Scientific article
OA Policy
English

Techno-economic assessment and operational CO2 emissions of High-Temperature Aquifer Thermal Energy Storage (HT-ATES) using demand-driven and subsurface-constrained dimensioning

Published inEnergy, 123682
Publication date2022-03
Abstract

High-Temperature – Aquifer Thermal Energy Storage (HT-ATES) can significantly increase Renewable Energy Sources (RES) capacity and storage temperature levels compared to traditional ATES, while improving efficiency. Combined assessment of subsurface performance and surface District Heating Networks (DHN) is key, but poses challenges for dimensioning, energy flow matching, and techno-economic performance of the joint system. We present a novel methodology for dimensioning and techno-economic assessment of an HT-ATES system combining subsurface, DHN, operational CO 2 emissions, and economics. Subsurface thermo-hydraulic simulations consider aquifer properties (thickness, permeability, porosity, depth, dip, artesian conditions and groundwater hydraulic gradient) and operational parameters (well pattern and cut-off temperature). Subject to subsurface constraints, aquifer permeability and thickness are major control variables. Transmissivity ≥ 2.5×10 -12 m 3 is required to keep the Levelised Cost Of Heat (LCOH) below 200 CHF/MWh and capacity ≥ 25 MW is needed for the HT-ATES system to compete with other large-scale DHN heat sources. Addition of Heat Pumps (HP) increases the LCOH, but also the nominal capacity of the system and yields higher cumulative avoided CO 2 emissions. The methodology presented exemplifies HT-ATES dimensioning and connection to DHN for planning purposes and opens-up the possibility for their fully-coupled assessment in site-specific assessments.

Funding
  • European Commission - GEOTHERMICA - ERA NET Cofund Geothermal [731117]
  • Autre
Citation (ISO format)
DANIILIDIS, Alexandros et al. Techno-economic assessment and operational CO2 emissions of High-Temperature Aquifer Thermal Energy Storage (HT-ATES) using demand-driven and subsurface-constrained dimensioning. In: Energy, 2022, p. 123682. doi: 10.1016/j.energy.2022.123682
Main files (2)
Article (Published version)
Article (Accepted version)
accessLevelRestricted
Identifiers
Journal ISSN0360-5442
464views
243downloads

Technical informations

Creation14/03/2022 18:29:00
First validation14/03/2022 18:29:00
Update10/04/2026 11:40:19
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