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Towards a subsurface predictive-model environment to simulate aquifer thermal energy storage for demand-side management applications

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Abstract
Considering that coupling electrically-driven heating, ventilation, and air-conditioning (HVAC) systems with thermal energy storage (TES) in buildings is seen as a promising tool for demand-side management (DSM) in the low-voltage grid, we propose to study high and low temperature aquifer thermal energy storage (ATES) for DSM applications and to improve the overall energy efficiency of an open-loop geothermal system connected to a building and a smart-grid. To do so, we present a detailed review of short-term ATES experiments conducted in alluvial aquifers of Belgium with the scope of defining the best prior information to design and construct a predictive-model environment to simulate subsurface ATES scenarios at different DSM frequencies: real time, intraday, interday, and interseasonal. This environment is built upon HydroGeoSphere (HGS): a three-dimensional numerical model describing fully-integrated subsurface and surface flow and solute and heat transport inside porous and fractured media. We focused on shallow and alluvial aquifers by summarizing the key parameters from several study sites of Wallonia (Belgium). The predictive-model environment is built in Matlab and allows to easily adapt the subsurface model to a specific alluvial aquifer as well as to predict any specific responses of the aquifer linked to energy storage and recovery cycles.
Keywords
Aquifer Thermal Energy Storage (ATES), Demand - Side Management (DSM), Predictive modeling

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Chicago
Robert, Tanguy, Thomas Hermans, Nolwenn Lesparre, Guillaume De Schepper, Frédéric Nguyen, Agathe Defourny, Philippe Orban, Serge Brouyère, and Alain Dassargues. 2018. “Towards a Subsurface Predictive-model Environment to Simulate Aquifer Thermal Energy Storage for Demand-side Management Applications.” In Proceedings of SSB 2018, 10th International Conference on System Simulation in Buildings.
APA
Robert, T., Hermans, T., Lesparre, N., De Schepper, G., Nguyen, F., Defourny, A., Orban, P., et al. (2018). Towards a subsurface predictive-model environment to simulate aquifer thermal energy storage for demand-side management applications. Proceedings of SSB 2018, 10th International Conference on System Simulation in Buildings. Presented at the 10th International Conference on System Simulation in Buildings (SSB2018).
Vancouver
1.
Robert T, Hermans T, Lesparre N, De Schepper G, Nguyen F, Defourny A, et al. Towards a subsurface predictive-model environment to simulate aquifer thermal energy storage for demand-side management applications. Proceedings of SSB 2018, 10th International Conference on System Simulation in Buildings. 2018.
MLA
Robert, Tanguy et al. “Towards a Subsurface Predictive-model Environment to Simulate Aquifer Thermal Energy Storage for Demand-side Management Applications.” Proceedings of SSB 2018, 10th International Conference on System Simulation in Buildings. 2018. Print.
@inproceedings{8614301,
  abstract     = {Considering   that   coupling   electrically-driven   heating,   ventilation,   and   air-conditioning (HVAC) systems with thermal energy storage (TES) in buildings is seen as a promising tool for demand-side management (DSM) in the low-voltage grid, we propose to study high and low temperature aquifer thermal energy storage (ATES) for DSM applications and to improve the overall  energy  efficiency  of an open-loop geothermal system  connected  to  a  building  and  a smart-grid. To do so, we present a detailed review of short-term ATES experiments conducted in alluvial 
aquifers of Belgium with the scope of defining the best prior information to design and construct a  predictive-model
environment  to  simulate subsurface ATES scenarios  at  different DSM frequencies:  real  time,  intraday,  interday,  and  interseasonal. This  environment is built  upon HydroGeoSphere  (HGS): a  three-dimensional  numerical  model  describing  fully-integrated subsurface and surface flow and solute and heat transport inside porous and fractured media. We  focused  on shallow and  alluvial  aquifers  by  summarizing  the  key  parameters from several study sites of Wallonia (Belgium). The predictive-model environment is built in Matlab and allows to easily adapt the subsurface model to a specific alluvial aquifer as well as to predict any specific responses of the aquifer linked to energy storage and recovery cycles.},
  author       = {Robert, Tanguy and Hermans, Thomas and Lesparre, Nolwenn and De Schepper, Guillaume and Nguyen, Fr{\'e}d{\'e}ric and Defourny, Agathe and Orban, Philippe and Brouy{\`e}re, Serge and Dassargues, Alain},
  booktitle    = {Proceedings of SSB 2018, 10th International Conference on System Simulation in Buildings},
  language     = {eng},
  location     = {Li{\`e}ge},
  title        = {Towards a subsurface predictive-model environment to simulate aquifer thermal energy storage for demand-side management applications},
  year         = {2018},
}