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The 14th International Modelica Conference
Linköping, September 20-24, 2021

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Papers by Damien Picard

Title: Detailed White-Box Non-Linear Model Predictive Control for Scalable Building HVAC Control
Authors: Filip Jorissen, Damien Picard, Kristoff Six and Lieve Helsen
Abstract: Grey-box and black-box MPC approaches for building HVAC applications often use lumped, low-order models with a low level of detail. While such models require smaller computation times, their accuracy is limited and there are practical constraints related to data collection, how to deal with multi-zone buildings and they often do not explicitly model the building HVAC equipment. In this paper we present an alternative approach based on detailed white-box models. TACO, a custom toolchain that builds upon physics-based Modelica models and JModelica, is used to efficiently solve the resulting optimisation problems. This paper presents a case study model of 79 zones and OCP results for this case study are discussed, demonstrating the high potential of detailed white-box MPC.
Keywords: Optimal control of hybrid systems, HVAC, white-box modelling, building automation, TACO, JModelica, MPC
Paper: full paper Creative Commons License
Bibtex:
@InProceedings{modelica.org:Jorissen:2021,
  title = "{Detailed White-Box Non-Linear Model Predictive Control for Scalable Building HVAC Control}",
  author = {Filip Jorissen and Damien Picard and Kristoff Six and Lieve Helsen},
  pages = {315--323},
  doi = {10.3384/ecp21181315},
  booktitle = {Proceedings of the 14th International Modelica Conference},
  location = {Link\"oping, Sweden},
  editor = {Martin Sj\"olund and Lena Buffoni and Adrian Pop and Lennart Ochel},
  isbn = {978-91-7929-027-6},
  issn = {1650-3740},
  month = sep,
  series = {Link\"oping Electronic Conference Proceedings},
  number = {181},
  publisher = {Modelica Association and Link\"oping University Electronic Press},
  year = {2021}
}