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On modelling effects in the battery and thermal storage scheduling problem

Murray, Alexander; Schütz, Thomas; Pan, Guanru; Müller, Dirk; Hagenmeyer, Veit

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
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 Dimensions
Web of Science
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