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Investment decision on shallow geothermal heating & cooling based on compound options model: A case study of China
China University of Petroleum-Beijing, China.
China University of Petroleum-Beijing, China.
Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Tianjin University of Commerce, China.ORCID iD: 0000-0002-6279-4446
Kyoto University, Japan.
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2019 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 254, article id 113655Article in journal (Refereed) Published
Abstract [en]

Developing shallow geothermal energy is expected to play an important role to supply affordable, clean and reliable heating by many countries in the world. However, the development is mainly hindered by the high upfront investment costs and various risks involved in the exploration, construction and operation phases. The present study proposed a compound options model to explore the optimal investment timing and value based on the consideration of both investment and operational flexibilities. The Least Square Monte Carlo and Markov Chain Monte Carlo methods were employed in the model to find the solutions. A case study was carried out for China, and five scenarios were simulated to understand the effects of different policies including subsidy, carbon trading mechanism, preferential taxation and preferential electricity price. The obtained results show that, (i) the incentive policies are essential for the development of shallow geothermal energy, which can attract more investment before 2030; (ii) the government is suggested to carry out a preferential electricity price for shallow geothermal development, rather than increase the subsidy; (iii) the application of compound options method increases the investment value in all five scenarios, but its impact on investment timing varies.

Place, publisher, year, edition, pages
Elsevier Ltd , 2019. Vol. 254, article id 113655
Keywords [en]
China, Compound options, Investment decision, Least Square Monte Carlo, Markov Chain Monte Carlo, Shallow geothermal energy
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-45098DOI: 10.1016/j.apenergy.2019.113655ISI: 000497974600053Scopus ID: 2-s2.0-85070825127OAI: oai:DiVA.org:mdh-45098DiVA, id: diva2:1346670
Available from: 2019-08-28 Created: 2019-08-28 Last updated: 2019-12-12Bibliographically approved

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Li, Hailong

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  • apa
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