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Energy Management System for Hybrid PV/Wind/Battery/Fuel Cell in Microgrid-Based Hydrogen and Economical Hybrid Battery/Super Capacitor Energy Storage

Author

Listed:
  • Younes Sahri

    (Laboratoire de Technologie Industrielle et de l’Information (LTII), Faculté de Technologie, Université de Bejaia, Bejaia 06000, Algeria)

  • Youcef Belkhier

    (Laboratoire de Technologie Industrielle et de l’Information (LTII), Faculté de Technologie, Université de Bejaia, Bejaia 06000, Algeria)

  • Salah Tamalouzt

    (Laboratoire de Technologie Industrielle et de l’Information (LTII), Faculté de Technologie, Université de Bejaia, Bejaia 06000, Algeria)

  • Nasim Ullah

    (Department of Electrical Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia)

  • Rabindra Nath Shaw

    (Department of Electronics & Communication Engineering, Galgotias University, Greater Noida 201306, India)

  • Md. Shahariar Chowdhury

    (Faculty of Environmental Management, Prince of Songkla University, Hat Yai 90112, Thailand)

  • Kuaanan Techato

    (Faculty of Environmental Management, Prince of Songkla University, Hat Yai 90112, Thailand
    Environmental Assessment and Technology for Hazardous Waste Management Research Center, Faculty of Environmental Management, Prince of Songkla University, Hat Yai 90112, Thailand)

Abstract

The present work addresses the modelling, control, and simulation of a microgrid integrated wind power system with Doubly Fed Induction Generator (DFIG) using a hybrid energy storage system. In order to improve the quality of the waveforms (voltages and currents) supplied to the grid, instead of a two level-inverter, the rotor of the DFIG is supplied using a three-level inverter. A new adaptive algorithm based on combined Direct Reactive Power Control (DRPC) and fuzzy logic controls techniques is applied to the proposed topology. In this work, two topologies are proposed. In the first one, the active power injected into the grid is smoothened by using an economical hybrid battery and supercapacitor energy storage system. However, in the second one, the excess wind energy is used to produce and store the hydrogen, and then a solid oxide fuel cell system (SOFC) is utilized to regenerate electricity by using the stored hydrogen when there is not enough wind energy. To avoid overcharging, deep discharging of batteries, to mitigate fluctuations due to wind speed variations, and to fulfil the requirement of the load profile, a power management algorithm is implemented. This algorithm ensures smooth output power in the first topology and service continuity in the second. The modelling and simulation results are presented and analysed using Matlab/Simulink.

Suggested Citation

  • Younes Sahri & Youcef Belkhier & Salah Tamalouzt & Nasim Ullah & Rabindra Nath Shaw & Md. Shahariar Chowdhury & Kuaanan Techato, 2021. "Energy Management System for Hybrid PV/Wind/Battery/Fuel Cell in Microgrid-Based Hydrogen and Economical Hybrid Battery/Super Capacitor Energy Storage," Energies, MDPI, vol. 14(18), pages 1-32, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5722-:d:633345
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    References listed on IDEAS

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    Cited by:

    1. Eunsung Oh, 2022. "Fair Virtual Energy Storage System Operation for Smart Energy Communities," Sustainability, MDPI, vol. 14(15), pages 1-16, August.
    2. Stanisław Jaworski & Mariola Chrzanowska & Monika Zielińska-Sitkiewicz & Robert Pietrzykowski & Aleksandra Jezierska-Thöle & Piotr Zielonka, 2023. "Evaluating the Progress of Renewable Energy Sources in Poland: A Multidimensional Analysis," Energies, MDPI, vol. 16(18), pages 1-21, September.
    3. Chun Yang & Shijun You & Yingzhu Han & Xuan Wang & Ji Li & Lu Wang, 2023. "Research on Optimization Method of Integrated Energy System Network Planning," Sustainability, MDPI, vol. 15(11), pages 1-15, May.
    4. Florian Rzepka & Philipp Hematty & Mano Schmitz & Julia Kowal, 2023. "Neural Network Architecture for Determining the Aging of Stationary Storage Systems in Smart Grids," Energies, MDPI, vol. 16(17), pages 1-20, August.
    5. Prabu Subramani & Sugadev Mani & Wen-Cheng Lai & Dineshkumar Ramamurthy, 2022. "Sustainable Energy Management and Control for Variable Load Conditions Using Improved Mayfly Optimization," Sustainability, MDPI, vol. 14(11), pages 1-22, May.
    6. M. Usman Saleem & Mustafa Shakir & M. Rehan Usman & M. Hamza Tahir Bajwa & Noman Shabbir & Payam Shams Ghahfarokhi & Kamran Daniel, 2023. "Integrating Smart Energy Management System with Internet of Things and Cloud Computing for Efficient Demand Side Management in Smart Grids," Energies, MDPI, vol. 16(12), pages 1-21, June.
    7. Chaoyang Chen & Hualing Liu & Yong Xiao & Fagen Zhu & Li Ding & Fuwen Yang, 2022. "Power Generation Scheduling for a Hydro-Wind-Solar Hybrid System: A Systematic Survey and Prospect," Energies, MDPI, vol. 15(22), pages 1-31, November.
    8. Younes Sahri & Salah Tamalouzt & Sofia Lalouni Belaid & Seddik Bacha & Nasim Ullah & Ahmad Aziz Al Ahamdi & Ali Nasser Alzaed, 2021. "Advanced Fuzzy 12 DTC Control of Doubly Fed Induction Generator for Optimal Power Extraction in Wind Turbine System under Random Wind Conditions," Sustainability, MDPI, vol. 13(21), pages 1-23, October.

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