ATES-smart grids

Due to large demand for ATES many urban aquifers experience scarcity of space to accommodate the demand for ATES systems. Under current practice ATES wells are placed at large mutual distance. This distance can be reduced when applying a self organization planning governance structure together with a Distributed Model-based Predictive Control (D-MPC). These methods  promise significant benefits by ensuring near-optimal operation and regulation of ATES grids while enforcing critical operating constraints. However, stochastic uncertainties with probabilistic time-varying constraints have never been incorporated in the design of such a distributed control network. This research sets out to deliver a proof-of-concept for the potential of D-MPC in the development of ATES systems into ATES Smart Grids.

Keywords: Shallow geothermal, storage

TUD researchers involved:
Martin Bloemendal
Tamas Kevicky (ME)
Jan Kwakkel (TPM)

Funder: NWO