[HTML][HTML] Reinforcement learning for HVAC control in intelligent buildings: A technical and conceptual review
Abstract Heating, Ventilation and Air Conditioning (HVAC) systems in buildings are a major
source of global operational CO 2 emissions, primarily due to their high energy demands …
source of global operational CO 2 emissions, primarily due to their high energy demands …
[HTML][HTML] Reinforced model predictive control (RL-MPC) for building energy management
Buildings need advanced control for the efficient and climate-neutral use of their energy
systems. Model predictive control (MPC) and reinforcement learning (RL) arise as two …
systems. Model predictive control (MPC) and reinforcement learning (RL) arise as two …
Ten questions concerning reinforcement learning for building energy management
As buildings account for approximately 40% of global energy consumption and associated
greenhouse gas emissions, their role in decarbonizing the power grid is crucial. The …
greenhouse gas emissions, their role in decarbonizing the power grid is crucial. The …
Comparison of reinforcement learning and model predictive control for building energy system optimization
Advanced controls could enhance buildings' energy efficiency and operational flexibility
while guaranteeing the indoor comfort. The control performance of reinforcement learning …
while guaranteeing the indoor comfort. The control performance of reinforcement learning …
[HTML][HTML] Evaluation of advanced control strategies for building energy systems
Advanced building control strategies like model predictive control and reinforcement
learning can consider forecasts for weather, occupancy, and energy prices. Combined with …
learning can consider forecasts for weather, occupancy, and energy prices. Combined with …
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 …
The functional mockup interface for tool independent exchange of simulation models
T Blochwitz, M Otter, M Arnold, C Bausch… - Proceedings of the 8th …, 2011 - elib.dlr.de
The Functional Mockup Interface (FMI) is a tool independent standard for the exchange of
dynamic models and for co-simulation. The development of FMI was initiated and organized …
dynamic models and for co-simulation. The development of FMI was initiated and organized …
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 …
[HTML][HTML] Reinforcement learning model-based and model-free paradigms for optimal control problems in power systems: Comprehensive review and future directions
E Ginzburg-Ganz, I Segev, A Balabanov, E Segev… - Energies, 2024 - mdpi.com
This paper reviews recent works related to applications of reinforcement learning in power
system optimal control problems. Based on an extensive analysis of works in the recent …
system optimal control problems. Based on an extensive analysis of works in the recent …
Energy saving and indoor temperature control for an office building using tube-based robust model predictive control
Actively controlling a building's heating, ventilation, and air conditioning (HVAC) system can
reduce costs and improve indoor comfort. Model predictive control (MPC) is an effective …
reduce costs and improve indoor comfort. Model predictive control (MPC) is an effective …