IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v134y2024ics0140988324003190.html
   My bibliography  Save this article

Integrated geo-techno-economic and real options analysis of the decision to invest in a medium enthalpy deep geothermal heating plant. A case study in Northern Belgium

Author

Listed:
  • Gkousis, Spiros
  • Welkenhuysen, Kris
  • Harcouët-Menou, Virginie
  • Pogacnik, Justin
  • Laenen, Ben
  • Compernolle, Tine

Abstract

Deep geothermal energy (DGE) is a renewable energy source that is considered to cause a low global warming impact. The potential of DGE for heating is widespread and interest in deep geothermal heating (DGH) has been growing in Europe to help achieving the decarbonization of the heating mix. Nevertheless, despite its large potential, DGH development in Europe remains underexplored. DGH investments are hindered by the risks born by geological and market uncertainties. However, various flexibility options inherent to the development process, such as the option to abandon or defer, could partly mitigate these risks. To account for managerial flexibility in the investment analysis, this study suggests a novel real options (RO) framework. The RO model splits DGH development into five phases, and considers several compound options and geological and market uncertainties to investigate the timing and value of DGH development at the Campine Basin in Northern Belgium. The RO model is coupled to a geo-techno-economic model and is solved using the Least Squares Monte Carlo algorithm. The RO analysis finds a 51% probability of abandonment and an average deferral time for the development of 12 years. The abandon option mitigates the risk of large financial losses in case of inadequate geological conditions. The defer option allows the investors to wait for more favorable market conditions before investing, to increase the project value. The results show that DGH development in the investigated area is not economically desirable. However, the investors' flexibility increases the project value by 12.16 million EUR, compared to a conventional techno-economic analysis. The implementation of supporting policy measures improves the economic performance of the plant. The consideration of flexibility leads to supporting policy measures with 3–4 times lower governmental expenditure, compared to a conventional techno-economic analysis. This study shows that a RO approach is more suitable to investigate DGH investments than static techno-economic methods. The inclusion of flexibility allows for identifying development pathways that increase the project value and for designing more cost-efficient supporting policy schemes.

