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Energy Management System and Control of Plug-in Hybrid Electric Vehicle Charging Stations in a Grid-Connected Microgrid

Author

Listed:
  • Muhammad Roaid

    (Department of Electrical and Computer Engineering, COMSATS University Islamabad, Abbottabad Campus, Abbottabad 22060, Pakistan)

  • Tayyab Ashfaq

    (School of Physics, Engineering and Computer Science, University of Hertfordshire, Hatfield AL10 9AB, UK)

  • Sidra Mumtaz

    (Department of Electrical and Computer Engineering, COMSATS University Islamabad, Abbottabad Campus, Abbottabad 22060, Pakistan)

  • Fahad R. Albogamy

    (Computer Sciences Program, Turabah University College, Taif University, Taif 21944, Saudi Arabia)

  • Saghir Ahmad

    (Department of Electrical and Computer Engineering, COMSATS University Islamabad, Abbottabad Campus, Abbottabad 22060, Pakistan)

  • Basharat Ullah

    (Department of Mechatronics Engineering, College of Electrical and Mechanical Engineering, National University of Sciences and Technology, Islamabad 44000, Pakistan)

Abstract

In the complex environment of microgrid deployments targeted at geographic regions, the seamless integration of renewable energy sources meets a variety of essential challenges. These include the unpredictable nature of renewable energy, characterized by intermittent energy generation, as well as ongoing fluctuations in load demand, the vulnerabilities present in distribution network failures, and the unpredictability that results from unfavorable weather conditions. These unexpected events work together to disturb the delicate balance between energy supply and demand, raising the alarming threat of system instability and, in the worst cases, the sudden advent of damaging blackouts. To address this issue, a fuzzy logic-based energy management system has been developed to monitor, manage, and optimize energy consumption in microgrids. This study focuses on the control of diesel generators and utility grids in a grid-connected microgrid which manages and evaluates numerous energy consumption and distribution features within a specified system, e.g., building or a microgrid. An energy management system is suggested based on fuzzy logic as a swift fix for complications with effective and competent resource management, and its presentation is compared with both the grid-connected and off-grid modes of the microgrid. In the end, the results exhibit that the proposed controller outclasses the predictable controllers in dropping sudden variations that arise during the addition of sources of renewable energy, supporting the refurbishment of the constant system.

Suggested Citation

  • Muhammad Roaid & Tayyab Ashfaq & Sidra Mumtaz & Fahad R. Albogamy & Saghir Ahmad & Basharat Ullah, 2024. "Energy Management System and Control of Plug-in Hybrid Electric Vehicle Charging Stations in a Grid-Connected Microgrid," Sustainability, MDPI, vol. 16(20), pages 1-18, October.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:20:p:9122-:d:1503342
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    References listed on IDEAS

    as
    1. Hirsch, Adam & Parag, Yael & Guerrero, Josep, 2018. "Microgrids: A review of technologies, key drivers, and outstanding issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 402-411.
    2. Cagnano, A. & De Tuglie, E. & Mancarella, P., 2020. "Microgrids: Overview and guidelines for practical implementations and operation," Applied Energy, Elsevier, vol. 258(C).
    3. Zia, Muhammad Fahad & Elbouchikhi, Elhoussin & Benbouzid, Mohamed, 2018. "Microgrids energy management systems: A critical review on methods, solutions, and prospects," Applied Energy, Elsevier, vol. 222(C), pages 1033-1055.
    4. Kusakana, Kanzumba & Vermaak, Herman Jacobus, 2014. "Hybrid diesel generator/renewable energy system performance modeling," Renewable Energy, Elsevier, vol. 67(C), pages 97-102.
    Full references (including those not matched with items on IDEAS)

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