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Research on Day-Ahead Optimal Scheduling Considering Carbon Emission Allowance and Carbon Trading

Author

Listed:
  • Jiangnan Li

    (Shenzhen Power Supply Company, China Southern Power Grid, Shenzhen 518067, China)

  • Tian Mao

    (Electric Power Research Institute, China Southern Power Grid, Guangzhou 510530, China)

  • Guanglei Huang

    (Shenzhen Power Supply Company, China Southern Power Grid, Shenzhen 518067, China)

  • Wenmeng Zhao

    (Electric Power Research Institute, China Southern Power Grid, Guangzhou 510530, China)

  • Tao Wang

    (Electric Power Research Institute, China Southern Power Grid, Guangzhou 510530, China)

Abstract

In the context of the marketization of carbon trading in the power system, it is of great theoretical and practical significance to study a scientific and effective carbon emission quota allocation strategy. To solve this problem, under the current situation of large-scale access to new energy, considering the limitations of the carbon emissions from different emission subjects plus the construction of a carbon trading model among the emission subjects, a day-ahead optimal scheduling method that takes carbon emission quotas and carbon trading into account is proposed. Firstly, carbon transaction cost models of thermal power and wind power are constructed, respectively, and a carbon emission quota allocation strategy based on the entropy method is proposed to redistribute the weights of baseline emission factors for the regional power grid. Then, considering the additional carbon emissions of conventional thermal power units caused by wind power access, the carbon trading costs of different types of generation units are calculated on the basis of carbon trading price prediction. Thereafter, a day-ahead optimal scheduling model considering carbon emissions trading is constructed with the objective of minimizing the total cost of the system in the scheduling period. The model is solved as an MINLP problem based on MATLAB 2016a software utilizing CPLEX 12.4. Simulation results verify the correctness and effectiveness of the proposed method.

Suggested Citation

  • Jiangnan Li & Tian Mao & Guanglei Huang & Wenmeng Zhao & Tao Wang, 2023. "Research on Day-Ahead Optimal Scheduling Considering Carbon Emission Allowance and Carbon Trading," Sustainability, MDPI, vol. 15(7), pages 1-23, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:7:p:6108-:d:1113547
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    References listed on IDEAS

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    1. Ma, Minda & Cai, Wei & Cai, Weiguang, 2018. "Carbon abatement in China's commercial building sector: A bottom-up measurement model based on Kaya-LMDI methods," Energy, Elsevier, vol. 165(PA), pages 350-368.
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    Cited by:

    1. Yi Zhang & Tian Lan & Wei Hu, 2023. "A Two-Stage Robust Optimization Microgrid Model Considering Carbon Trading and Demand Response," Sustainability, MDPI, vol. 15(19), pages 1-22, October.
    2. Boyu Zhu & Dazhi Wang, 2024. "Master–Slave Game Optimal Scheduling for Multi-Agent Integrated Energy System Based on Uncertainty and Demand Response," Sustainability, MDPI, vol. 16(8), pages 1-27, April.
    3. Li, Ruhuan & Zhou, Jun & Qiu, Zitong & Li, Haonan & Li, Jinman & Wu, Ji & Wu, Kai, 2025. "Bi-level optimization of hybrid energy conversion system based on a multi-distinct low-carbon microgrid," Renewable Energy, Elsevier, vol. 239(C).

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