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Optimization model of low-carbon technology adoption timing for coal power under decarbonization and flexibility demand: Empirical study in Beijing-Tianjin-Hebei region, China

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  • Shan, Zijing
  • Tan, Qinliang
  • Dong, Haoxin
  • Ding, Yihong

Abstract

Substituting renewable energy for coal power under the carbon neutrality goal is an inevitable path for power system transformation, while the high share of renewable energy leads to a rapid rise in system flexibility demand. Currently, coal-fired power is still one of the most economical and reliable large-scale flexible resources in China. Therefore, the issue of how to mitigate the conflict between cleanliness and flexibility for coal-fired power is urgent to be solved. Accordingly, this paper established an optimization framework for the retirement and technology adoption of coal-fired power units with high spatial-temporal resolution, and the regional carbon emission budget is estimated from a top-down perspective. Secondly, a dynamic carbon quota allocation method considering technological innovation and adoption is proposed. The carbon trading cost of the units is evaluated from a bottom-up perspective, to realize the interaction between the obligatory policy constraints of the top-level target and the flexible incentives of the market mechanism. Finally, the empirical analysis was conducted in the Beijing-Tianjin-Hebei region of China. The optimal solution achieved by proposed method results in a substantial 27% reduction in total costs while keeping the increase in carbon emissions below 3%. By analyzing the dynamic evolution path of coal and the scale of diffusion of multi-type technologies, the differences in the roles coal power assuming at various stages of decarbonization are discussed. The robustness of the model and the validity of the proposed method were verified by comparing the dynamic/static carbon quota allocation. Overall, this study provides an effective optimization model for investigating the low-carbon technology adoption timing for coal power in Beijing-Tianjin-Hebei region, and offers valuable insights for other coal-dominated emerging economies seeking for power system transformation roadmap in the forthcoming net-zero carbon age.

Suggested Citation

  • Shan, Zijing & Tan, Qinliang & Dong, Haoxin & Ding, Yihong, 2024. "Optimization model of low-carbon technology adoption timing for coal power under decarbonization and flexibility demand: Empirical study in Beijing-Tianjin-Hebei region, China," Applied Energy, Elsevier, vol. 358(C).
    • Handle: RePEc:eee:appene:v:358:y:2024:i:c:s0306261924000308
    DOI: 10.1016/j.apenergy.2024.122647
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    References listed on IDEAS

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    1. Tan, Qinliang & Han, Jian & Liu, Yuan, 2023. "Examining the synergistic diffusion process of carbon capture and renewable energy generation technologies under market environment: A multi-agent simulation analysis," Energy, Elsevier, vol. 282(C).
    2. Zhi, Zhang & Ming, Zhou & Bo, Yuan & Zun, Guo & Zhaoyuan, Wu & Gengyin, Li, 2023. "Multipath retrofit planning approach for coal-fired power plants in low-carbon power system transitions: Shanxi Province case in China," Energy, Elsevier, vol. 275(C).
    3. Ryna Yiyun Cui & Nathan Hultman & Diyang Cui & Haewon McJeon & Sha Yu & Morgan R. Edwards & Arijit Sen & Kaihui Song & Christina Bowman & Leon Clarke & Junjie Kang & Jiehong Lou & Fuqiang Yang & Jiaha, 2021. "A plant-by-plant strategy for high-ambition coal power phaseout in China," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    4. Abdin, Adam F. & Caunhye, Aakil & Zio, Enrico & Cardin, Michel-Alexandre, 2022. "Optimizing generation expansion planning with operational uncertainty: A multistage adaptive robust approach," Applied Energy, Elsevier, vol. 306(PA).
    5. Maulén, Lucas & Castro, Margarita & Lorca, Álvaro & Negrete-Pincetic, Matías, 2023. "Optimization-based expansion planning for power and hydrogen systems with feedback from a unit commitment model," Applied Energy, Elsevier, vol. 343(C).
    6. Ma, Huan & Sun, Qinghan & Chen, Lei & Chen, Qun & Zhao, Tian & He, Kelun & Xu, Fei & Min, Yong & Wang, Shunjiang & Zhou, Guiping, 2023. "Cogeneration transition for energy system decarbonization: From basic to flexible and complementary multi-energy sources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    7. Zhang, Xiaoyue & Huang, Guohe & Xie, Yulei & Liu, Lirong & Song, Tangnyu, 2022. "A coupled non-deterministic optimization and mixed-level factorial analysis model for power generation expansion planning – A case study of Jing-Jin-Ji metropolitan region, China," Applied Energy, Elsevier, vol. 311(C).
    8. Du, Binglin & Liu, Pei & Li, Zheng, 2023. "Coal power plants transition based on joint planning of power and central heating sectors: A case study of China," Energy, Elsevier, vol. 283(C).
    9. Gabrielli, Paolo & Gazzani, Matteo & Mazzotti, Marco, 2018. "Electrochemical conversion technologies for optimal design of decentralized multi-energy systems: Modeling framework and technology assessment," Applied Energy, Elsevier, vol. 221(C), pages 557-575.
    10. Neetzow, Paul, 2021. "The effects of power system flexibility on the efficient transition to renewable generation," Applied Energy, Elsevier, vol. 283(C).
    11. Greg Muttitt & James Price & Steve Pye & Dan Welsby, 2023. "Socio-political feasibility of coal power phase-out and its role in mitigation pathways," Nature Climate Change, Nature, vol. 13(2), pages 140-147, February.
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