There are strong policy drivers for the promotion of energy efficiency in buildings. In the literature, Model Predictive Control (MPC) is seen as a promising solution to deal with the energy management problem in buildings. Model identification is the primary task involved in the design of MPC control and defining the good level of complexity for the thermal dynamic model is a critical question. This paper focuses on the development of reliable models that can be used to support the deployment of (Distributive (Di)) MPC application
Rule-based control (RBC) strategies are often unable to execute the optimal control action, which le...
Model uncertainty is a significant challenge to more widespread use of model predictive controllers ...
Advantages of Model Predictive Control (MPC) strategies for control of building energy systems have ...
International audienceThere are strong policy drivers for the promotion of energy efficiency in buil...
In the last few years, the application of Model Predictive Control (MPC) for energy management in bu...
© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Model Predictive Control (MPC) is a good candidate to exploit the energy cost savings potential of C...
Model predictive control (MPC) is a control technique with a large potential to reduce the energy co...
A model-based predictive control (MPC) is designed for optimal thermal energy storage in building co...
Model-based control of building energy offers an attractive way to minimize energy consumption in bu...
The building sector consumes about 40% of energy used in the United States and is responsible for ne...
Controllers employing optimal control strategies will path the way to enable flexible operations in ...
© 2015 American Automatic Control Council. This paper deals with identification of a building model ...
Model predictive controllers (MPC) have shown great potential for activating the energy flexibility ...
Within the last decade, needs for building control systems that reduce cost, energy, or peak demand,...
Rule-based control (RBC) strategies are often unable to execute the optimal control action, which le...
Model uncertainty is a significant challenge to more widespread use of model predictive controllers ...
Advantages of Model Predictive Control (MPC) strategies for control of building energy systems have ...
International audienceThere are strong policy drivers for the promotion of energy efficiency in buil...
In the last few years, the application of Model Predictive Control (MPC) for energy management in bu...
© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Model Predictive Control (MPC) is a good candidate to exploit the energy cost savings potential of C...
Model predictive control (MPC) is a control technique with a large potential to reduce the energy co...
A model-based predictive control (MPC) is designed for optimal thermal energy storage in building co...
Model-based control of building energy offers an attractive way to minimize energy consumption in bu...
The building sector consumes about 40% of energy used in the United States and is responsible for ne...
Controllers employing optimal control strategies will path the way to enable flexible operations in ...
© 2015 American Automatic Control Council. This paper deals with identification of a building model ...
Model predictive controllers (MPC) have shown great potential for activating the energy flexibility ...
Within the last decade, needs for building control systems that reduce cost, energy, or peak demand,...
Rule-based control (RBC) strategies are often unable to execute the optimal control action, which le...
Model uncertainty is a significant challenge to more widespread use of model predictive controllers ...
Advantages of Model Predictive Control (MPC) strategies for control of building energy systems have ...