IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v208y2017icp691-702.html
   My bibliography  Save this article

Economic feasibility of calcium looping under uncertainty

Author

Listed:
  • Hanak, Dawid P.
  • Manovic, Vasilije

Abstract

An emerging calcium looping process has been shown to be a promising alternative to solvent scrubbing, which is regarded as the most mature CO2 capture technology. Its retrofits to coal-fired power plants have the potential to reduce both energy and economic penalties associated with the mature CO2 capture technologies. However, these conclusions have been made based on the deterministic outputs of the economic models that have not considered uncertainties in the model inputs. Therefore, this study incorporates a stochastic approach into the economic analysis of the retrofit of such emerging CO2 capture technology to the coal-fired power plant. The stochastic analysis revealed that levelised cost of electricity (LCOE) and specific total capital requirement were highly affected by the uncertainty in the input variables to the process and economic models. The most probable values for these key economic performance indicators were shown to fall between 75 and 115 €/MWelh, and 2100 and 2300 €/kWel,gross, respectively. Interestingly, the most probable LCOE values for the coal-fired power plant will fall between 50 and 150 €/MWelh. This indicated that the calcium looping retrofit scenario can become economically favoured, mainly due to the high economic penalties incurred by unabated coal-fired power plant associated with carbon tax. Importantly, the outputs of the stochastic economic assessment aligned well with the deterministic results reported in the literature. As the latter were generated using different sets of assumptions regarding the process and economic models, the stochastic approach to the economic assessment can minimise the impact of the model assumptions on estimates of the key economic parameters. Moreover, by indicating the probability of particular outputs, as well as ranking the model input variables according to their influence on the key economic performance, such analysis would allow making more insightful decisions regarding further funding and development of the calcium looping process. Finally, use of the stochastic approach in the economic feasibility assessment enables a more profound and reliable comparison of the different calcium looping retrofit configurations, as well as benchmarking different CO2 capture technologies.

