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

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.

Jaar van publicatie:2018

Toegankelijkheid:Closed