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On modelling effects in the battery and thermal storage scheduling problem

Murray, Alexander 1; Schütz, Thomas; Pan, Guanru 1; Müller, Dirk; Hagenmeyer, Veit 1
1 Institut für Automation und angewandte Informatik (IAI), Karlsruher Institut für Technologie (KIT)


The growing use of intermittent renewable energy sources requires an increased amount of storage capacity to match uncertain generation with uncertain demand. A possible solution is the use of thermal and electrical storages. This paper compares several model formulations: mixed integer linear programs (MILPs), nonlinear programs (NLPs), mixed integer nonlinear programs (MINLPs) for optimizing the operation of a multi-modal home energy system comprising heating and electricity subsystems. The respective optimization problems are then resolved within a model predictive control scheme and the final solutions are compared in terms of runtime and optimality. The results indicate that a thermocline-based thermal storage model leads to the overall lowest costs while not significantly impeding computing times. Additionally, the results show that a continuous heat pump model leads to reduced computing times without affecting the modelling accuracy.

Verlagsausgabe §
DOI: 10.5445/IR/1000126053
Veröffentlicht am 26.01.2021
DOI: 10.1080/19401493.2020.1838611
Zitationen: 1
Web of Science
Zitationen: 1
Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 1940-1493, 1940-1507
KITopen-ID: 1000126053
HGF-Programm 37.98.11 (POF III, LK 01) ES 2050
Erschienen in Journal of building performance simulation
Verlag Taylol & Francis
Band 14
Heft 1
Seiten 38–51
Vorab online veröffentlicht am 05.11.2020
Schlagwörter Thermal storages, battery scheduling, model predictive control, mixed integer optimization, nonlinear optimization, modelling
Nachgewiesen in Scopus
Web of Science
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