Details zur Publikation |
| Kategorie | Textpublikation |
| Referenztyp | Zeitschriften |
| DOI | 10.1016/j.geoen.2026.214393 |
Lizenz  |
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| Titel (primär) | Feasibility assessment of high-temperature aquifer thermal energy storage using design of experiments |
| Autor | Khasheei, M.; Kulich, J.; Scholey, R.; Götzl, G.; Yoshioka, K. |
| Quelle | Geoenergy Science and Engineering |
| Erscheinungsjahr | 2026 |
| Department | ENVINF |
| Band/Volume | 260 |
| Seite von | art. 214393 |
| Sprache | englisch |
| Topic | T8 Georesources |
| Keywords | Aquifer thermal energy storage; Design of experiment |
| Abstract | Thermal energy storage technologies can mitigate the seasonal imbalance of the heating and cooling supply. Among these, Aquifer Thermal Energy Storage (ATES) is particularly promising because of its small surface footprint and large subsurface storage capacity. However, its performance assessment is affected by uncertainties in subsurface properties and operational conditions. This poses challenges for decision- making. Moreover, systematic and computationally efficient uncertainty quantification frameworks for high-temperature ATES systems remain rare, particularly for sites with limited prior data. While Monte Carlo simulations are commonly used to address these uncertainties, their computational cost can become prohibitively high when hydrological simulators are employed. To overcome this challenge, this study presents a Design of Experiments based workflow. The workflow includes parameter screening to identify the most influential variables on ATES performance and the development of a surrogate model to enable efficient Monte Carlo simulations. Such workflows are widely applied in the oil and gas industry for field development and uncertainty quantification. However, their use in the context of ATES remains limited. The entire workflow is integrated into a fully automated Python script and was tested using data from the southern Vienna Basin, Austria, which represents an uninvestigated greenfield site for ATES development. Results from the screening step identify injection temperature at the hot well, total circulating water volume, thermal gradient, and longitudinal dispersivity as the most influential factors. Monte Carlo simulation results indicate that, given the uncertainty ranges considered, the most probable values for the Heat Recovery Factor and gross heat production in winter are 0.89 and 19.03 GWh. |
| Khasheei, M., Kulich, J., Scholey, R., Götzl, G., Yoshioka, K. (2026): Feasibility assessment of high-temperature aquifer thermal energy storage using design of experiments Geoenergy Sci. Eng. 260 , art. 214393 10.1016/j.geoen.2026.214393 |
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