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Demand Management for Resilience Enhancement of Integrated Energy Distribution System against Natural Disasters

Author

Listed:
  • Yuting Xu

    (China Electric Power Research Institute Co., Ltd., Beijing 100192, China)

  • Songsong Chen

    (China Electric Power Research Institute Co., Ltd., Beijing 100192, China)

  • Shiming Tian

    (China Electric Power Research Institute Co., Ltd., Beijing 100192, China)

  • Feixiang Gong

    (China Electric Power Research Institute Co., Ltd., Beijing 100192, China)

Abstract

For energy sustainability, the integrated energy distribution system (IEDS) is an efficient and clean energy system, which is based on the coordinated operation of a power distribution network, a gas distribution network and a district heating system. In this paper, considering the damage of natural disasters to IEDS, a demand management strategy is proposed to improve resilience of IEDS and ensure stable operation, which is divided into three stages. In the first stage, the electricity, natural gas and thermal energy are co-optimized in the simulating fault state to develop the importance ranking of transmission lines and gas pipelines. In the second stage, the natural disasters are classified as surface natural disasters and geological natural disasters. According to the types of natural disasters, the demand management strategy includes semi-emergency demand management scheme and full-emergency demand management scheme in the electrical resilience mode and the integrated resilience mode, respectively. In the third stage, the non-sequential Monte-Carlo simulation and scenario reduction algorithm are applied to describe potential natural disaster scenarios. According to the importance ranking of transmission lines and gas pipelines, a demand management strategy is formulated. Finally, the proposed strategy is applied on an IEEE 33-bus power system and a 19-node natural gas system. Its effectiveness is verified by numerical case studies.

Suggested Citation

  • Yuting Xu & Songsong Chen & Shiming Tian & Feixiang Gong, 2021. "Demand Management for Resilience Enhancement of Integrated Energy Distribution System against Natural Disasters," Sustainability, MDPI, vol. 14(1), pages 1-18, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2021:i:1:p:5-:d:707193
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    References listed on IDEAS

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    1. Jin, Xiaolong & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Xu, Xiandong & Yu, Xiaodan, 2016. "Optimal day-ahead scheduling of integrated urban energy systems," Applied Energy, Elsevier, vol. 180(C), pages 1-13.
    2. Shulin Wang & Yongtao Li & Mahfuzul Haque, 2019. "Evidence on the Impact of Winter Heating Policy on Air Pollution and Its Dynamic Changes in North China," Sustainability, MDPI, vol. 11(10), pages 1-15, May.
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