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
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} }