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Day-ahead optimal dispatch of a virtual power plant in the joint energy-reserve-carbon market

Author

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  • Wei, Xuan
  • Xu, Yinliang
  • Sun, Hongbin
  • Bai, Xiang
  • Chang, Xinyue
  • Xue, Yixun

Abstract

As an efficient technique to manage massive distributed energy resources (DER), the virtual power plant (VPP) can leverage the aggregated flexibility to enhance the economy and security of the system. However, few efforts have been reported on the carbon emission reduction benefit of the VPP. In this paper, a novel incentive mechanism for low-carbon demand response is designed, which is based on dynamic pricing and carbon intensity. Considering the uncertainty of renewable energy output characterized by the chance-constrained approach, a coordinated optimization model in the joint day-ahead energy, reserve and carbon market for the VPP operator and flexible consumers is proposed, including the pre-dispatch model, the energy storage systems (ESSs) incorporated carbon emission flow calculation model, and the bi-level final-dispatch model. Numerical simulations of both small-scale and large-scale cases demonstrate that the proposed low-carbon dispatch strategy can boost the payoff of the VPP operator, reduce carbon emissions in the joint energy-reserve-carbon market, and improve the robustness of the power system against uncertainty.

Suggested Citation

  • Wei, Xuan & Xu, Yinliang & Sun, Hongbin & Bai, Xiang & Chang, Xinyue & Xue, Yixun, 2024. "Day-ahead optimal dispatch of a virtual power plant in the joint energy-reserve-carbon market," Applied Energy, Elsevier, vol. 356(C).
    • Handle: RePEc:eee:appene:v:356:y:2024:i:c:s0306261923018238
    DOI: 10.1016/j.apenergy.2023.122459
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    Citations

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    Cited by:

    1. Li, Jinchao & Sun, Zihao & Niu, Xiaoxuan & Li, Shiwei, 2024. "Economic optimization scheduling of virtual power plants considering an incentive based tiered carbon price," Energy, Elsevier, vol. 305(C).
    2. Jiang, Yuzheng & Dong, Jun & Huang, Hexiang, 2024. "Optimal bidding strategy for the price-maker virtual power plant in the day-ahead market based on multi-agent twin delayed deep deterministic policy gradient algorithm," Energy, Elsevier, vol. 306(C).
    3. Cao, Jinye & Yang, Dechang & Dehghanian, Payman, 2024. "Cooperative operation for multiple virtual power plants considering energy-carbon trading: A Nash bargaining model," Energy, Elsevier, vol. 307(C).
    4. Khalid, Muhammad, 2024. "A techno-economic framework for optimizing multi-area power dispatch in microgrids with tie-line constraints," Renewable Energy, Elsevier, vol. 231(C).
    5. Hao, Junhong & Feng, Xiaolong & Chen, Xiangru & Jin, Xilin & Wang, Xingce & Hao, Tong & Hong, Feng & Du, Xiaoze, 2024. "Optimal scheduling of active distribution network considering symmetric heat and power source-load spatial-temporal characteristics," Applied Energy, Elsevier, vol. 373(C).

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