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Optimizing the technology pathway of China's liquid fuel production considering uncertain oil prices: A robust programming model

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  • Ding, Bingqing
  • Makowski, Marek
  • Nahorski, Zbigniew
  • Ren, Hongtao
  • Ma, Tieju

Abstract

Even though China has been increasingly producing liquid fuel from alternative resources in recent decades, crude oil to liquid fuel process (OTL) still has a dominant position in China's liquid fuel industry. Therefore, the uncertainty of oil prices would greatly impact this country's economic and environmental valuations of alternative liquid fuel technologies. The present study develops an optimization model to analyze the technology portfolio of the liquid fuel industry. Two significant elements constitute this model, namely, the deterministic optimization part and the robust model. They achieve the aims of minimizing the total cost and maximizing the tolerance of data uncertainty under an ellipsoidal uncertainty set. In addition, we also investigate the impact of the increase in carbon prices on the technology portfolio. The results show that alternative technologies will be rapidly developed from 2020 to 2050 under oil price uncertainty, especially coal to liquid fuel (CTL) technology, which can reduce the dependency on crude oil but can generate a large amount of carbon emissions. For reducing the CO2 emissions in the liquid fuel industry, carbon prices have been additionally considered in this research. The results show that the increase of carbon prices could substantially decrease CO2 emissions, but using carbon trading alone cannot achieve the peak of carbon emissions by 2030. Thus, various types of clean technologies, i.e., hydrogen, solar, and wind, should be widely used in energy systems.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:eneeco:v:115:y:2022:i:c:s014098832200500x
    DOI: 10.1016/j.eneco.2022.106371
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