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Pre-Disaster Optimal Operation Strategy for Hydrogen-Fuel-Based Isolated Power System with Disaster Uncertainties

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  • Junhui Yu

    (Qinghai Key Lab of Efficient Utilization of Clean Energy, School of Energy and Electrical Engineering, University of Qinghai, Xining 810016, China)

  • Yan Yang

    (Qinghai Key Lab of Efficient Utilization of Clean Energy, School of Energy and Electrical Engineering, University of Qinghai, Xining 810016, China)

  • Zhiyong Li

    (Department of Computer Technology and Application, Qinghai University, Xining 810016, China)

  • Wenbin Wu

    (Qinghai Key Lab of Efficient Utilization of Clean Energy, School of Energy and Electrical Engineering, University of Qinghai, Xining 810016, China)

Abstract

The increasing occurrence of severe weather phenomena presents substantial difficulties for electricity distribution systems. This study investigates the integration of hydrogen production plants (HPPs) into power distribution networks to bolster resilience against the increasing frequency of extreme weather events. It highlights the innovative use of hydrogen, generated from renewable sources, as an energy storage medium to ensure a stable power supply during disruptions. By employing stochastic optimization, the study aims to effectively manage hydrogen production and utilization, considering uncertainties in disaster scenarios and energy demands. It addresses critical research gaps, such as the lack of focus on pre-disaster preventive scheduling using hydrogen, the under-explored application of stochastic optimization in such contexts, and the predominance of real-time response strategies over pre-emptive measures. This approach significantly advances current understanding by proposing novel strategies that leverage hydrogen production and sophisticated optimization to enhance the resilience of power networks against extreme weather events. In some scenarios, using our method can reduce the cost of pre-disaster prevention by approximately 15.68% while ensuring that the disaster recovery effect remains unchanged.

Suggested Citation

  • Junhui Yu & Yan Yang & Zhiyong Li & Wenbin Wu, 2024. "Pre-Disaster Optimal Operation Strategy for Hydrogen-Fuel-Based Isolated Power System with Disaster Uncertainties," Sustainability, MDPI, vol. 16(9), pages 1-18, April.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:9:p:3636-:d:1383581
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    References listed on IDEAS

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    1. Antonio J. Conejo & Miguel Carrión & Juan M. Morales, 2010. "Decision Making Under Uncertainty in Electricity Markets," International Series in Operations Research and Management Science, Springer, number 978-1-4419-7421-1, December.
    2. Ding, Tao & Lin, Yanling & Bie, Zhaohong & Chen, Chen, 2017. "A resilient microgrid formation strategy for load restoration considering master-slave distributed generators and topology reconfiguration," Applied Energy, Elsevier, vol. 199(C), pages 205-216.
    3. Molavi, Anahita & Shi, Jian & Wu, Yiwei & Lim, Gino J., 2020. "Enabling smart ports through the integration of microgrids: A two-stage stochastic programming approach," Applied Energy, Elsevier, vol. 258(C).
    4. Li, Boda & Chen, Ying & Wei, Wei & Hou, Yunhe & Mei, Shengwei, 2022. "Enhancing resilience of emergency heat and power supply via deployment of LNG tube trailers: A mean-risk optimization approach," Applied Energy, Elsevier, vol. 318(C).
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