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Analysis of China's olefin industry with a system optimization model – With different scenarios of dynamic oil and coal prices

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  • Xu, Zhongming
  • Zhang, Yaru
  • Fang, Chenhao
  • Yu, Yadong
  • Ma, Tieju

Abstract

Recently, China produces olefins increasingly from coal, although OTO (oil-to-olefins) is still dominating China's olefin industry. With the uncertain future dynamics of oil and coal prices, as well as environmental issues, how should China configure its future olefin industry? And what kind of carbon emission controlling policies should be implemented if more olefins would be produced with CTO (coal-to-olefins) in China? This paper develops a system optimization model to explore these questions. With four different scenarios of oil and coal prices, we first explore the optimal configuration of China's olefin industry without considering controlling carbon emission; then we explore the situation in which new CTO capacity must implement CCS (carbon capture and storage) for controlling carbon emission. The results of our study imply that investing in CTO technology in China is not a wrong direction, especially as a technology stock for energy safety, and it could be a good regulation to require CTO to implement CCS for achieving both economic and environmental values.

Suggested Citation

  • Xu, Zhongming & Zhang, Yaru & Fang, Chenhao & Yu, Yadong & Ma, Tieju, 2019. "Analysis of China's olefin industry with a system optimization model – With different scenarios of dynamic oil and coal prices," Energy Policy, Elsevier, vol. 135(C).
    • Handle: RePEc:eee:enepol:v:135:y:2019:i:c:s0301421519305919
    DOI: 10.1016/j.enpol.2019.111004
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    Cited by:

    1. Ding, Bingqing & Makowski, Marek & Nahorski, Zbigniew & Ren, Hongtao & Ma, Tieju, 2022. "Optimizing the technology pathway of China's liquid fuel production considering uncertain oil prices: A robust programming model," Energy Economics, Elsevier, vol. 115(C).
    2. Xu, Zhongming & Fang, Chenhao & Ma, Tieju, 2020. "Analysis of China’s olefin industry using a system optimization model considering technological learning and energy consumption reduction," Energy, Elsevier, vol. 191(C).
    3. Li, Hong & Zhou, Hao & Liu, Kailong & Gao, Xin & Li, Xingang, 2021. "Retrofit application of traditional petroleum chemical technologies to coal chemical industry for sustainable energy-efficiency production," Energy, Elsevier, vol. 218(C).

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