Suggested Citation

  • Gkousis, Spiros & Welkenhuysen, Kris & Harcouët-Menou, Virginie & Pogacnik, Justin & Laenen, Ben & Compernolle, Tine, 2024. "Integrated geo-techno-economic and real options analysis of the decision to invest in a medium enthalpy deep geothermal heating plant. A case study in Northern Belgium," Energy Economics, Elsevier, vol. 134(C).
  • Handle: RePEc:eee:eneeco:v:134:y:2024:i:c:s0140988324003190
    DOI: 10.1016/j.eneco.2024.107611
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988324003190
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2024.107611?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. Xu, Tianfu & Yuan, Yilong & Jia, Xiaofeng & Lei, Yude & Li, Shengtao & Feng, Bo & Hou, Zhaoyun & Jiang, Zhenjiao, 2018. "Prospects of power generation from an enhanced geothermal system by water circulation through two horizontal wells: A case study in the Gonghe Basin, Qinghai Province, China," Energy, Elsevier, vol. 148(C), pages 196-207.
    2. Ma, Yiju & Swandi, Kevin & Chapman, Archie C. & Verbič, Gregor, 2020. "Multi-stage compound real options valuation in residential PV-Battery investment," Energy, Elsevier, vol. 191(C).
    3. Welkenhuysen, Kris & Rupert, Jort & Compernolle, Tine & Ramirez, Andrea & Swennen, Rudy & Piessens, Kris, 2017. "Considering economic and geological uncertainty in the simulation of realistic investment decisions for CO2-EOR projects in the North Sea," Applied Energy, Elsevier, vol. 185(P1), pages 745-761.
    4. Fuss, Sabine & Szolgayova, Jana & Obersteiner, Michael & Gusti, Mykola, 2008. "Investment under market and climate policy uncertainty," Applied Energy, Elsevier, vol. 85(8), pages 708-721, August.
    5. Li, Longxi & Cao, Xilin, 2022. "Comprehensive effectiveness assessment of energy storage incentive mechanisms for PV-ESS projects based on compound real options," Energy, Elsevier, vol. 239(PA).
    6. Zhang, M.M. & Zhou, P. & Zhou, D.Q., 2016. "A real options model for renewable energy investment with application to solar photovoltaic power generation in China," Energy Economics, Elsevier, vol. 59(C), pages 213-226.
    7. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474.
    8. Gkousis, Spiros & Welkenhuysen, Kris & Compernolle, Tine, 2022. "Deep geothermal energy extraction, a review on environmental hotspots with focus on geo-technical site conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    9. Maeda, Mansaku & Watts, David, 2019. "The unnoticed impact of long-term cost information on wind farms’ economic value in the USA. – A real option analysis," Applied Energy, Elsevier, vol. 241(C), pages 540-547.
    10. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," University of California at Los Angeles, Anderson Graduate School of Management qt43n1k4jb, Anderson Graduate School of Management, UCLA.
    11. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 113-147.
    12. Van Erdeweghe, Sarah & Van Bael, Johan & Laenen, Ben & D'haeseleer, William, 2018. "Feasibility study of a low-temperature geothermal power plant for multiple economic scenarios," Energy, Elsevier, vol. 155(C), pages 1004-1012.
    13. Daniilidis, Alexandros & Alpsoy, Betül & Herber, Rien, 2017. "Impact of technical and economic uncertainties on the economic performance of a deep geothermal heat system," Renewable Energy, Elsevier, vol. 114(PB), pages 805-816.
    14. Pringles, Rolando & Olsina, Fernando & Garcés, Francisco, 2015. "Real option valuation of power transmission investments by stochastic simulation," Energy Economics, Elsevier, vol. 47(C), pages 215-226.
    15. Compernolle, Tine & Welkenhuysen, Kris & Petitclerc, Estelle & Maes, Dries & Piessens, Kris, 2019. "The impact of policy measures on profitability and risk in geothermal energy investments," Energy Economics, Elsevier, vol. 84(C).
    16. International Finance Corporation, 2013. "Success of Geothermal Wells : A Global Study," World Bank Publications - Reports 16493, The World Bank Group.
    17. Chen, Siyuan & Zhang, Qi & Wang, Ge & Zhu, Lijing & Li, Yan, 2018. "Investment strategy for underground gas storage facilities based on real option model considering gas market reform in China," Energy Economics, Elsevier, vol. 70(C), pages 132-142.
    18. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    19. Xia, Z.H. & Jia, G.S. & Ma, Z.D. & Wang, J.W. & Zhang, Y.P. & Jin, L.W., 2021. "Analysis of economy, thermal efficiency and environmental impact of geothermal heating system based on life cycle assessments," Applied Energy, Elsevier, vol. 303(C).
    20. Chen, Siyuan & Zhang, Qi & Li, Hailong & Mclellan, Benjamin & Zhang, Tiantian & Tan, Zhizhou, 2019. "Investment decision on shallow geothermal heating & cooling based on compound options model: A case study of China," Applied Energy, Elsevier, vol. 254(C).
    Full references (including those not matched with items on IDEAS)

