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Digital Real-Time Simulation and Power Quality Analysis of a Hydrogen-Generating Nuclear-Renewable Integrated Energy System

Author

Listed:
  • Sushanta Gautam

    (EECS Department, The University of Toledo, Toledo, OH 43606, USA)

  • Austin Szczublewski

    (EECS Department, The University of Toledo, Toledo, OH 43606, USA)

  • Aidan Fox

    (EECS Department, The University of Toledo, Toledo, OH 43606, USA)

  • Sadab Mahmud

    (EECS Department, The University of Toledo, Toledo, OH 43606, USA)

  • Ahmad Javaid

    (EECS Department, The University of Toledo, Toledo, OH 43606, USA)

  • Temitayo O. Olowu

    (Idaho National Laboratory, Idaho Falls, ID 83415, USA)

  • Tyler Westover

    (Idaho National Laboratory, Idaho Falls, ID 83415, USA)

  • Raghav Khanna

    (EECS Department, The University of Toledo, Toledo, OH 43606, USA)

Abstract

This paper investigates the challenges and solutions associated with integrating a hydrogen-generating nuclear-renewable integrated energy system (NR-IES) under a transactive energy framework. The proposed system directs excess nuclear power to hydrogen production during periods of low grid demand while utilizing renewables to maintain grid stability. Using digital real-time simulation (DRTS) in the Typhoon HIL 404 model, the dynamic interactions between nuclear power plants, electrolyzers, and power grids are analyzed to mitigate issues such as harmonic distortion, power quality degradation, and low power factor caused by large non-linear loads. A three-phase power conversion system is modeled using the Typhoon HIL 404 model and includes a generator, a variable load, an electrolyzer, and power filters. Active harmonic filters (AHFs) and hybrid active power filters (HAPFs) are implemented to address harmonic mitigation and reactive power compensation. The results reveal that the HAPF topology effectively balances cost efficiency and performance and significantly reduces active filter current requirements compared to AHF-only systems. During maximum electrolyzer operation at 4 MW, the grid frequency dropped below 59.3 Hz without filtering; however, the implementation of power filters successfully restored the frequency to 59.9 Hz, demonstrating its effectiveness in maintaining grid stability. Future work will focus on integrating a deep reinforcement learning (DRL) framework with real-time simulation and optimizing real-time power dispatch, thus enabling a scalable, efficient NR-IES for sustainable energy markets.

Suggested Citation

  • Sushanta Gautam & Austin Szczublewski & Aidan Fox & Sadab Mahmud & Ahmad Javaid & Temitayo O. Olowu & Tyler Westover & Raghav Khanna, 2025. "Digital Real-Time Simulation and Power Quality Analysis of a Hydrogen-Generating Nuclear-Renewable Integrated Energy System," Energies, MDPI, vol. 18(4), pages 1-22, February.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:4:p:937-:d:1592071
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    References listed on IDEAS

    as
    1. Stephen Hancock & Tyler Westover, 2022. "Simulation of 15% and 50% Thermal Power Dispatch to an Industrial Facility Using a Flexible Generic Full-Scope Pressurized Water Reactor Plant Simulator," Energies, MDPI, vol. 15(3), pages 1-15, February.
    2. Poudineh, Rahmatallah & Jamasb, Tooraj, 2014. "Distributed generation, storage, demand response and energy efficiency as alternatives to grid capacity enhancement," Energy Policy, Elsevier, vol. 67(C), pages 222-231.
    3. Yi, Zonggen & Luo, Yusheng & Westover, Tyler & Katikaneni, Sravya & Ponkiya, Binaka & Sah, Suba & Mahmud, Sadab & Raker, David & Javaid, Ahmad & Heben, Michael J. & Khanna, Raghav, 2022. "Deep reinforcement learning based optimization for a tightly coupled nuclear renewable integrated energy system," Applied Energy, Elsevier, vol. 328(C).
    4. Mahmud, Sadab & Ponkiya, Binaka & Katikaneni, Sravya & Pandey, Srijana & Mattimadugu, Kranthikiran & Yi, Zonggen & Walker, Victor & Wang, Congjian & Westover, Tyler & Javaid, Ahmad Y. & Heben, Michael, 2024. "Design and optimization of a modular hydrogen-based integrated energy system to maximize revenue via nuclear-renewable sources," Energy, Elsevier, vol. 313(C).
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