Abstract
Deep Enhanced Geothermal Systems (EGS) represent a vast, continuous source of renewable baseload energy. Utilizing supercritical carbon dioxide (sCO2) instead of water as the heat transmission fluid offers compelling thermodynamic advantages, including lower fluid viscosity, significant density variations across operating temperature windows that drive a powerful thermosiphon effect, and potential permanent carbon sequestration. This paper presents a comprehensive thermodynamic modeling and multi-objective optimization study of a deep sCO2-EGS operating at depths between 4.0 and 6.0 km with reservoir temperatures from 180 °C to 280 °C. A coupled wellbore-reservoir thermo-hydraulic model was integrated with a modified recompression sCO2 Brayton surface power cycle. Using the Non-dominated Sorting Genetic Algorithm II (NSGA-II), the system was optimized for net electrical power output and overall exergy efficiency across key decision variables: fluid mass flow rate, injection pressure, injection temperature, and well spacing. The optimized sCO2-EGS achieved a peak net power generation of 14.8 MW per well doublet with a total exergy efficiency of 52.4%. Crucially, the strong self-propelling buoyancy force reduced parasitic pumping work by up to 68% compared to equivalent water-based EGS configurations. Sensitivity analyses revealed that reservoir permeability and fracture network aperture exert dominant controls on long-term thermal yield. These findings provide actionable thermodynamic insights for designing high-efficiency, low-parasitic-loss deep geothermal power plants utilizing supercritical fluid architectures.