Suggested Citation

  • Hanak, Dawid P. & Manovic, Vasilije, 2017. "Economic feasibility of calcium looping under uncertainty," Applied Energy, Elsevier, vol. 208(C), pages 691-702.
    • Handle: RePEc:eee:appene:v:208:y:2017:i:c:p:691-702
    DOI: 10.1016/j.apenergy.2017.09.078
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261917313600
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2017.09.078?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hanak, Dawid P. & Biliyok, Chechet & Manovic, Vasilije, 2015. "Efficiency improvements for the coal-fired power plant retrofit with CO2 capture plant using chilled ammonia process," Applied Energy, Elsevier, vol. 151(C), pages 258-272.
    2. Yu, Shiwei & Wei, Yi-Ming & Guo, Haixiang & Ding, Liping, 2014. "Carbon emission coefficient measurement of the coal-to-power energy chain in China," Applied Energy, Elsevier, vol. 114(C), pages 290-300.
    3. Abdul Manaf, Norhuda & Qadir, Abdul & Abbas, Ali, 2016. "Temporal multiscalar decision support framework for flexible operation of carbon capture plants targeting low-carbon management of power plant emissions," Applied Energy, Elsevier, vol. 169(C), pages 912-926.
    4. Zhu, Zhi-Shuang & Liao, Hua & Cao, Huai-Shu & Wang, Lu & Wei, Yi-Ming & Yan, Jinyue, 2014. "The differences of carbon intensity reduction rate across 89 countries in recent three decades," Applied Energy, Elsevier, vol. 113(C), pages 808-815.
    5. Kalogirou, Soteris A., 2000. "Applications of artificial neural-networks for energy systems," Applied Energy, Elsevier, vol. 67(1-2), pages 17-35, September.
    6. Osmundsen, Petter & Emhjellen, Magne, 2010. "CCS from the gas-fired power station at Kårstø? A commercial analysis," Energy Policy, Elsevier, vol. 38(12), pages 7818-7826, December.
    7. Geissmann, Thomas, 2017. "A probabilistic approach to the computation of the levelized cost of electricity," Energy, Elsevier, vol. 124(C), pages 372-381.
    8. Hu, Mengqi & Cho, Heejin, 2014. "A probability constrained multi-objective optimization model for CCHP system operation decision support," Applied Energy, Elsevier, vol. 116(C), pages 230-242.
    9. Karampinis, E. & Nikolopoulos, N. & Nikolopoulos, A. & Grammelis, P. & Kakaras, E., 2012. "Numerical investigation Greek lignite/cardoon co-firing in a tangentially fired furnace," Applied Energy, Elsevier, vol. 97(C), pages 514-524.
    10. Hanak, D.P. & Kolios, A.J. & Biliyok, C. & Manovic, V., 2015. "Probabilistic performance assessment of a coal-fired power plant," Applied Energy, Elsevier, vol. 139(C), pages 350-364.
    11. Perejón, Antonio & Romeo, Luis M. & Lara, Yolanda & Lisbona, Pilar & Martínez, Ana & Valverde, Jose Manuel, 2016. "The Calcium-Looping technology for CO2 capture: On the important roles of energy integration and sorbent behavior," Applied Energy, Elsevier, vol. 162(C), pages 787-807.
    12. Boukelia, T.E. & Arslan, O. & Mecibah, M.S., 2017. "Potential assessment of a parabolic trough solar thermal power plant considering hourly analysis: ANN-based approach," Renewable Energy, Elsevier, vol. 105(C), pages 324-333.
    13. Hanak, Dawid P. & Kolios, Athanasios J. & Manovic, Vasilije, 2016. "Comparison of probabilistic performance of calcium looping and chemical solvent scrubbing retrofits for CO2 capture from coal-fired power plant," Applied Energy, Elsevier, vol. 172(C), pages 323-336.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Strojny, Magdalena & Gładysz, Paweł & Hanak, Dawid P. & Nowak, Wojciech, 2023. "Comparative analysis of CO2 capture technologies using amine absorption and calcium looping integrated with natural gas combined cycle power plant," Energy, Elsevier, vol. 284(C).
    2. Zhang, Chaobo & Sun, Jie & Qiao, Yang & Wei, Jinjia, 2024. "Design, off-design and operation study of concentrating solar power system with calcium-looping thermochemical energy storage and photovoltaic-driven compressed CO2 energy storage," Energy, Elsevier, vol. 312(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hanak, Dawid P. & Kolios, Athanasios J. & Manovic, Vasilije, 2016. "Comparison of probabilistic performance of calcium looping and chemical solvent scrubbing retrofits for CO2 capture from coal-fired power plant," Applied Energy, Elsevier, vol. 172(C), pages 323-336.
    2. Hanak, D.P. & Kolios, A.J. & Biliyok, C. & Manovic, V., 2015. "Probabilistic performance assessment of a coal-fired power plant," Applied Energy, Elsevier, vol. 139(C), pages 350-364.
