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Costs and CO2 emissions of technological transformation in China's power industry: The impact of market regulation and assistive technologies

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  • Zhang, Yingnan
  • Wu, Guanqi
  • Zhang, Bin

Abstract

This study explores the transformation pathways of China's power industry from 2020 to 2060 using the "Dynamic System and Low Emissions Analysis Platform" (SD-LEAP) model. The analysis assumes market regulation mechanisms include the carbon emission trading (CET) and the tradable green certificate (TGC) market, while assistive technologies encompass Carbon Capture, Utilization, and Storage (CCUS) and energy storage. The study evaluates costs and CO2 emissions under these influences. Our findings indicate higher CET prices reduce fossil and biomass energy capacity, while higher TGC prices boost clean energy capacity. CCUS implementation and increased CET prices lower fossil power generation costs. Conversely, higher TGC prices and advances in energy storage raise renewable energy capacity and costs by 2060. Combined market regulations and assistive technologies are projected to reduce CO2 emissions by 509.3 to 1466.3 million tons by 2060, with policy recommendations for supporting China's power system development.

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  • Zhang, Yingnan & Wu, Guanqi & Zhang, Bin, 2025. "Costs and CO2 emissions of technological transformation in China's power industry: The impact of market regulation and assistive technologies," Structural Change and Economic Dynamics, Elsevier, vol. 73(C), pages 211-222.
    • Handle: RePEc:eee:streco:v:73:y:2025:i:c:p:211-222
    DOI: 10.1016/j.strueco.2025.01.001
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    1. Zhou, Bo & Zhang, Cheng & Wang, Qunwei & Zhou, Dequn, 2020. "Does emission trading lead to carbon leakage in China? Direction and channel identifications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    2. Hayashi, Daisuke & Huenteler, Joern & Lewis, Joanna I., 2018. "Gone with the wind: A learning curve analysis of China's wind power industry," Energy Policy, Elsevier, vol. 120(C), pages 38-51.
    3. Zhang, Bin & Xin, Qingyao & Chen, Siyuan & Yang, Zhiying & Wang, Zhaohua, 2024. "Urban spatial structure and commuting-related carbon emissions in China: Do monocentric cities emit more?," Energy Policy, Elsevier, vol. 186(C).
    4. Richard Blundell & Monica Costa Dias, 2009. "Alternative Approaches to Evaluation in Empirical Microeconomics," Journal of Human Resources, University of Wisconsin Press, vol. 44(3).
    5. John E. T. Bistline & Geoffrey J. Blanford, 2021. "Impact of carbon dioxide removal technologies on deep decarbonization of the electric power sector," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    6. Agnolucci, Paolo, 2007. "The effect of financial constraints, technological progress and long-term contracts on tradable green certificates," Energy Policy, Elsevier, vol. 35(6), pages 3347-3359, June.
    7. Hong, Sungjun & Chung, Yanghon & Kim, Jongwook & Chun, Dongphil, 2016. "Analysis on the level of contribution to the national greenhouse gas reduction target in Korean transportation sector using LEAP model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 549-559.
    8. Li, Dan & Li, Yijun & Wang, Chaoqun & Chen, Min & Wu, Qi, 2023. "Forecasting carbon prices based on real-time decomposition and causal temporal convolutional networks," Applied Energy, Elsevier, vol. 331(C).
    9. David E. H. J. Gernaat & Harmen Sytze Boer & Vassilis Daioglou & Seleshi G. Yalew & Christoph Müller & Detlef P. Vuuren, 2021. "Climate change impacts on renewable energy supply," Nature Climate Change, Nature, vol. 11(2), pages 119-125, February.
    10. Feng, Tian-tian & Yang, Yi-sheng & Yang, Yu-heng, 2018. "What will happen to the power supply structure and CO2 emissions reduction when TGC meets CET in the electricity market in China?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 92(C), pages 121-132.
    11. Chen, Qixin & Kang, Chongqing & Xia, Qing & Guan, Dabo, 2011. "Preliminary exploration on low-carbon technology roadmap of China’s power sector," Energy, Elsevier, vol. 36(3), pages 1500-1512.
    12. Liu, Huachen & Lu, Hao & Hu, Heng, 2024. "CO2 capture and mineral storage: State of the art and future challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    13. Vu, Thang Toan & Lim, Young-Il & Song, Daesung & Mun, Tae-Young & Moon, Ji-Hong & Sun, Dowon & Hwang, Yoon-Tae & Lee, Jae-Goo & Park, Young Cheol, 2020. "Techno-economic analysis of ultra-supercritical power plants using air- and oxy-combustion circulating fluidized bed with and without CO2 capture," Energy, Elsevier, vol. 194(C).
    14. Zhang, Bin & Zhang, Yingnan & Li, Jia & Song, Yanwu & Wang, Zhaohua, 2023. "Does the energy efficiency of buildings bring price premiums? Evidence from urban micro-level energy data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 181(C).
