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Low-Carbon Optimization Scheduling for Systems Considering Carbon Responsibility Allocation and Electric Vehicle Demand Response

Author

Listed:
  • Bin Qian

    (CSG Electric Power Research Institute, Guangzhou 510000, China)

  • Houpeng Hu

    (Guizhou Power Grid Co., Ltd., Guizhou 550000, China)

  • Jianlin Tang

    (CSG Electric Power Research Institute, Guangzhou 510000, China)

  • Yanhong Xiao

    (Guizhou Power Grid Co., Ltd., Guizhou 550000, China)

  • Xiaoming Lin

    (CSG Electric Power Research Institute, Guangzhou 510000, China)

  • Zerui Chen

    (Guizhou Power Grid Co., Ltd., Guizhou 550000, China)

Abstract

To achieve low carbon emissions in the power system and contribute to economic growth, a low-carbon optimization scheduling strategy for a power system, considering carbon responsibility sharing and electric vehicle demand response, is proposed based on the establishment of a flexible-load model guided by carbon potential. Firstly, utilizing the principle of proportional sharing to track carbon emission flow and establish a carbon emission flow model. Secondly, based on the Shapley value carbon responsibility allocation method, the reasonable range of carbon responsibility on each load side is calculated, and a hierarchical carbon price is established. A load aggregator demand response carbon emission model is established using the node carbon potential, and a dual-layer optimization scheduling model for the power system based on the node carbon potential demand response is constructed. The upper layer of the model is the optimal economic dispatch of the power grid operator, and the lower layer is the demand response economic dispatch of the load aggregator. Through numerical verification, the carbon trading model takes into account the system’s carbon emissions and overall operating costs while balancing the system’s low-carbon and economic aspects.

Suggested Citation

  • Bin Qian & Houpeng Hu & Jianlin Tang & Yanhong Xiao & Xiaoming Lin & Zerui Chen, 2025. "Low-Carbon Optimization Scheduling for Systems Considering Carbon Responsibility Allocation and Electric Vehicle Demand Response," Sustainability, MDPI, vol. 17(10), pages 1-22, May.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:10:p:4299-:d:1652213
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    References listed on IDEAS

    as
    1. Ouyang, Tiancheng & Li, Yinxuan & Xie, Shutao & Wang, Chengchao & Mo, Chunlan, 2024. "Low-carbon economic dispatch strategy for integrated power system based on the substitution effect of carbon tax and carbon trading," Energy, Elsevier, vol. 294(C).
    2. Nie, Qingyun & Zhang, Lihui & Tong, Zihao & Dai, Guyu & Chai, Jianxue, 2022. "Cost compensation method for PEVs participating in dynamic economic dispatch based on carbon trading mechanism," Energy, Elsevier, vol. 239(PA).
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