IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v86y2015icp627-637.html
   My bibliography  Save this article

Simulation and optimization of enhanced geothermal systems using CO2 as a working fluid

Author

Listed:
  • Biagi, James
  • Agarwal, Ramesh
  • Zhang, Zheming

Abstract

Because of rising concerns about CO2 emissions from fossil fueled power plants, in recent years there has been strong emphasis on the development of safe and economical CCUS (Carbon Capture Utilization and Storage) technology. One such technology that shows some promise is EGS (Enhanced Geothermal System), where CO2 is used as a working fluid to extract heat from a geothermal reservoir. Permanent carbon sequestration is also achieved as a byproduct due to subsurface fluid losses throughout the life of the system. In this paper, numerical simulations of subsurface flow in EGS are conducted using the multi-phase flow solver TOUGH2 (Transport of Unsaturated Groundwater and Heat). An optimization code based on a multi-objective genetic algorithm is combined with TOUGH2 (designated as GA-TOUGH2) and modified for EGS application. Using GA-TOUGH2, the CO2 injection rate is optimized for both constant mass and constant pressure injection scenarios to manage the production temperature profile and to ensure that the heat extraction occurs for the entire life of the system thus allowing more efficient use of CO2. The results of this study show promise of EGS technology for consideration of deployment on a commercial scale.

Suggested Citation

  • Biagi, James & Agarwal, Ramesh & Zhang, Zheming, 2015. "Simulation and optimization of enhanced geothermal systems using CO2 as a working fluid," Energy, Elsevier, vol. 86(C), pages 627-637.
  • Handle: RePEc:eee:energy:v:86:y:2015:i:c:p:627-637
    DOI: 10.1016/j.energy.2015.04.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054421500448X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2015.04.020?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.

    Citations

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


    Cited by:

    1. Shi, Yu & Song, Xianzhi & Shen, Zhonghou & Wang, Gaosheng & Li, Xiaojiang & Zheng, Rui & Geng, Lidong & Li, Jiacheng & Zhang, Shikun, 2018. "Numerical investigation on heat extraction performance of a CO2 enhanced geothermal system with multilateral wells," Energy, Elsevier, vol. 163(C), pages 38-51.
    2. Sun, Fengrui & Yao, Yuedong & Li, Guozhen & Li, Xiangfang, 2018. "Geothermal energy extraction in CO2 rich basin using abandoned horizontal wells," Energy, Elsevier, vol. 158(C), pages 760-773.
    3. Pan, Shu-Yuan & Gao, Mengyao & Shah, Kinjal J. & Zheng, Jianming & Pei, Si-Lu & Chiang, Pen-Chi, 2019. "Establishment of enhanced geothermal energy utilization plans: Barriers and strategies," Renewable Energy, Elsevier, vol. 132(C), pages 19-32.
    4. Cheng, Wen-Long & Wang, Chang-Long & Nian, Yong-Le & Han, Bing-Bing & Liu, Jian, 2016. "Analysis of influencing factors of heat extraction from enhanced geothermal systems considering water losses," Energy, Elsevier, vol. 115(P1), pages 274-288.
    5. Olasolo, P. & Juárez, M.C. & Morales, M.P. & Olasolo, A. & Agius, M.R., 2018. "Analysis of working fluids applicable in Enhanced Geothermal Systems: Nitrous oxide as an alternative working fluid," Energy, Elsevier, vol. 157(C), pages 150-161.
    6. Samin, Maleaha Y. & Faramarzi, Asaad & Jefferson, Ian & Harireche, Ouahid, 2019. "A hybrid optimisation approach to improve long-term performance of enhanced geothermal system (EGS) reservoirs," Renewable Energy, Elsevier, vol. 134(C), pages 379-389.
    7. Wang, Nanzhe & Chang, Haibin & Kong, Xiang-Zhao & Zhang, Dongxiao, 2023. "Deep learning based closed-loop well control optimization of geothermal reservoir with uncertain permeability," Renewable Energy, Elsevier, vol. 211(C), pages 379-394.
    8. Wu, Bisheng & Zhang, Xi & Jeffrey, Robert G. & Bunger, Andrew P. & Jia, Shanpo, 2016. "A simplified model for heat extraction by circulating fluid through a closed-loop multiple-fracture enhanced geothermal system," Applied Energy, Elsevier, vol. 183(C), pages 1664-1681.
    9. Chi Yao & Yulong Shao & Jianhua Yang, 2018. "Numerical Investigation on the Influence of Areal Flow on EGS Thermal Exploitation Based on the 3-D T-H Single Fracture Model," Energies, MDPI, vol. 11(11), pages 1-19, November.
    10. Lu, Shyi-Min, 2018. "A global review of enhanced geothermal system (EGS)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2902-2921.
    11. Esteves, Ana Filipa & Santos, Francisca Maria & Magalhães Pires, José Carlos, 2019. "Carbon dioxide as geothermal working fluid: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    12. Chen, Yun & Ma, Guowei & Wang, Huidong & Li, Tuo & Wang, Yang & Sun, Zizheng, 2020. "Optimizing heat mining strategies in a fractured geothermal reservoir considering fracture deformation effects," Renewable Energy, Elsevier, vol. 148(C), pages 326-337.
    13. Olasolo, P. & Juárez, M.C. & Morales, M.P. & D´Amico, Sebastiano & Liarte, I.A., 2016. "Enhanced geothermal systems (EGS): A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 133-144.
    14. Paweł Gładysz & Anna Sowiżdżał & Maciej Miecznik & Maciej Hacaga & Leszek Pająk, 2020. "Techno-Economic Assessment of a Combined Heat and Power Plant Integrated with Carbon Dioxide Removal Technology: A Case Study for Central Poland," Energies, MDPI, vol. 13(11), pages 1-34, June.
    15. Schifflechner, Christopher & Dawo, Fabian & Eyerer, Sebastian & Wieland, Christoph & Spliethoff, Hartmut, 2020. "Thermodynamic comparison of direct supercritical CO2 and indirect brine-ORC concepts for geothermal combined heat and power generation," Renewable Energy, Elsevier, vol. 161(C), pages 1292-1302.
    16. Chen, Guodong & Jiao, Jiu Jimmy & Jiang, Chuanyin & Luo, Xin, 2024. "Surrogate-assisted level-based learning evolutionary search for geothermal heat extraction optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    17. Wang, Chang-Long & Cheng, Wen-Long & Nian, Yong-Le & Yang, Lei & Han, Bing-Bing & Liu, Ming-Hou, 2018. "Simulation of heat extraction from CO2-based enhanced geothermal systems considering CO2 sequestration," Energy, Elsevier, vol. 142(C), pages 157-167.

    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:energy:v:86:y:2015:i:c:p:627-637. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.journals.elsevier.com/energy .

    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.