Implementing an efficient control strategy for heating, ventilation, and air conditioning
(HVAC) systems can lead to improvements in both energy efficiency and thermal …

It has been proven that advanced building control, like model predictive control (MPC), can
notably reduce the energy use and mitigate greenhouse gas emissions. However, despite …

Advanced building control strategies like model predictive control and reinforcement
learning can consider forecasts for weather, occupancy, and energy prices. Combined with …

We present a physics-constrained deep learning method to develop control-oriented models
of building thermal dynamics. The proposed method uses systematic encoding of physics …

Smart buildings aim to create a safe, comfortable and sustainable environment for the
occupants while increasing the energy performance of the building to reduce the …

Abstract Model Predictive Control (MPC) can be used in the context of building automation
to improve energy efficiency and occupant comfort. Ideally, the MPC algorithm should …

Accurate forecasting of cooling and heating loads is critical for optimizing the energy usage
of devices and planning for energy storage in building district energy systems (BDESs). Data …

Community energy systems, integrating electricity storage, smart transportation, and flexible
energy interactions can mitigate renewable energy intermittency and uncertainty, and …

The implementation of load management and demand response programs is motivating
utilities to propose demand-side management to incentivize customers to modify their …

Abstract Model Predictive Control has gained much attention due to its potential to improve
building operations by reducing costs, integrating renewable energy sources, and …