Successful application of predictive information in deep reinforcement learning control: A case study based on an office building HVAC system
Reinforcement Learning (RL), a promising algorithm for the operational control of Heating,
Ventilation, and Air Conditioning (HVAC) systems, has garnered considerable attention and …
Ventilation, and Air Conditioning (HVAC) systems, has garnered considerable attention and …
Practical implementation and evaluation of deep reinforcement learning control for a radiant heating system
Deep reinforcement learning (DRL) has become a popular optimal control method in recent
years. This is mainly because DRL has the potential to solve the optimal control problems …
years. This is mainly because DRL has the potential to solve the optimal control problems …
Comparative study of model-based and model-free reinforcement learning control performance in HVAC systems
Reinforcement learning (RL) shows the potential to address drawbacks of rule-based control
and model predictive control and exhibits great effectiveness in heating, ventilation and air …
and model predictive control and exhibits great effectiveness in heating, ventilation and air …
A Comparison of Classical and Deep Reinforcement Learning Methods for HVAC Control
Reinforcement learning (RL) is a promising approach for optimizing HVAC control. RL offers
a framework for improving system performance, reducing energy consumption, and …
a framework for improving system performance, reducing energy consumption, and …
Building HVAC control with reinforcement learning for reduction of energy cost and demand charge
Z Jiang, MJ Risbeck, V Ramamurti, S Murugesan… - Energy and …, 2021 - Elsevier
Energy efficiency remains a significant topic in the control of building heating, ventilation,
and air-conditioning (HVAC) systems, and diverse set of control strategies have been …
and air-conditioning (HVAC) systems, and diverse set of control strategies have been …
Deep reinforcement learning for residential HVAC control with consideration of human occupancy
The Artificial Intelligence (AI) development described herein uses model-free Deep
Reinforcement Learning (DRL) to minimize energy cost during residential heating …
Reinforcement Learning (DRL) to minimize energy cost during residential heating …
Multi-zone hvac control with model-based deep reinforcement learning
The application of reinforcement learning in controlling Heating, Ventilation, and Air
Conditioning (HVAC) systems has been extensively researched. Existing studies primarily …
Conditioning (HVAC) systems has been extensively researched. Existing studies primarily …
Evaluating the adaptability of reinforcement learning based HVAC control for residential houses
K Kurte, J Munk, O Kotevska, K Amasyali, R Smith… - Sustainability, 2020 - mdpi.com
Intelligent Heating, Ventilation, and Air Conditioning (HVAC) control using deep
reinforcement learning (DRL) has recently gained a lot of attention due to its ability to …
reinforcement learning (DRL) has recently gained a lot of attention due to its ability to …
[HTML][HTML] Real building implementation of a deep reinforcement learning controller to enhance energy efficiency and indoor temperature control
Abstract Deep Reinforcement Learning (DRL) has emerged as a promising approach to
address the trade-off between energy efficiency and indoor comfort in buildings, potentially …
address the trade-off between energy efficiency and indoor comfort in buildings, potentially …
ED-DQN: An event-driven deep reinforcement learning control method for multi-zone residential buildings
Q Fu, Z Li, Z Ding, J Chen, J Luo, Y Wang, Y Lu - Building and Environment, 2023 - Elsevier
Abstract Residential Heating, Ventilation, and Air conditioning (HVAC) systems are
responsible for a significant amount of energy consumption, but their management is …
responsible for a significant amount of energy consumption, but their management is …