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Experimental operation of a solar-driven climate system with thermal energy storages using mixed-integer nonlinear model predictive control

  • This work presents the results of experimental operation of a solar-driven climate system using mixed-integer nonlinear model predictive control (MPC). The system is installed in a university building and consists of two solar thermal collector fields, an adsorption cooling machine with different operation modes, a stratified hot water storage with multiple inlets and outlets as well as a coldThis work presents the results of experimental operation of a solar-driven climate system using mixed-integer nonlinear model predictive control (MPC). The system is installed in a university building and consists of two solar thermal collector fields, an adsorption cooling machine with different operation modes, a stratified hot water storage with multiple inlets and outlets as well as a cold water storage. The system and the applied modeling approach is described and a parallelized algorithm for mixed-integer nonlinear MPC and a corresponding implementation for the system are presented. Finally, we show and discuss the results of experimental operation of the system and highlight the advantages of the mixed-integer nonlinear MPC application.show moreshow less

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Metadaten
Document Type:Article (reviewed)
Zitierlink: https://opus.hs-offenburg.de/4895
Bibliografische Angaben
Title (English):Experimental operation of a solar-driven climate system with thermal energy storages using mixed-integer nonlinear model predictive control
Author:Adrian Bürger, Daniel Bull, Parantapa Amarsinh SawantStaff MemberORCiDGND, Markus Bohlayer, Andreas Klotz, Daniel Beschütz, Angelika Altmann-Dieses, Marco Braun, Moritz Diehl
Year of Publication:2021
Publisher:Wiley
First Page:1293
Last Page:1319
Parent Title (English):Optimal Control Applications and Methods
Volume:42
Issue:5
ISSN:0143-2087 (Print)
ISSN:1099-1514 (Online)
DOI:https://doi.org/10.1002/oca.2728
URN:https://urn:nbn:de:bsz:ofb1-opus4-48953
Language:English
Inhaltliche Informationen
Institutes:Forschung / INES - Institut für nachhaltige Energiesysteme
Fakultät Maschinenbau und Verfahrenstechnik (M+V)
Institutes:Bibliografie
Formale Angaben
Open Access: Open Access 
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International