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Robust Optimization of a CCS-P2G Virtual Power Plant Accounting for Penalized Carbon Price

EasyChair Preprint no. 11267

6 pagesDate: November 8, 2023


The virtual power plant (VPP) consisting of power to gas (P2G) and carbon capture system (CCS) can reduce the system carbon emissions and effectively respond to the low-carbon electricity market. However, the fluctuation of carbon price in the carbon trading market affects the carbon capture rate and carbon trading cost of the VPP system, and the uncertainty of renewable energy output in the VPP also affects the optimal scheduling. Therefore, this paper constructs a robust optimal scheduling model of CCS-P2G virtual power plant taking into account the punitive carbon price. In the model, the penalty carbon price increases the price of excessive carbon emission; the volatility of renewable energy output is included in the robust optimization. The simulation results show that compared with the traditional carbon price, the penalty carbon price has a better carbon reduction effect on VPP; the smaller the robustness index in the robust optimization, the more conservative the system is, and the larger the VPP gain is, and vice versa. The model proposed in this paper can efficiently participate in the competition of power market and carbon trading market, and the formulation of reasonable penalty carbon price and robustness index can realize the synergy of economy and low carbon of VPP system.

Keyphrases: carbon trading, electricity-to-gas conversion, robust optimization, virtual power plant, Wind-scenic uncertainty

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Shuangning Ding and Zhiyun Sun and Xiaolong Lu and Qizhen Wei and Hewei Chen and Yuancheng Tang},
  title = {Robust Optimization of a CCS-P2G Virtual Power Plant Accounting for Penalized Carbon Price},
  howpublished = {EasyChair Preprint no. 11267},

  year = {EasyChair, 2023}}
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