Techno-Economic Assessment of Deep Geothermal Heating Plants Targeting Medium Enthalpy Resources Under a Real Options Approach to Include Flexibility and Uncertainty. A Case Study in Northern Belgium

Investment in deep geothermal heating (DGH) plants is 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-technical model and is solved using the Least Squares Monte Carlo algorithm. The RO analysis finds a probability of abandonment of 51% and suggests the deferral of the development for 12 years on average. The abandon option mitigates the risk of bearing large financial losses in case of achieving 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 inclusion of flexibility leads to an increase in the project value of 12.16 million EUR, compared to a case where the flexibility is neglected. The implementation of supporting policy measures is shown to improve the economic performance of the plant. The inclusion of flexibility in the design of supporting policy measures can lead to a 3-4 times lower governmental expenditure, compared to the case that flexibility is neglected. This study shows that a RO approach is more suitable to investigate DGH investments. The inclusion of flexibility allows for identifying development pathways that increase the project value and for designing more cost-efficient supporting policy schemes