. "A Continuous Multistage Load Shedding Algorithm for Industrial Processes Based on Metaheuristic Optimization," Mathematics, MDPI, vol. 11(12), pages 1-19, June.
    5. Olumuyiwa T. Amusan & Nnamdi I. Nwulu & Saheed Lekan Gbadamosi, 2022. "Identification of Weak Buses for Optimal Load Shedding Using Differential Evolution," Sustainability, MDPI, vol. 14(6), pages 1-12, March.
    6. Ifedayo Oladeji & Ramon Zamora & Tek Tjing Lie, 2021. "An Online Security Prediction and Control Framework for Modern Power Grids," Energies, MDPI, vol. 14(20), pages 1-27, October.
    7. Skrjanc, T. & Mihalic, R. & Rudez, U., 2023. "A systematic literature review on under-frequency load shedding protection using clustering methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 180(C).
    8. Kai Wang & Lixia Kang & Songhao Yang, 2022. "A Coordination Optimization Method for Load Shedding Considering Distribution Network Reconfiguration," Energies, MDPI, vol. 15(21), pages 1-18, November.

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