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Deep geothermal energy presents large untapped renewable energy potential could significantly contribute to global energy needs. However, developing geothermal projects involves uncertainties regarding adequate geothermal brine extraction and huge costs related to preparation phases and consequently drilling and stimulation activities. Therefore, evaluating utilization alternatives of such projects is a complex decision-making problem effectively addressed using multi-criteria decision-making (MCDM) methods. This study introduces the MCDM method utilizing analytic hierarchy process (AHP) and weighted decision matrix (WDM) to assess different utilization alternatives (electricity generation, direct heat use and cogeneration). The AHP method determines the weight of each criterion and sub-criterion, while the WDM calculates the final project grade. Five criteria groups - technological, geological, economic, societal and environmental – comprising twenty-eight influencing factors were selected and used for the assessment of investment in Enhanced Geothermal Systems (EGS) projects. The AHP-WDM method was used by 38 experts from six categories: industry, educational institution, research and technology organization (RTO), small- and medium-sized enterprises (SME), local community and other. These diverse expert inputs aimed to capture varying perspectives and knowledge influence investment decisions in geothermal energy. The results were analysed accordingly. The results underscore the importance of incorporating different viewpoints to develop robust, credible, and effective investment strategies for EGS projects. Therefore, this method will contribute to more efficient EGS project development, enabling thus a greater penetration of the EGS into the market. Additionally, the proposed AHP-WDM method was implemented for a case study examining two locations. Locations were assessed and compared on scenario-based evaluation. The results confirmed the method's adequacy for assessing various end uses and comparing project feasibility across different locations.
Raos et al. (Thu,) studied this question.