    15. Qi, Shaozhou & Cheng, Shihan & Tan, Xiujie & Feng, Shenghao & Zhou, Qi, 2022. "Predicting China's carbon price based on a multi-scale integrated model," Applied Energy, Elsevier, vol. 324(C).
    16. Zhang, Yingnan & Hu, Wei & Tao, Yirui & Zhang, Bin, 2025. "How does smart artificial intelligence influence energy system resilience? Evidence from energy vulnerability assessments in G20 countries," Energy, Elsevier, vol. 314(C).
    17. Zhang, Shengling & Wang, Yao & Hao, Yu & Liu, Zhiwei, 2021. "Shooting two hawks with one arrow: Could China's emission trading scheme promote green development efficiency and regional carbon equality?," Energy Economics, Elsevier, vol. 101(C).
    18. Zeng, Lijun & Wang, Jiafeng & Zhao, Laijun, 2022. "An inter-provincial tradable green certificate futures trading model under renewable portfolio standard policy," Energy, Elsevier, vol. 257(C).
    19. Wang, Yun & Xie, Haipeng & Sun, Xiaotian & Tang, Lingfeng & Bie, Zhaohong, 2022. "A cross-chain enabled day-ahead collaborative power-carbon-TGC market," Energy, Elsevier, vol. 258(C).
    20. McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March.
    21. Kazemi, Abolghasem & Moreno, Jovita & Iribarren, Diego, 2022. "Techno-economic comparison of optimized natural gas combined cycle power plants with CO2 capture," Energy, Elsevier, vol. 255(C).
    22. Aslani, Alireza & Helo, Petri & Naaranoja, Marja, 2014. "Role of renewable energy policies in energy dependency in Finland: System dynamics approach," Applied Energy, Elsevier, vol. 113(C), pages 758-765.
    23. Guerra, K. & Gutiérrez-Alvarez, R. & Guerra, Omar J. & Haro, P., 2023. "Opportunities for low-carbon generation and storage technologies to decarbonise the future power system," Applied Energy, Elsevier, vol. 336(C).
    24. Lohwasser, Richard & Madlener, Reinhard, 2013. "Relating R&D and investment policies to CCS market diffusion through two-factor learning," Energy Policy, Elsevier, vol. 52(C), pages 439-452.
    25. Hu, Yingying & Wu, Wei, 2023. "Can fossil energy make a soft landing？— the carbon-neutral pathway in China accompanying CCS," Energy Policy, Elsevier, vol. 174(C).
    26. Zhang, Bin & Niu, Niu & Li, Hao & Wang, Zhaohua, 2023. "Assessing the efforts of coal phaseout for carbon neutrality in China," Applied Energy, Elsevier, vol. 352(C).
    27. Park, Nyun-Bae & Yun, Sun-Jin & Jeon, Eui-Chan, 2013. "An analysis of long-term scenarios for the transition to renewable energy in the Korean electricity sector," Energy Policy, Elsevier, vol. 52(C), pages 288-296.
    28. Castrejon-Campos, Omar & Aye, Lu & Hui, Felix Kin Peng, 2022. "Effects of learning curve models on onshore wind and solar PV cost developments in the USA," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    29. Winskel, Mark & Markusson, Nils & Jeffrey, Henry & Candelise, Chiara & Dutton, Geoff & Howarth, Paul & Jablonski, Sophie & Kalyvas, Christos & Ward, David, 2014. "Learning pathways for energy supply technologies: Bridging between innovation studies and learning rates," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 96-114.
    30. Zhang, Feng & Li, Yun & Li, Fengling & Yuan, Jiahang & Li, Yanbin, 2022. "Decision-making behavior of power suppliers in the green certificate market: A system dynamics analysis," Energy Policy, Elsevier, vol. 171(C).
    31. Rubin, Edward S. & Azevedo, Inês M.L. & Jaramillo, Paulina & Yeh, Sonia, 2015. "A review of learning rates for electricity supply technologies," Energy Policy, Elsevier, vol. 86(C), pages 198-218.
    32. Li, Mingquan & Shan, Rui & Virguez, Edgar & Patiño-Echeverri, Dalia & Gao, Shuo & Ma, Haichao, 2022. "Energy storage reduces costs and emissions even without large penetration of renewable energy: The case of China Southern Power Grid," Energy Policy, Elsevier, vol. 161(C).
    33. Helgesen, Per Ivar & Tomasgard, Asgeir, 2018. "An equilibrium market power model for power markets and tradable green certificates, including Kirchhoff's Laws and Nash-Cournot competition," Energy Economics, Elsevier, vol. 70(C), pages 270-288.
    34. Zhang, Yue-Jun & Wang, Wei, 2021. "How does China's carbon emissions trading (CET) policy affect the investment of CET-covered enterprises?," Energy Economics, Elsevier, vol. 98(C).
    35. Zhang, Mingshun & Wang, Mujie & Jin, Wei & Xia-Bauer, Chun, 2018. "Managing energy efficiency of buildings in China: A survey of energy performance contracting (EPC) in building sector," Energy Policy, Elsevier, vol. 114(C), pages 13-21.
    36. Sarah M. Jordaan & Andrew W. Ruttinger & Kavita Surana & Destenie Nock & Scot M. Miller & Arvind P. Ravikumar, 2022. "Global mitigation opportunities for the life cycle of natural gas-fired power," Nature Climate Change, Nature, vol. 12(11), pages 1059-1067, November.
    37. Zhang, Wen & Wu, Zhibin & Zeng, Xiaojun & Zhu, Changhui, 2023. "An ensemble dynamic self-learning model for multiscale carbon price forecasting," Energy, Elsevier, vol. 263(PC).
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