Occupancy-based HVAC control systems in buildings: A state-of-the-art review
M Esrafilian-Najafabadi, F Haghighat - Building and Environment, 2021 - Elsevier
Intelligent buildings have drawn considerable attention due to rapid progress in
communication and information technologies. These buildings can utilize current and …
communication and information technologies. These buildings can utilize current and …
Reinforcement learning for demand response: A review of algorithms and modeling techniques
JR Vázquez-Canteli, Z Nagy - Applied energy, 2019 - Elsevier
Buildings account for about 40% of the global energy consumption. Renewable energy
resources are one possibility to mitigate the dependence of residential buildings on the …
resources are one possibility to mitigate the dependence of residential buildings on the …
[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 …
Deep reinforcement learning for building HVAC control
Buildings account for nearly 40% of the total energy consumption in the United States, about
half of which is used by the HVAC (heating, ventilation, and air conditioning) system …
half of which is used by the HVAC (heating, ventilation, and air conditioning) system …
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 …
On heat pumps in smart grids: A review
This paper investigates heat pump systems in smart grids, focussing on fields of application
and control approaches that have emerged in academic literature. Based on a review of …
and control approaches that have emerged in academic literature. Based on a review of …
A review of reinforcement learning for autonomous building energy management
K Mason, S Grijalva - Computers & Electrical Engineering, 2019 - Elsevier
The area of building energy management has received a significant amount of interest in
recent years. This area is concerned with combining advancements in sensor technologies …
recent years. This area is concerned with combining advancements in sensor technologies …
Modeling occupant behavior in buildings
In the last four decades several methods have been used to model occupants' presence and
actions (OPA) in buildings according to different purposes, available computational power …
actions (OPA) in buildings according to different purposes, available computational power …
Fusing TensorFlow with building energy simulation for intelligent energy management in smart cities
Buildings account for 35% of the global final energy demand. Efficiency improvements and
advanced control strategies have a significant impact in the reduction of energy costs and …
advanced control strategies have a significant impact in the reduction of energy costs and …
A review of reinforcement learning methodologies for controlling occupant comfort in buildings
Classical building control systems are becoming vulnerable with increasing complexities in
contemporary built environments and energy systems. Due to this, the reinforcement …
contemporary built environments and energy systems. Due to this, the reinforcement …