Abstract

High-temperature aquifer thermal energy storage (HT-ATES) systems can store renewable-based or waste heat in the subsurface on a seasonal scale and may thus reduce the carbon footprint of future heat supply systems. Thermal recovery, i.e. the ratio of extracted to injected heat over one cycle, is required in a pre-application assessment because it determines the operational and economic viability of a HT-ATES system. The induced temperature changes in the subsurface are required to obtain the legal permits and are of interest for the design of a monitoring network. However, uncertainty in our knowledge on subsurface hydraulic and thermal parameters translates into uncertainties of the expected thermal recovery and the temperature changes induced during HT-ATES operation. In order to address these uncertainties for a case study in Hamburg, Germany, we use numerical modeling of the coupled thermo-hydraulic processes during the design stage of a HT-ATES system, based on a realistic load curve and the local geological setting of the storage aquifer. An ensemble of 50 scenarios was parameterized based on site-specific parameter uncertainties using Latin hypercube sampling to reflect the global parameter distributions, and the HT-ATES operation was simulated over a period of 26 years in each case. Most of the scenarios show high thermal recoveries with a median of 89 % in the 26th year, with thermal recovery most sensitive to the vertical hydraulic conductivity. The expected temperature distribution is well defined by the ensemble of model simulations, with far-field temperature changes reaching for hundreds of meters and showing greater variability between scenarios than those in the near-field region of the warm HT-ATES well on the tens of meters scale. Locations with large temperature differences between scenarios are identified as suitable for the placement of temperature monitoring wells. The presented work thus contributes directly to the design and permitting of HT-ATES systems and can also be used for uncertainty assessment of future HT-ATES plants and the identification of suitable monitoring setups.

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