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Model predictive control of residential energy systems using energy storage and controllable loads

Title data

Braun, Philipp ; Grüne, Lars ; Kellett, Christopher M. ; Weller, Steven R. ; Worthmann, Karl:
Model predictive control of residential energy systems using energy storage and controllable loads.
In: Russo, Giovanni ; Capasso, Vincenzo ; Nicosia, Giuseppe ; Romano, Vittorio (ed.): Progress in Industrial Mathematics at ECMI 2014. - Heidelberg : Springer , 2016 . - pp. 617-623 . - (Mathematics in Industry ; 22 )
ISBN 978-3-319-23413-7
DOI: https://doi.org/10.1007/978-3-319-23413-7_85

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Abstract in another language

Local energy storage and smart energy scheduling can be used to fatten energy profiles with undesirable peaks. Extending a recently developed model to allow controllable loads, we present Centralized and Decentralized Model Predictive Control algorithms to reduce these peaks. Numerical results show that the additional degree of freedom leads to improved performance.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: model predictive control; smart grid application; distributed control
Institutions of the University: Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics V (Applied Mathematics)
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics V (Applied Mathematics) > Chair Mathematics V (Applied Mathematics) - Univ.-Prof. Dr. Lars Grüne)
Profile Fields
Profile Fields > Advanced Fields
Profile Fields > Advanced Fields > Nonlinear Dynamics
Research Institutions > Research Centres > Forschungszentrum für Modellbildung und Simulation (MODUS)
Research Institutions
Research Institutions > Research Centres
Result of work at the UBT: Yes
DDC Subjects: 500 Science > 510 Mathematics
Date Deposited: 18 Sep 2017 09:16
Last Modified: 18 Sep 2017 09:16
URI: https://eref.uni-bayreuth.de/id/eprint/39668

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