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Targeting for carbon sequestration retrofit planning in the power generation sector for multi-period problems

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  • Ooi, Raymond E.H.
  • Foo, Dominic C.Y.
  • Tan, Raymond R.

Abstract

Carbon constrained energy planning (CCEP) is useful to ensure that the CO2 emissions limit for a region is met through deployment of low-carbon technologies. The increased demand in energy consumption due to economic growth requires additional energy supply and generation which would subsequently increase the carbon emissions. Nevertheless, most countries are now committed to reduce carbon emission to achieve long term sustainability goals. However, the development of alternative energy sources or carbon capture and storage (CCS) initiatives for power plants entails major capital investments. This paper demonstrates how these issues may be handled using CCEP with insight- and optimisation-based targeting techniques for multi-period scenarios. Both approaches were developed recently for CCEP problems, but previous techniques were limited to single-period planning. The extensions to multi-period scenarios are demonstrated in this work with hypothetical illustrative examples, as well as a Malaysian case study.

Suggested Citation

  • Ooi, Raymond E.H. & Foo, Dominic C.Y. & Tan, Raymond R., 2014. "Targeting for carbon sequestration retrofit planning in the power generation sector for multi-period problems," Applied Energy, Elsevier, vol. 113(C), pages 477-487.
    • Handle: RePEc:eee:appene:v:113:y:2014:i:c:p:477-487
    DOI: 10.1016/j.apenergy.2013.07.047
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    References listed on IDEAS

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    Cited by:

    1. Peter Viebahn & Emile J. L. Chappin, 2018. "Scrutinising the Gap between the Expected and Actual Deployment of Carbon Capture and Storage—A Bibliometric Analysis," Energies, MDPI, vol. 11(9), pages 1-45, September.
    2. Lee, Jui-Yuan & Tan, Raymond R. & Chen, Cheng-Liang, 2014. "A unified model for the deployment of carbon capture and storage," Applied Energy, Elsevier, vol. 121(C), pages 140-148.
    3. Zhang, Shuai & Liu, Linlin & Zhang, Lei & Zhuang, Yu & Du, Jian, 2018. "An optimization model for carbon capture utilization and storage supply chain: A case study in Northeastern China," Applied Energy, Elsevier, vol. 231(C), pages 194-206.
    4. Rok Gomilšek & Lidija Čuček & Marko Homšak & Raymond R. Tan & Zdravko Kravanja, 2020. "Carbon Emissions Constrained Energy Planning for Aluminum Products," Energies, MDPI, vol. 13(11), pages 1-18, June.
    5. Walmsley, Michael R.W. & Walmsley, Timothy G. & Atkins, Martin J., 2015. "Achieving 33% renewable electricity generation by 2020 in California," Energy, Elsevier, vol. 92(P3), pages 260-269.
    6. Lee, Jui-Yuan, 2017. "A multi-period optimisation model for planning carbon sequestration retrofits in the electricity sector," Applied Energy, Elsevier, vol. 198(C), pages 12-20.
    7. Jia, Xiaoping & Xu, Tianshu & Zhang, Yanmei & Li, Zhiwei & Tan, Raymond R. & Aviso, Kathleen B. & Wang, Fang, 2023. "An improved multi-period algebraic targeting approach to low carbon energy planning," Energy, Elsevier, vol. 268(C).
    8. Walmsley, Michael R.W. & Walmsley, Timothy G. & Atkins, Martin J. & Kamp, Peter J.J. & Neale, James R. & Chand, Alvin, 2015. "Carbon Emissions Pinch Analysis for emissions reductions in the New Zealand transport sector through to 2050," Energy, Elsevier, vol. 92(P3), pages 569-576.
    9. Purusothmn Nair S. Bhasker Nair & Raymond R. Tan & Dominic C. Y. Foo & Disni Gamaralalage & Michael Short, 2023. "DECO2—An Open-Source Energy System Decarbonisation Planning Software including Negative Emissions Technologies," Energies, MDPI, vol. 16(4), pages 1-27, February.
    10. Chong, Fah Keen & Lawrence‎, Kelvin Kuhanraj & Lim, Pek Peng & Poon, Marcus Chinn Yoong & Foo, Dominic Chwan Yee & Lam, Hon Loong & Tan, Raymond R., 2014. "Planning of carbon capture storage deployment using process graph approach," Energy, Elsevier, vol. 76(C), pages 641-651.
    11. Tapia, John Frederick D. & Lee, Jui-Yuan & Ooi, Raymond E.H. & Foo, Dominic C.Y. & Tan, Raymond R., 2016. "Optimal CO2 allocation and scheduling in enhanced oil recovery (EOR) operations," Applied Energy, Elsevier, vol. 184(C), pages 337-345.
    12. Jui-Yuan Lee & Han-Fu Lin, 2019. "Multi-Footprint Constrained Energy Sector Planning," Energies, MDPI, vol. 12(12), pages 1-18, June.
    13. Krishna Priya, G.S. & Bandyopadhyay, Santanu, 2017. "Multi-objective pinch analysis for power system planning," Applied Energy, Elsevier, vol. 202(C), pages 335-347.
    14. Walmsley, Michael R.W. & Walmsley, Timothy G. & Atkins, Martin J. & Kamp, Peter J.J. & Neale, James R., 2014. "Minimising carbon emissions and energy expended for electricity generation in New Zealand through to 2050," Applied Energy, Elsevier, vol. 135(C), pages 656-665.
    15. Diban, Pitchaimuthu & Foo, Dominic C.Y., 2019. "A pinch-based automated targeting technique for heating medium system," Energy, Elsevier, vol. 166(C), pages 193-212.

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