Data driven predictive control for geothermal heating-cooling system with standing column well

Geothermal energy is a promising source of renewable energy and is gradually gaining attention in application in building heating and cooling system. Standing column wells (SCW) are an efficient way of harnessing geothermal energy for such building applications. However, currently rule-based controllers are used for these geothermal heating-cooling systems with simplifying assumptions to avoid the inherent complexities of the system dynamics. This leaves room for implementing sophisticated yet easy-to-implement control methods which can significantly improve the overall performance of the SCW based geothermal systems. The goal of this project is to design an advanced controller using available measurement data from the existing SCW based geothermal units to achieve improved energy efficiency.

Sayani Seal
Faculty Supervisor: 
Benoit Boulet
Partner University: