[HTML][HTML] Data-driven predictive control for unlocking building energy flexibility: A review
Managing supply and demand in the electricity grid is becoming more challenging due to
the increasing penetration of variable renewable energy sources. As significant end-use …
the increasing penetration of variable renewable energy sources. As significant end-use …
Model predictive control (MPC) for enhancing building and HVAC system energy efficiency: Problem formulation, applications and opportunities
In the last few years, the application of Model Predictive Control (MPC) for energy
management in buildings has received significant attention from the research community …
management in buildings has received significant attention from the research community …
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 …
[HTML][HTML] Approximate model predictive building control via machine learning
Many studies have proven that the building sector can significantly benefit from replacing the
current practice rule-based controllers (RBC) by more advanced control strategies like …
current practice rule-based controllers (RBC) by more advanced control strategies like …
A comprehensive review of predictive control strategies in heating, ventilation, and air-conditioning (HVAC): Model-free VS model
X **n, Z Zhang, Y Zhou, Y Liu, D Wang… - Journal of Building …, 2024 - Elsevier
Predictive control offers significant advantages in nonlinear control, high thermal inertia, and
dynamic control. This article uses a Systematic Reviews and Meta-Analyses methodology to …
dynamic control. This article uses a Systematic Reviews and Meta-Analyses methodology to …
Collaborative scheduling and flexibility assessment of integrated electricity and district heating systems utilizing thermal inertia of district heating network and …
In the traditional scheduling of integrated electricity and district heating systems (IEDHS)
with high penetrations of wind power, large amounts of wind power curtailments can still …
with high penetrations of wind power, large amounts of wind power curtailments can still …
Experiment study of machine-learning-based approximate model predictive control for energy-efficient building control
The adoption of model predictive control (MPC) for building automation and control
applications is challenged by the high hardware and software requirements to solve its …
applications is challenged by the high hardware and software requirements to solve its …
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 …
Solutions for enhancement of energy and exergy efficiencies in air handling units
In this study, five layouts of using air-to-air heat exchangers (AAHE) were added in the Air
Handling Unit (AHU) to diminish the cooling and heating coils energy usage through the …
Handling Unit (AHU) to diminish the cooling and heating coils energy usage through the …
Smart buildings as Cyber-Physical Systems: Data-driven predictive control strategies for energy efficiency
Due to its significant contribution to global energy usage and the associated greenhouse
gas emissions, existing building stock's energy efficiency must improve. Predictive building …
gas emissions, existing building stock's energy efficiency must improve. Predictive building …