    3. Zhang, Xiaoshun & Chen, Yixuan & Yu, Tao & Yang, Bo & Qu, Kaiping & Mao, Senmao, 2017. "Equilibrium-inspired multiagent optimizer with extreme transfer learning for decentralized optimal carbon-energy combined-flow of large-scale power systems," Applied Energy, Elsevier, vol. 189(C), pages 157-176.
    4. Zhi-Fu Mi & Yi-Ming Wei & Chen-Qi He & Hua-Nan Li & Xiao-Chen Yuan & Hua Liao, 2017. "Regional efforts to mitigate climate change in China: a multi-criteria assessment approach," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 22(1), pages 45-66, January.
    5. Eising, Jan Willem & van Onna, Tom & Alkemade, Floortje, 2014. "Towards smart grids: Identifying the risks that arise from the integration of energy and transport supply chains," Applied Energy, Elsevier, vol. 123(C), pages 448-455.
    6. Yang, Ranran & Long, Ruyin & Yue, Ting & Shi, Haihong, 2014. "Calculation of embodied energy in Sino-USA trade: 1997–2011," Energy Policy, Elsevier, vol. 72(C), pages 110-119.
    7. Shu-Hong Wang & Ma-Lin Song & Tao Yu, 2019. "Hidden Carbon Emissions, Industrial Clusters, and Structure Optimization in China," Computational Economics, Springer;Society for Computational Economics, vol. 54(4), pages 1319-1342, December.
    8. Hanak, Dawid P. & Jenkins, Barrie G. & Kruger, Tim & Manovic, Vasilije, 2017. "High-efficiency negative-carbon emission power generation from integrated solid-oxide fuel cell and calciner," Applied Energy, Elsevier, vol. 205(C), pages 1189-1201.
    9. Li, Jin & Wang, Rui & Li, Haoran & Nie, Yaoyu & Song, Xinke & Li, Mingyu & Shi, Mai & Zheng, Xinzhu & Cai, Wenjia & Wang, Can, 2021. "Unit-level cost-benefit analysis for coal power plants retrofitted with biomass co-firing at a national level by combined GIS and life cycle assessment," Applied Energy, Elsevier, vol. 285(C).
    10. Qianyu Zhao & Boyu Xie & Mengyao Han, 2023. "Unpacking the Sub-Regional Spatial Network of Land-Use Carbon Emissions: The Case of Sichuan Province in China," Land, MDPI, vol. 12(10), pages 1-22, October.
    11. Guangfang Luo & Jianjun Zhang & Yongheng Rao & Xiaolei Zhu & Yiqiang Guo, 2017. "Coal Supply Chains: A Whole-Process-Based Measurement of Carbon Emissions in a Mining City of China," Energies, MDPI, vol. 10(11), pages 1-18, November.
    12. Wang, Ke & Zhang, Jianjun & Cai, Bofeng & Yu, Shengmin, 2019. "Emission factors of fugitive methane from underground coal mines in China: Estimation and uncertainty," Applied Energy, Elsevier, vol. 250(C), pages 273-282.
    13. Shaikh, Mohammad A. & Kucukvar, Murat & Onat, Nuri Cihat & Kirkil, Gokhan, 2017. "A framework for water and carbon footprint analysis of national electricity production scenarios," Energy, Elsevier, vol. 139(C), pages 406-421.
    14. Yang, Qing & Zhang, Lei & Zou, Shaohui & Zhang, Jinsuo, 2020. "Intertemporal optimization of the coal production capacity in China in terms of uncertain demand, economy, environment, and energy security," Energy Policy, Elsevier, vol. 139(C).
    15. Gong, Chengzhu & Yu, Shiwei & Zhu, Kejun & Hailu, Atakelty, 2016. "Evaluating the influence of increasing block tariffs in residential gas sector using agent-based computational economics," Energy Policy, Elsevier, vol. 92(C), pages 334-347.
    16. Yu Hao & Shang Gao & Yunxia Guo & Zhiqiang Gai & Haitao Wu, 2021. "Measuring the nexus between economic development and environmental quality based on environmental Kuznets curve: a comparative study between China and Germany for the period of 2000–2017," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(11), pages 16848-16873, November.
    17. Hasdi Aimon & Anggi Putri Kurniadi & Sri Ulfa Sentosa & Nurhayati Abd Rahman, 2023. "Production, Consumption, Export and Carbon Emission for Coal Commodities: Cases of Indonesia and Australia," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 484-492, September.
    18. Bin Ye & Jingjing Jiang & Lixin Miao & Peng Yang & Ji Li & Bo Shen, 2015. "Feasibility Study of a Solar-Powered Electric Vehicle Charging Station Model," Energies, MDPI, vol. 8(11), pages 1-19, November.
    19. Li, Tailu & Zhang, Yao & Wang, Jingyi & Jin, Fengyun & Gao, Ruizhao, 2024. "Techno-economic and environmental performance of a novel thermal station characterized by electric power generation recovery as by-product," Renewable Energy, Elsevier, vol. 221(C).
    20. Jie Wu & Jun-Fei Chu & Liang Liang, 2016. "Target setting and allocation of carbon emissions abatement based on DEA and closest target: an application to 20 APEC economies," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(1), pages 279-296, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:208:y:2017:i:c:p:691-702. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.