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Investment Decision on Shallow Geothermal Heating & Cooling Based on Compound Options Model: A Case Study of China

Chen, Siyuan, Zhang, Qi, Li, Hailong, Mclellan, Benjamin, Zhang, Tiantian, Tan, Zhizhou
Applied energy 2019
Markov chain, Monte Carlo method, carbon markets, case studies, cooling, electricity costs, geothermal energy, heat, issues and policy, risk, taxes, China
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 flexibility. 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.