    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. Locatelli, Giorgio & Mancini, Mauro & Lotti, Giovanni, 2020. "A simple-to-implement real options method for the energy sector," Energy, Elsevier, vol. 197(C).
    2. Liu, Haomin & Zhang, Zaixu & Zhang, Tao, 2022. "Shale gas investment decision-making: Green and efficient development under market, technology and environment uncertainties," Applied Energy, Elsevier, vol. 306(PA).
    3. Zhang, M.M. & Zhou, D.Q. & Zhou, P. & Chen, H.T., 2017. "Optimal design of subsidy to stimulate renewable energy investments: The case of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 873-883.
    4. Chen, Siyuan & Zhang, Qi & Li, Hailong & Mclellan, Benjamin & Zhang, Tiantian & Tan, Zhizhou, 2019. "Investment decision on shallow geothermal heating & cooling based on compound options model: A case study of China," Applied Energy, Elsevier, vol. 254(C).
    5. Pringles, Rolando & Olsina, Fernando & Penizzotto, Franco, 2020. "Valuation of defer and relocation options in photovoltaic generation investments by a stochastic simulation-based method," Renewable Energy, Elsevier, vol. 151(C), pages 846-864.
    6. Zhang, M.M. & Wang, Qunwei & Zhou, Dequn & Ding, H., 2019. "Evaluating uncertain investment decisions in low-carbon transition toward renewable energy," Applied Energy, Elsevier, vol. 240(C), pages 1049-1060.
    7. Mombello, Bruno & Olsina, Fernando & Pringles, Rolando, 2023. "Valuing photovoltaic power plants by compound real options," Renewable Energy, Elsevier, vol. 216(C).
    8. Zhang, M.M. & Zhou, P. & Zhou, D.Q., 2016. "A real options model for renewable energy investment with application to solar photovoltaic power generation in China," Energy Economics, Elsevier, vol. 59(C), pages 213-226.
    9. Pan, Yingjie & Yao, Xing & Wang, Xin & Zhu, Lei, 2019. "Policy uncertainties: What investment choice for solar panel producers?," Energy Economics, Elsevier, vol. 78(C), pages 454-467.
    10. Hieronymi, Philipp & Schüller, David, 2015. "The Clean-Development Mechanism, stochastic permit prices and energy investments," Energy Economics, Elsevier, vol. 47(C), pages 25-36.
    11. Penizzotto, F. & Pringles, R. & Olsina, F., 2019. "Real options valuation of photovoltaic power investments in existing buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    12. Assereto, Martina & Byrne, Julie, 2021. "No real option for solar in Ireland: A real option valuation of utility scale solar investment in Ireland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    13. Àlex Alonso-Travesset & Diederik Coppitters & Helena Martín & Jordi de la Hoz, 2023. "Economic and Regulatory Uncertainty in Renewable Energy System Design: A Review," Energies, MDPI, vol. 16(2), pages 1-30, January.
    14. Zhang, Mingming & Liu, Liyun & Wang, Qunwei & Zhou, Dequn, 2020. "Valuing investment decisions of renewable energy projects considering changing volatility," Energy Economics, Elsevier, vol. 92(C).
    15. Hu, Junfei & Chen, Huanyue & Zhou, Peng & Guo, Peng, 2022. "Optimal subsidy level for waste-to-energy investment considering flexibility and uncertainty," Energy Economics, Elsevier, vol. 108(C).
    16. Chen, Siyuan & Zhang, Qi & Wang, Ge & Zhu, Lijing & Li, Yan, 2018. "Investment strategy for underground gas storage facilities based on real option model considering gas market reform in China," Energy Economics, Elsevier, vol. 70(C), pages 132-142.
    17. Mo, Jian-Lei & Schleich, Joachim & Zhu, Lei & Fan, Ying, 2015. "Delaying the introduction of emissions trading systems—Implications for power plant investment and operation from a multi-stage decision model," Energy Economics, Elsevier, vol. 52(PB), pages 255-264.
    18. Jungmin An & Dong-Kwan Kim & Jinyeong Lee & Sung-Kwan Joo, 2021. "Least Squares Monte Carlo Simulation-Based Decision-Making Method for Photovoltaic Investment in Korea," Sustainability, MDPI, vol. 13(19), pages 1-14, September.
    19. Linnerud, Kristin & Andersson, Ane Marte & Fleten, Stein-Erik, 2014. "Investment timing under uncertain renewable energy policy: An empirical study of small hydropower projects," Energy, Elsevier, vol. 78(C), pages 154-164.
    20. Mo, Jian-Lei & Agnolucci, Paolo & Jiang, Mao-Rong & Fan, Ying, 2016. "The impact of Chinese carbon emission trading scheme (ETS) on low carbon energy (LCE) investment," Energy Policy, Elsevier, vol. 89(C), pages 271-283.

    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:eneeco:v:134:y:2024:i:c:s0140988324003190. 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/locate/eneco .

    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.