Comparison of Model Complexities in Optimal Control Tested in a Real Thermally Activated Building System

• Main Authors: Arroyo, J. (Author), Helsen, L. (Author), Spiessens, F. (Author)
• Format: Article
• Language: English
• Published: MDPI 2022
• Subjects: advanced controls; control-oriented models; energy efficiency; model predictive control; optimization; thermal comfort
• Online Access: View Fulltext in Publisher

 Building predictive control has proven to achieve energy savings and higher comfort levels than classical rule-based controllers. The choice of the model complexity needed to be used in modelbased optimal control is not trivial, and a wide variety of model types is implemented in the scientific literature. This paper shares practical aspects of implementing different control-oriented models for model predictive control in a building. A real thermally activated test building is used to compare the white-, grey-, and black-box modeling paradigms in prediction and control performance. The experimental results obtained in our particular case reveal that there is not a significant correlation between prediction and control performance and highlight the importance of modeling the heat emission system based on physics. It is also observed that most of the complexity of the physicsbased model arises from the building envelope while this part of the building is the most sensitive to weather forecast uncertainty. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.