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Distributed energy-reserve Co-Optimization of electricity and natural gas systems with multi-type reserve resources

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  • Wu, Gang
  • Xiang, Yue
  • Liu, Junyong
  • Shen, Xiaodong
  • Cheng, Shikun
  • Hong, Bowen
  • Jawad, Shafqat

Abstract

An energy-reserve co-optimization model for electricity and natural gas systems with multi-type reserve resources is proposed. Considering the reserve capacity provided by generating units is difficult to meet the large-scale regulation requirements caused by wind power, load demand forecast errors and unexpected contingencies, a reserve scheme with multi-type reserve resources including generating units, energy storage devices, and interruptible loads is designed. Besides, the transmission capability of reserve capacity in the electricity and gas networks when facing forecast errors and contingencies is considered in the proposed model. To protect information privacy of different energy systems, an improved alternating direction method of multipliers (ADMM) is adopted to solve the energy-reserve co-optimization model. The feasibility and effectiveness of the proposed model and method are verified on a modified IEEE 24-bus power system and 6-node natural gas systems.

Suggested Citation

  • Wu, Gang & Xiang, Yue & Liu, Junyong & Shen, Xiaodong & Cheng, Shikun & Hong, Bowen & Jawad, Shafqat, 2020. "Distributed energy-reserve Co-Optimization of electricity and natural gas systems with multi-type reserve resources," Energy, Elsevier, vol. 207(C).
  • Handle: RePEc:eee:energy:v:207:y:2020:i:c:s0360544220313360
    DOI: 10.1016/j.energy.2020.118229
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    References listed on IDEAS

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    7. Hou, Yanqiu & Bao, Minglei & Sang, Maosheng & Ding, Yi, 2024. "A market framework to exploit the multi-energy operating reserve of smart energy hubs in the integrated electricity-gas systems," Applied Energy, Elsevier, vol. 357(C).
    8. Yan, Zhongzhen & Zhu, Xinyuan & Chang, Yiming & Wang, Xianglong & Ye, Zhiwei & Xu, Zhigang & Fars, Ashk, 2023. "Renewable energy effects on energy management based on demand response in microgrids environment," Renewable Energy, Elsevier, vol. 213(C), pages 205-217.
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