Analytically estimating the efficiency of high temperature aquifer thermal energy storage

Abstract High-Temperature Aquifer Thermal Energy Storage (HT-ATES) can be used to reduce greenhouse gas emissions from heating. The thermal recovery efficiency is the main parameter indicating the performance of an HT-ATES system and it is influenced by multiple aquifer properties and storage characteristics. This study presents a method for estimating recovery efficiency through numerical modeling, data analysis, and curve fitting. This method shows the relation between the recovery efficiency and various storage conditions, such as aquifer properties and storage temperature. In addition, this research explores an analytical relationship between energetic efficiency and recovery efficiency and verifies that relationship with the generated data. The proposed method can be used for the purpose of initial screening to estimate the performance of an HT-ATES system and for efficiently using HT-ATES as a component in larger energy system models. This method uses the modified Rayleigh number in combination with aquifer thickness and injected volume and has a $$R^2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>R</mml:mi> <mml:mn>2</mml:mn> </mml:msup> </mml:math> of 85%. The analytical relation between energetic efficiency and recovery efficiency was shown to be accurate for all calculated energetic efficiency values above 60% and is less accurate with lower calculated energetic efficiency values.

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Publication Details

Journal
Geothermal Energy
Published
2025-04-22
DOI
https://doi.org/10.1186/s40517-025-00343-8
Citations
3
Primary Topic
Geothermal Energy Systems and Applications
Type
article
Field-Weighted Citation Impact
1.09

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article

Analytically estimating the efficiency of high temperature aquifer thermal energy storage

Alexandros Daniilidis, Gert Jan Kramer, Wen Liu, Martin Bloemendal et al.
3 citations
Geothermal Energy
Geothermal Energy Systems and Applications
1.09
article

Analytically estimating the efficiency of high temperature aquifer thermal energy storage

Alexandros Daniilidis, Gert Jan Kramer, Wen Liu, Martin Bloemendal, David Geerts
article en
3 citations

Abstract

Abstract High-Temperature Aquifer Thermal Energy Storage (HT-ATES) can be used to reduce greenhouse gas emissions from heating. The thermal recovery efficiency is the main parameter indicating the performance of an HT-ATES system and it is influenced by multiple aquifer properties and storage characteristics. This study presents a method for estimating recovery efficiency through numerical modeling, data analysis, and curve fitting. This method shows the relation between the recovery efficiency and various storage conditions, such as aquifer properties and storage temperature. In addition, this research explores an analytical relationship between energetic efficiency and recovery efficiency and verifies that relationship with the generated data. The proposed method can be used for the purpose of initial screening to estimate the performance of an HT-ATES system and for efficiently using HT-ATES as a component in larger energy system models. This method uses the modified Rayleigh number in combination with aquifer thickness and injected volume and has a $$R^2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>R</mml:mi> <mml:mn>2</mml:mn> </mml:msup> </mml:math> of 85%. The analytical relation between energetic efficiency and recovery efficiency was shown to be accurate for all calculated energetic efficiency values above 60% and is less accurate with lower calculated energetic efficiency values.

Geothermal EnergyVol. 13(1)
Utrecht University (NL), Delft University of Technology (NL)
European Commission, European Climate, Infrastructure and Environment Executive Agency, HORIZON EUROPE Framework Programme
Openalex Percentile: Top 24%
Geothermal Energy Systems and Applications
1.09
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Analytically estimating the efficiency of high temperature aquifer thermal energy storage — Alexandros Daniilidis, Gert Jan Kramer, et al. · Geothermal Energy (2025) | TGRS Research Map | TGRS