Deep learning

A practical deep reinforcement learning framework for multivariate occupant-centric control in buildings

Reinforcement learning (RL) has been shown to have the potential for optimal control of heating, ventilation, and air conditioning (HVAC) systems. Although research on RL-based building control has received extensive attention in recent years, there …

Deep learning and physics-based modeling for the optimization of ice-based thermal energy systems in cooling plants

Renewable energy usage is continuing to increase as many countries worldwide are aiming to reach peak carbon emission and achieve carbon neutrality in the near future. One inherent problem with renewable energy is that its generation profile does not …

Calibrating building simulation models using multi-source datasets and meta-learned Bayesian optimization

Reliable building simulation models are key to optimizing building performance and reducing greenhouse gas emissions. Informed decision making requires simulation models to be accurate, extrapolatable, and interpretable, all of which require …