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Stochastic optimal scheduling strategy of cross-regional carbon emissions trading and green certificate trading market based on Stackelberg game

Author

Listed:
  • Yan, Sizhe
  • Wang, Weiqing
  • Li, Xiaozhu
  • Lv, Haipeng
  • Fan, Tianyuan
  • Aikepaer, Sumaiya

Abstract

Under the urgent goal of "carbon peaking and carbon neutralization" in China and based on the distribution characteristics of renewable energy, it is essential to promote the large-scale consumption of renewable energy and increase the proportion of large-scale renewable energy in market transactions. Therefore, a stochastic optimal scheduling model that combines the Stackelberg game, cross-regional carbon emissions trading, and tradable green certificate transaction to consider the uncertainty of renewable energy power generation is proposed. To encourage more market participants to participate in the tradable green certificate trading, the model uses Stackelberg game theory to analyze the complex interest relationship between different market participants and obtain a scheduling scheme that balances the interests of different participants. To give full play to the role of the trading mechanism on the cross-regional system, the tradable green certificate trading mechanism and the carbon emission trading mechanism are combined to optimize the overall allocation of green certificates and carbon emission rights, to stimulate renewable energy generation, limit the carbon emission of traditional thermal power units and promote energy conversion. Finally, the modified IEEE 39-bus system and Hami power grid (in Western China) are used as examples to illustrate the feasibility and effectiveness of the proposed scheduling model. The results show that the proposed strategy improves the cross-regional system economy and reduces emissions, fully reflects the monetary value of the external characteristics of renewable energy, guides renewable energy investment and power grid planning, and promotes the consumption of renewable energy.

Suggested Citation

  • Yan, Sizhe & Wang, Weiqing & Li, Xiaozhu & Lv, Haipeng & Fan, Tianyuan & Aikepaer, Sumaiya, 2023. "Stochastic optimal scheduling strategy of cross-regional carbon emissions trading and green certificate trading market based on Stackelberg game," Renewable Energy, Elsevier, vol. 219(P1).
    • Handle: RePEc:eee:renene:v:219:y:2023:i:p1:s0960148123011837
    DOI: 10.1016/j.renene.2023.119268
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    as
    1. Ming, Zeng & Lilin, Peng & Qiannan, Fan & Yingjie, Zhang, 2016. "Trans-regional electricity transmission in China: Status, issues and strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 572-583.
    2. Unger, Thomas & Ahlgren, Erik O., 2005. "Impacts of a common green certificate market on electricity and CO2-emission markets in the Nordic countries," Energy Policy, Elsevier, vol. 33(16), pages 2152-2163, November.
    3. Tan, Qinliang & Ding, Yihong & Ye, Qi & Mei, Shufan & Zhang, Yimei & Wei, Yongmei, 2019. "Optimization and evaluation of a dispatch model for an integrated wind-photovoltaic-thermal power system based on dynamic carbon emissions trading," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    4. Wu, Yunna & Xu, Chuanbo & Zhang, Ting, 2018. "Evaluation of renewable power sources using a fuzzy MCDM based on cumulative prospect theory: A case in China," Energy, Elsevier, vol. 147(C), pages 1227-1239.
    5. Li, Ying & Lukszo, Zofia & Weijnen, Margot, 2016. "The impact of inter-regional transmission grid expansion on China’s power sector decarbonization," Applied Energy, Elsevier, vol. 183(C), pages 853-873.
    6. Feijoo, Felipe & Das, Tapas K., 2015. "Emissions control via carbon policies and microgrid generation: A bilevel model and Pareto analysis," Energy, Elsevier, vol. 90(P2), pages 1545-1555.
    7. Dongqi Liu & Yaonan Wang & Yongpeng Shen, 2016. "Electric Vehicle Charging and Discharging Coordination on Distribution Network Using Multi-Objective Particle Swarm Optimization and Fuzzy Decision Making," Energies, MDPI, vol. 9(3), pages 1-17, March.
    8. Li, Xiaozhu & Wang, Weiqing & Wang, Haiyun, 2021. "A novel bi-level robust game model to optimize a regionally integrated energy system with large-scale centralized renewable-energy sources in Western China," Energy, Elsevier, vol. 228(C).
    9. Kabir, M.N. & Mishra, Y. & Bansal, R.C., 2016. "Probabilistic load flow for distribution systems with uncertain PV generation," Applied Energy, Elsevier, vol. 163(C), pages 343-351.
    10. Jin, Jingliang & Zhou, Peng & Li, Chenyu & Guo, Xiaojun & Zhang, Mingming, 2019. "Low-carbon power dispatch with wind power based on carbon trading mechanism," Energy, Elsevier, vol. 170(C), pages 250-260.
    11. Tu, Qiang & Mo, Jianlei & Betz, Regina & Cui, Lianbiao & Fan, Ying & Liu, Yu, 2020. "Achieving grid parity of solar PV power in China- The role of Tradable Green Certificate," Energy Policy, Elsevier, vol. 144(C).
    12. Tengfei Ma & Junyong Wu & Liangliang Hao & Huaguang Yan & Dezhi Li, 2018. "A Real-Time Pricing Scheme for Energy Management in Integrated Energy Systems: A Stackelberg Game Approach," Energies, MDPI, vol. 11(10), pages 1-19, October.
    13. Chen, J.J. & Qi, B.X. & Peng, K. & Li, Y. & Zhao, Y.L., 2020. "Conditional value-at-credibility for random fuzzy wind power in demand response integrated multi-period economic emission dispatch," Applied Energy, Elsevier, vol. 261(C).
    14. Tan, Qinliang & Ding, Yihong & Zheng, Jin & Dai, Mei & Zhang, Yimei, 2021. "The effects of carbon emissions trading and renewable portfolio standards on the integrated wind–photovoltaic–thermal power-dispatching system: Real case studies in China," Energy, Elsevier, vol. 222(C).
    15. McPherson, Madeleine & Karney, Bryan, 2017. "A scenario based approach to designing electricity grids with high variable renewable energy penetrations in Ontario, Canada: Development and application of the SILVER model," Energy, Elsevier, vol. 138(C), pages 185-196.
    16. Qu, Kaiping & Zheng, Baomin & Yu, Tao & Li, Haofei, 2019. "Convex decoupled-synergetic strategies for robust multi-objective power and gas flow considering power to gas," Energy, Elsevier, vol. 168(C), pages 753-771.
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    1. Guo, Xiaopeng & Zhang, Xinyue & Zhang, Xingping, 2024. "Incentive-oriented power‑carbon emissions trading-tradable green certificate integrated market mechanisms using multi-agent deep reinforcement learning," Applied Energy, Elsevier, vol. 357(C).

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