Research Explorer

Project

Improving Aquifer Thermal Energy Storage Systems Design through Advanced Hydrogeological Uncertainty Quantification (ATES2.0)
Code
01D03222
Duration
01 November 2022 → 31 October 2023
Funding
Regional and community funding: Special Research Fund
Research disciplines
  • Natural sciences
    • Hydrogeology
    • Geology not elsewhere classified
  • Engineering and technology
    • Renewable power and energy systems engineering
    • Energy storage
    • Geothermal energy
Keywords
Aquifer thermal energy storage (ATES) system Bayesian Evidential Learning Uncertainty quantification
 
Project description
 

Shallow geothermal energy is a sustainable alternative to provide heating or cooling to buildings. The objective of this research is to improve the design of shallow geothermal systems and predict the uncertainty of their energy efficiency using a new stochastic framework called Bayesian evidential learning (BEL). The method will be validated on two in-use aquifer thermal energy storage systems.