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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 …
Data requirements and performance evaluation of model predictive control in buildings: A modeling perspective
Abstract Model predictive control (MPC) has shown great potential in improving building
performance and saving energy. However, after over 20 years of research, it is yet to be …
performance and saving energy. However, after over 20 years of research, it is yet to be …
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 …
A model predictive control strategy to optimize the performance of radiant floor heating and cooling systems in office buildings
This paper introduces a smart operation strategy based on model predictive control (MPC) to
optimize the performance of hydronic radiant floor systems in office buildings and presents …
optimize the performance of hydronic radiant floor systems in office buildings and presents …
Review of control strategies for improving the energy flexibility provided by heat pump systems in buildings
The present work constitutes a review of the existing literature on supervisory control for
improving the energy flexibility provided by heat pumps in buildings. A distinction was drawn …
improving the energy flexibility provided by heat pumps in buildings. A distinction was drawn …
Physics-informed neural networks for building thermal modeling and demand response control
Buildings energy consumption constitutes over 40% of the total primary energy
consumption, and buildings can provide potential energy flexibility for the grid. In the grid …
consumption, and buildings can provide potential energy flexibility for the grid. In the grid …
Data-driven methods for building control—A review and promising future directions
A review of the heating, ventilation and air-conditioning control problem for buildings is
presented with particular emphasis on its distinguishing features. Next, we not only examine …
presented with particular emphasis on its distinguishing features. Next, we not only examine …
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 …
[HTML][HTML] Cloud-based implementation of white-box model predictive control for a GEOTABS office building: A field test demonstration
Abstract Model predictive control (MPC) has been proven in simulations and pilot case
studies to be a superior control strategy for large buildings. MPC can utilize the weather and …
studies to be a superior control strategy for large buildings. MPC can utilize the weather and …
Smart greenhouse control under harsh climate conditions based on data-driven robust model predictive control with principal component analysis and kernel density …
Efficient greenhouse climate control under harsh climate conditions at locations such as
Qatar is a challenge because of the high temperature and high relative humidity. This work …
Qatar is a challenge because of the high temperature and high relative humidity. This work …