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Coordinated Volt-Var Control of Reconfigurable Microgrids with Power-to-Hydrogen Systems

Author

Listed:
  • Khalil Gholami

    (Renewable Energy and Electric Vehicle (REEV) Laboratory, School of Engineering, Deakin University, Geelong, VIC 3216, Australia)

  • Ali Azizivahed

    (School of Electrical and Data Engineering, University of Technology Sydney, Sydney, NSW 2007, Australia)

  • Ali Arefi

    (School of Engineering and Energy, Murdoch University, Perth, WA 6150, Australia)

  • Li Li

    (School of Electrical and Data Engineering, University of Technology Sydney, Sydney, NSW 2007, Australia)

  • Mohammad Taufiqul Arif

    (Renewable Energy and Electric Vehicle (REEV) Laboratory, School of Engineering, Deakin University, Geelong, VIC 3216, Australia)

  • Md Enamul Haque

    (Renewable Energy and Electric Vehicle (REEV) Laboratory, School of Engineering, Deakin University, Geelong, VIC 3216, Australia)

Abstract

The integration of electrolyzers and fuel cells can cause voltage fluctuations within microgrids if not properly scheduled. Therefore, controlling voltage and reactive power becomes crucial to mitigate the impact of fluctuating voltage levels, ensuring system stability and preventing damage to equipment. This paper, therefore, seeks to enhance voltage and reactive power control within reconfigurable microgrids in the presence of innovative power-to-hydrogen technologies via electrolyzers and hydrogen-to-power through fuel cells. Specifically, it focuses on the simultaneous coordination of an electrolyzer, hydrogen storage, and a fuel cell alongside on-load tap changers, smart photovoltaic inverters, renewable energy sources, diesel generators, and electric vehicle aggregation within the microgrid system. Additionally, dynamic network reconfiguration is employed to enhance microgrid flexibility and improve the overall system adaptability. Given the inherent unpredictability linked to resources, the unscented transformation method is employed to account for these uncertainties in the proposed voltage and reactive power management. Finally, the model is formulated as a convex optimization problem and is solved through GUROBI version 11, which leads to having a time-efficient model with high accuracy. To assess the effectiveness of the model, it is eventually examined on a modified 33-bus microgrid in several cases. Through the results of the under-study microgrid, the developed model is a great remedy for the simultaneous operation of diverse resources in reconfigurable microgrids with a flatter voltage profile across the microgrid.

Suggested Citation

  • Khalil Gholami & Ali Azizivahed & Ali Arefi & Li Li & Mohammad Taufiqul Arif & Md Enamul Haque, 2024. "Coordinated Volt-Var Control of Reconfigurable Microgrids with Power-to-Hydrogen Systems," Energies, MDPI, vol. 17(24), pages 1-20, December.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:24:p:6442-:d:1548980
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    References listed on IDEAS

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    1. Zhang, Wenjie & Gandhi, Oktoviano & Quan, Hao & Rodríguez-Gallegos, Carlos D. & Srinivasan, Dipti, 2018. "A multi-agent based integrated volt-var optimization engine for fast vehicle-to-grid reactive power dispatch and electric vehicle coordination," Applied Energy, Elsevier, vol. 229(C), pages 96-110.
    2. Shahbazbegian, Vahid & Shafie-khah, Miadreza & Laaksonen, Hannu & Strbac, Goran & Ameli, Hossein, 2023. "Resilience-oriented operation of microgrids in the presence of power-to-hydrogen systems," Applied Energy, Elsevier, vol. 348(C).
    3. Javadi, Mohammad Sadegh & Esmaeel Nezhad, Ali & Jordehi, Ahmad Rezaee & Gough, Matthew & Santos, Sérgio F. & Catalão, João P.S., 2022. "Transactive energy framework in multi-carrier energy hubs: A fully decentralized model," Energy, Elsevier, vol. 238(PB).
    4. J. Boland & J. A. Filar & G. Mohammadian & A. Nazari, 2016. "Australian electricity market and price volatility," Annals of Operations Research, Springer, vol. 241(1), pages 357-372, June.
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