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The potential role of carbon capture and storage technology in sustainable electric-power systems under multiple uncertainties

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  • Jin, S.W.
  • Li, Y.P.
  • Nie, S.
  • Sun, J.

Abstract

One of the problems facing researchers in managing carbon capture and storage (CCS) technology is that complex energy systems accommodate the relevant social, economic, environmental, and political factors. Many system behaviors, factors, and parameters are associated with uncertainties. Effective management of such a complex system involves balancing tradeoffs among these key influencing factors under multiple uncertainties. In this study, an interval-fuzzy stochastic programming (IFSP) method is developed to deal with multiple uncertainties expressed as fuzzy sets, intervals and probability distributions. An IFSP-CCS model is formulated to plan CCS technology of power system in Bayingolin Mongol Autonomous Prefecture (Bazhou). Policy scenarios are introduced to investigate the potential role of CCS technology and sensitivity analyses are performed to assess the influence of various economic factors on system cost. Results indicate various uncertainties existed in CCS development and the related factors can affect the modeling outputs. Results also reveal that CO2-mitigation constraint can induce the development of renewable energy and CCS, and CCS technology can make a great contribution to CO2 emission reductions from a long-term planning perspective. The findings can provide support for CCS investment in fossil-fuel-dominated electric-power system and offer useful information for policy investigation under multiple uncertainties.

