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Decentralized day-ahead scheduling of multi-area integrated electricity and natural gas systems considering reserve optimization

Author

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  • Wu, Gang
  • Xiang, Yue
  • Liu, Junyong
  • Gou, Jing
  • Shen, Xiaodong
  • Huang, Yuan
  • Jawad, Shafqat

Abstract

To maximize the benefits of multi-area cooperation and guarantee system reliability, a day-ahead scheduling model for multi-area integrated electricity and natural gas systems (IEGS) considering reserve optimization is proposed in this paper. The reserve scheduling is integrated into the multi-area optimal dispatch model to hedge against the risk caused by the uncertainties in electricity and gas systems. The reserve constraints in electricity and natural gas systems are modeled as probabilistic forms with a predefined confidence level based on chance-constrained programming (CCP). In order to protect the information privacy of each area, the original centralized energy-reserve co-optimization problems are decomposed into several area sub-problems that can be solved independently. Furthermore, the alternating direction method of multipliers (ADMM) with self-adaptive penalty parameters is adopted to solve the proposed model in a decentralized manner. The feasibility and effectiveness of the proposed models and methods are verified in a three-area IEGS.

Suggested Citation

  • Wu, Gang & Xiang, Yue & Liu, Junyong & Gou, Jing & Shen, Xiaodong & Huang, Yuan & Jawad, Shafqat, 2020. "Decentralized day-ahead scheduling of multi-area integrated electricity and natural gas systems considering reserve optimization," Energy, Elsevier, vol. 198(C).
    • Handle: RePEc:eee:energy:v:198:y:2020:i:c:s0360544220303789
    DOI: 10.1016/j.energy.2020.117271
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    References listed on IDEAS

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    3. He, Chuan & Wu, Lei & Liu, Tianqi & Wei, Wei & Wang, Cheng, 2018. "Co-optimization scheduling of interdependent power and gas systems with electricity and gas uncertainties," Energy, Elsevier, vol. 159(C), pages 1003-1015.
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    Cited by:

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    2. Zhou, Dengji & Yan, Siyun & Huang, Dawen & Shao, Tiemin & Xiao, Wang & Hao, Jiarui & Wang, Chen & Yu, Tianqi, 2022. "Modeling and simulation of the hydrogen blended gas-electricity integrated energy system and influence analysis of hydrogen blending modes," Energy, Elsevier, vol. 239(PA).
    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. Qian, Tong & Tang, Wenhu & Wu, Qinghua, 2020. "A fully decentralized dual consensus method for carbon trading power dispatch with wind power," Energy, Elsevier, vol. 203(C).
    5. He, Shuaijia & Gao, Hongjun & Wang, Lingfeng & Xiang, Yingmeng & Liu, Junyong, 2020. "Distributionally robust planning for integrated energy systems incorporating electric-thermal demand response," Energy, Elsevier, vol. 213(C).
    6. Lv, Chaoxian & Liang, Rui & Jin, Wei & Chai, Yuanyuan & Yang, Tiankai, 2022. "Multi-stage resilience scheduling of electricity-gas integrated energy system with multi-level decentralized reserve," Applied Energy, Elsevier, vol. 317(C).
    7. Gan, Wei & Yan, Mingyu & Yao, Wei & Guo, Jianbo & Ai, Xiaomeng & Fang, Jiakun & Wen, Jinyu, 2021. "Decentralized computation method for robust operation of multi-area joint regional-district integrated energy systems with uncertain wind power," Applied Energy, Elsevier, vol. 298(C).
    8. Sayed, Ahmed Rabee & Wang, Cheng & Chen, Sheng & Shang, Ce & Bi, Tianshu, 2021. "Distributionally robust day-ahead operation of power systems with two-stage gas contracting," Energy, Elsevier, vol. 231(C).
    9. Zhang, Mingyang & Zhou, Ming & Wu, Zhaoyuan & Yang, Hongji & Li, Gengyin, 2022. "A ramp capability-aware scheduling strategy for integrated electricity-gas systems," Energy, Elsevier, vol. 241(C).

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