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Implementation of a scenario-based MPC for HVAC systems: An experimental case study
School of Electrical Engineering, KTH Royal Institute of Technology.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-4310-7938
Kungliga tekniska högskolan, KTH, School of Electrical Engineering, Royal Institute of Technology, Stockholm.
Kungliga tekniska högskolan, KTH, School of Electrical Engineering, Royal Institute of Technology, Stockholm.
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2014 (English)In: 19th IFAC World Congress on International Federation of Automatic Control: IFAC 2014, Cape Town, South Africa 24 - 29 August 2014 / [ed] X. Xia; E. Boje, IFAC, International Federation of Automatic Control , 2014, p. 599-605Conference paper, Published paper (Refereed)
Abstract [en]

Heating, Ventilation and Air Conditioning (HVAC) systems play a fundamental role in maintaining acceptable thermal comfort and air quality levels. Model Predictive Control (MPC) techniques are known to bring significant energy savings potential. Developing effective MPC-based control strategies for HVAC systems is nontrivial since buildings dynamics are nonlinear and influenced by various uncertainties. This complicates the use of MPC techniques in practice. We propose to address this issue by designing a stochastic MPC strategy that dynamically learns the statistics of the building occupancy patterns and weather conditions. The main advantage of this method is the absence of a-priori assumptions on the distributions of the uncertain variables, and that it can be applied to any type of building. We investigate the practical implementation of the proposed MPC controller on a student laboratory, showing its effectiveness and computational tractability.

Place, publisher, year, edition, pages
IFAC, International Federation of Automatic Control , 2014. p. 599-605
Series
I F A C Workshop Series, ISSN 1474-6670 ; 19
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-38632Local ID: d12fa64c-5e05-490c-9fc1-fe65086f2ac1ISBN: 9783902823625 (print)OAI: oai:DiVA.org:ltu-38632DiVA, id: diva2:1012133
Conference
IFAC World Congress : 25/08/2014 - 29/08/2014
Note
Godkänd; 2014; 20150603 (andbra)Available from: 2016-10-03 Created: 2016-10-03 Last updated: 2017-11-25Bibliographically approved

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Varagnolo, Damiano

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