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Analysis of regional electric vehicle aggregation response behavior in the coupling electricity and carbon markets

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  • Wang, Jun
  • Meng, Jiajun
  • Li, Hongyan
  • Xu, Xiao

Abstract

As electric vehicles (EVs) increasingly permeate distribution networks (DNs), harmonizing electricity and carbon dual pricing mechanisms becomes pivotal for facilitating orderly EV charging and advancing the coordinated evolution of electricity market (EM) and carbon market (CM). This paper proposes an integrated framework coupling demand response (DR) strategies with dual pricing mechanisms by formulating a tiered reward-penalty carbon pricing scheme alongside an adaptive time-of-use (TOU) pricing approach to guide aggregated EV charging behaviors. The comparative analysis illustrates that the proposed dual pricing mechanism substantially outperforms tiered reward-free carbon pricing schemes, notably reducing the carbon trading costs of independent power producers (IPPs) by approximately 87.85 %. A multi-objective optimization (MOO) problem is formulated and solved utilizing the non-dominated sorting genetic algorithm II (NSGA-II) and multi-objective particle swarm optimization (MOPSO). Results confirm the marked superiority of NSGA-II over MOPSO, achieving approximately 93.32 % improvement in solution uniformity according to the spacing metric (SP) and demonstrating about 41.37 % greater solution diversity based on the diversification metric (DM). Furthermore, techno-economic analyses substantiate that the proposed approach effectively fosters sustainable energy system development, enhances environmental sustainability, and significantly improves the EV user experience.

Suggested Citation

  • Wang, Jun & Meng, Jiajun & Li, Hongyan & Xu, Xiao, 2025. "Analysis of regional electric vehicle aggregation response behavior in the coupling electricity and carbon markets," Energy, Elsevier, vol. 326(C).
    • Handle: RePEc:eee:energy:v:326:y:2025:i:c:s0360544225015567
    DOI: 10.1016/j.energy.2025.135914
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    1. Gao, Shuang & Huang, Shengyu & Jin, Xiaolong & Jia, Hongjie & Zhao, Yuming & Tang, Wenjun, 2025. "Cloud-edge collaborative optimal control strategy for virtually aggregated EV charging facilities in a market environment," Energy, Elsevier, vol. 337(C).
    2. Meng, Yunfan & Sun, Yonghui & Zhao, Liang & Yin, Chenxu & Sheng, Fan, 2025. "A hierarchical robust scheduling framework for electric vehicle aggregators in coupled spot and ancillary service markets," Energy, Elsevier, vol. 332(C).
    3. Chao Yan & Jianyun Xu & Chunrui Li & Qilin Han & Hongwei Li & Jun Wang, 2025. "Carbon-Aware Dispatch of Industrial Park Energy Systems with Demand Response and Ladder-Type Carbon Trading," Sustainability, MDPI, vol. 17(21), pages 1-18, October.
    4. Liang, Yunyang & Pu, Yang & Yu, Mengmeng & Li, Yi-Chang & Jiang, Min & Cui, Lijie & Xiong, Xiaoqin & Jin, Zhong, 2025. "A dual carbon reward mechanism for electric vehicle charging scheduling based on multi-level Stackelberg game," Energy, Elsevier, vol. 337(C).

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