Suggested Citation

  • Jin, S.W. & Li, Y.P. & Nie, S. & Sun, J., 2017. "The potential role of carbon capture and storage technology in sustainable electric-power systems under multiple uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 467-480.
    • Handle: RePEc:eee:rensus:v:80:y:2017:i:c:p:467-480
    DOI: 10.1016/j.rser.2017.05.230
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    as
    1. Asian Development Bank (ADB), 2013. "Prospects for Carbon Capture and Storage in Southeast Asia," ADB Reports RPT135683-2, Asian Development Bank (ADB), revised 05 Feb 2014.
    2. Viebahn, Peter & Vallentin, Daniel & Höller, Samuel, 2015. "Prospects of carbon capture and storage (CCS) in China’s power sector – An integrated assessment," Applied Energy, Elsevier, vol. 157(C), pages 229-244.
    3. Ang, B.W. & Su, Bin, 2016. "Carbon emission intensity in electricity production: A global analysis," Energy Policy, Elsevier, vol. 94(C), pages 56-63.
    4. Maqsood, Imran & Huang, Guo H. & Scott Yeomans, Julian, 2005. "An interval-parameter fuzzy two-stage stochastic program for water resources management under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 208-225, November.
    5. Hope, Aimie L.B. & Jones, Christopher R., 2014. "The impact of religious faith on attitudes to environmental issues and Carbon Capture and Storage (CCS) technologies: A mixed methods study," Technology in Society, Elsevier, vol. 38(C), pages 48-59.
    6. Li, Y.P. & Liu, J. & Huang, G.H., 2014. "A hybrid fuzzy-stochastic programming method for water trading within an agricultural system," Agricultural Systems, Elsevier, vol. 123(C), pages 71-83.
    7. Zhang, Xian & Wang, Xingwei & Chen, Jiajun & Xie, Xi & Wang, Ke & Wei, Yiming, 2014. "A novel modeling based real option approach for CCS investment evaluation under multiple uncertainties," Applied Energy, Elsevier, vol. 113(C), pages 1059-1067.
    8. Mendoza, Guillermo A. & Bruce Bare, B. & Zhou, Zehai, 1993. "A fuzzy multiple objective linear programming approach to forest planning under uncertainty," Agricultural Systems, Elsevier, vol. 41(3), pages 257-274.
    9. van Alphen, Klaas & Noothout, Paul M. & Hekkert, Marko P. & Turkenburg, Wim C., 2010. "Evaluating the development of carbon capture and storage technologies in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 971-986, April.
    10. Sadeghi, Mehdi & Mirshojaeian Hosseini, Hossein, 2006. "Energy supply planning in Iran by using fuzzy linear programming approach (regarding uncertainties of investment costs)," Energy Policy, Elsevier, vol. 34(9), pages 993-1003, June.
    11. Chen, W.T. & Li, Y.P. & Huang, G.H. & Chen, X. & Li, Y.F., 2010. "A two-stage inexact-stochastic programming model for planning carbon dioxide emission trading under uncertainty," Applied Energy, Elsevier, vol. 87(3), pages 1033-1047, March.
    12. Koronaki, I.P. & Prentza, L. & Papaefthimiou, V., 2015. "Modeling of CO2 capture via chemical absorption processes − An extensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 547-566.
    13. Bistline, John E., 2015. "Electric sector capacity planning under uncertainty: Climate policy and natural gas in the US," Energy Economics, Elsevier, vol. 51(C), pages 236-251.
    14. Middleton, Richard S. & Eccles, Jordan K., 2013. "The complex future of CO2 capture and storage: Variable electricity generation and fossil fuel power," Applied Energy, Elsevier, vol. 108(C), pages 66-73.
    15. Wang, Can & Zhang, Weishi & Cai, Wenjia & Xie, Xi, 2013. "Employment impacts of CDM projects in China's power sector," Energy Policy, Elsevier, vol. 59(C), pages 481-491.
    16. Verdejo, Humberto & Awerkin, Almendra & Saavedra, Eugenio & Kliemann, Wolfgang & Vargas, Luis, 2016. "Stochastic modeling to represent wind power generation and demand in electric power system based on real data," Applied Energy, Elsevier, vol. 173(C), pages 283-295.
    17. Zhou, Wenji & Zhu, Bing & Fuss, Sabine & Szolgayová, Jana & Obersteiner, Michael & Fei, Weiyang, 2010. "Uncertainty modeling of CCS investment strategy in China's power sector," Applied Energy, Elsevier, vol. 87(7), pages 2392-2400, July.
    18. Raugei, Marco & Leccisi, Enrica, 2016. "A comprehensive assessment of the energy performance of the full range of electricity generation technologies deployed in the United Kingdom," Energy Policy, Elsevier, vol. 90(C), pages 46-59.
    19. Cai, Y.P. & Huang, G.H. & Tan, Q. & Liu, L., 2011. "An integrated approach for climate-change impact analysis and adaptation planning under multi-level uncertainties. Part II. Case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 3051-3073, August.
    20. Q. Lin & G. Huang, 2011. "Interval-fuzzy stochastic optimization for regional energy systems planning and greenhouse-gas emission management under uncertainty—a case study for the Province of Ontario, Canada," Climatic Change, Springer, vol. 104(2), pages 353-378, January.
    21. Fuss, Sabine & Szolgayová, Jana, 2010. "Fuel price and technological uncertainty in a real options model for electricity planning," Applied Energy, Elsevier, vol. 87(9), pages 2938-2944, September.
    22. Aien, Morteza & Hajebrahimi, Ali & Fotuhi-Firuzabad, Mahmud, 2016. "A comprehensive review on uncertainty modeling techniques in power system studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1077-1089.
    23. Lohwasser, Richard & Madlener, Reinhard, 2012. "Economics of CCS for coal plants: Impact of investment costs and efficiency on market diffusion in Europe," Energy Economics, Elsevier, vol. 34(3), pages 850-863.
    24. Nabavieh, Alireza & Gholamiangonabadi, Davoud & Ahangaran, Ali Asghar, 2015. "Dynamic changes in CO2 emission performance of different types of Iranian fossil-fuel power plants," Energy Economics, Elsevier, vol. 52(PA), pages 142-150.
    25. Sreedhar, I. & Vaidhiswaran, R. & Kamani, Bansi. M. & Venugopal, A., 2017. "Process and engineering trends in membrane based carbon capture," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 659-684.
    26. Lai, N.Y.G. & Yap, E.H. & Lee, C.W., 2011. "Viability of CCS: A broad-based assessment for Malaysia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(8), pages 3608-3616.
    27. Koo, Jamin & Han, Kyusang & Yoon, En Sup, 2011. "Integration of CCS, emissions trading and volatilities of fuel prices into sustainable energy planning, and its robust optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 665-672, January.
    28. Muela, E. & Schweickardt, G. & Garces, F., 2007. "Fuzzy possibilistic model for medium-term power generation planning with environmental criteria," Energy Policy, Elsevier, vol. 35(11), pages 5643-5655, November.
    29. Cai, Y.P. & Huang, G.H. & Tan, Q. & Yang, Z.F., 2011. "An integrated approach for climate-change impact analysis and adaptation planning under multi-level uncertainties. Part I: Methodology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 2779-2790, August.
    30. Parvizimosaed, M. & Farmani, F. & Monsef, H. & Rahimi-Kian, A., 2017. "A multi-stage Smart Energy Management System under multiple uncertainties: A data mining approach," Renewable Energy, Elsevier, vol. 102(PA), pages 178-189.
    31. Li, Y.F. & Li, Y.P. & Huang, G.H. & Chen, X., 2010. "Energy and environmental systems planning under uncertainty--An inexact fuzzy-stochastic programming approach," Applied Energy, Elsevier, vol. 87(10), pages 3189-3211, October.
    32. Abadie, Luis M. & Chamorro, José M., 2008. "European CO2 prices and carbon capture investments," Energy Economics, Elsevier, vol. 30(6), pages 2992-3015, November.
    33. Li, Y.P. & Huang, G.H. & Chen, X., 2011. "Planning regional energy system in association with greenhouse gas mitigation under uncertainty," Applied Energy, Elsevier, vol. 88(3), pages 599-611, March.
    34. Sreenivasulu, B. & Gayatri, D.V. & Sreedhar, I. & Raghavan, K.V., 2015. "A journey into the process and engineering aspects of carbon capture technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1324-1350.
    35. Višković, Alfredo & Franki, Vladimir & Valentić, Vladimir, 2014. "CCS (carbon capture and storage) investment possibility in South East Europe: A case study for Croatia," Energy, Elsevier, vol. 70(C), pages 325-337.
    36. Cheng, Rui & Xu, Zhaofeng & Liu, Pei & Wang, Zhe & Li, Zheng & Jones, Ian, 2015. "A multi-region optimization planning model for China’s power sector," Applied Energy, Elsevier, vol. 137(C), pages 413-426.
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