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Three-level market optimization model of virtual power plant with carbon capture equipment considering copula–CVaR theory

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  • Tan, Caixia
  • Wang, Jing
  • Geng, Shiping
  • Pu, Lei
  • Tan, Zhongfu

Abstract

To achieve carbon neutrality, promoting clean and renewable energy consumption and reducing CO2 emissions have become important measures. Therefore, virtual power plants (VPPs) containing carbon capture devices have become a research focus. This study first builds a VPP model containing carbon capture devices, analyzes the cooperative operation mode of a carbon capture system and power-to-gas, and develops a comprehensive demand response mechanism for the VPP. Second, owing to the uncertainty of the electricity market clearing price and the natural gas market price, a risk dependence model between electricity price and gas price based on the copula–conditional value-at-risk theory is constructed. Then, a VPP three-level market optimization model considering risk dependence and carbon trading mechanisms is proposed, and an improved collaborative evolutionary algorithm that combines the NSGAII and AGE-MOEA algorithms is used to solve multi-objective problems. Finally, an example of a VPP is used to verify the effectiveness of the model.

Suggested Citation

  • Tan, Caixia & Wang, Jing & Geng, Shiping & Pu, Lei & Tan, Zhongfu, 2021. "Three-level market optimization model of virtual power plant with carbon capture equipment considering copula–CVaR theory," Energy, Elsevier, vol. 237(C).
    • Handle: RePEc:eee:energy:v:237:y:2021:i:c:s0360544221018685
    DOI: 10.1016/j.energy.2021.121620
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    Cited by:

    1. Mei, Shufan & Tan, Qinliang & Liu, Yuan & Trivedi, Anupam & Srinivasan, Dipti, 2023. "Optimal bidding strategy for virtual power plant participating in combined electricity and ancillary services market considering dynamic demand response price and integrated consumption satisfaction," Energy, Elsevier, vol. 284(C).
    2. Mohammad Mohammadi Roozbehani & Ehsan Heydarian-Forushani & Saeed Hasanzadeh & Seifeddine Ben Elghali, 2022. "Virtual Power Plant Operational Strategies: Models, Markets, Optimization, Challenges, and Opportunities," Sustainability, MDPI, vol. 14(19), pages 1-23, September.
    3. Kong, Xiangyu & Lu, Wenqi & Wu, Jianzhong & Wang, Chengshan & Zhao, Xv & Hu, Wei & Shen, Yu, 2023. "Real-time pricing method for VPP demand response based on PER-DDPG algorithm," Energy, Elsevier, vol. 271(C).
    4. Zhao, Kaifang & Qiu, Kai & Yan, Jian & Shaker, Mir Pasha, 2023. "Technical and economic operation of VPPs based on competitive bi–level negotiations," Energy, Elsevier, vol. 282(C).
    5. Lau, Jat-Syu & Jiang, Yihuo & Li, Ziyuan & Qian, Qian, 2023. "Stochastic trading of storage systems in short term electricity markets considering intraday demand response market," Energy, Elsevier, vol. 280(C).
    6. Ju, Liwei & Yin, Zhe & Lu, Xiaolong & Yang, Shenbo & Li, Peng & Rao, Rao & Tan, Zhongfu, 2022. "A Tri-dimensional Equilibrium-based stochastic optimal dispatching model for a novel virtual power plant incorporating carbon Capture, Power-to-Gas and electric vehicle aggregator," Applied Energy, Elsevier, vol. 324(C).
    7. Li, Jiamei & Ai, Qian & Chen, Minyu, 2023. "Strategic behavior modeling and energy management for electric-thermal-carbon-natural gas integrated energy system considering ancillary service," Energy, Elsevier, vol. 278(C).

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