Reducing transient and steady state electricity consumption in HVAC using learning-based model-predictive control
Heating, ventilation, and air conditioning (HVAC) systems are an important target for
efficiency improvements through new equipment and retrofitting because of their large …
efficiency improvements through new equipment and retrofitting because of their large …
Energy-efficient building HVAC control using hybrid system LBMPC
Improving the energy-efficiency of heating, ventilation, and air-conditioning (HVAC) systems
has the potential to realize large economic and societal benefits. This paper concerns the …
has the potential to realize large economic and societal benefits. This paper concerns the …
Development and evaluation of data-driven controls for residential smart thermostats
The advent of smart thermostats with real-time sensing raises the question of how to
preemptively control heating, ventilation, and air conditioning (HVAC) systems to minimize …
preemptively control heating, ventilation, and air conditioning (HVAC) systems to minimize …
[HTML][HTML] Reinforcement learning for whole-building HVAC control and demand response
This paper proposes a novel reinforcement learning (RL) architecture for the efficient
scheduling and control of the heating, ventilation and air conditioning (HVAC) system in a …
scheduling and control of the heating, ventilation and air conditioning (HVAC) system in a …
Gnu-rl: A precocial reinforcement learning solution for building hvac control using a differentiable mpc policy
Reinforcement learning (RL) was first demonstrated to be a feasible approach to controlling
heating, ventilation, and air conditioning (HVAC) systems more than a decade ago …
heating, ventilation, and air conditioning (HVAC) systems more than a decade ago …
[HTML][HTML] Experimental evaluation of model-free reinforcement learning algorithms for continuous HVAC control
Controlling heating, ventilation and air-conditioning (HVAC) systems is crucial to improving
demand-side energy efficiency. At the same time, the thermodynamics of buildings and …
demand-side energy efficiency. At the same time, the thermodynamics of buildings and …
NeurOpt: Neural network based optimization for building energy management and climate control
Abstract Model predictive control (MPC) can provide significant energy cost savings in
building operations in the form of energy-efficient control with better occupant comfort, lower …
building operations in the form of energy-efficient control with better occupant comfort, lower …
Whole building energy model for HVAC optimal control: A practical framework based on deep reinforcement learning
Whole building energy model (BEM) is a physics-based modeling method for building
energy simulation. It has been widely used in the building industry for code compliance …
energy simulation. It has been widely used in the building industry for code compliance …
Data-driven model predictive control with regression trees—an application to building energy management
Model Predictive Control (MPC) plays an important role in optimizing operations of complex
cyber-physical systems because of its ability to forecast system's behavior and act under …
cyber-physical systems because of its ability to forecast system's behavior and act under …
Optimal HVAC building control with occupancy prediction
A Beltran, AE Cerpa - Proceedings of the 1st ACM conference on …, 2014 - dl.acm.org
Buildings account for about 41% of primary energy consumption and 75% of the electricity.
Space heating, space cooling, and ventilation are the dominant end uses, accounting for …
Space heating, space cooling, and ventilation are the dominant end uses, accounting for …