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Postprint
DOI: 10.5445/IR/1000075353
Veröffentlicht am 23.04.2018
Originalveröffentlichung
DOI: 10.1007/s00450-017-0343-x

A comprehensive modelling framework for demand side flexibility in smart grids

Barth, Lukas; Ludwig, Nicole; Mengelkamp, Esther; Staudt, Philipp

Abstract:
The increasing share of renewable energy generation in the electricity system comes with significant challenges, such as the volatility of renewable energy sources. To tackle those challenges, demand side management is a frequently mentioned remedy. However, measures of demand side management need a high level of exibility to be successful. Although extensive research exists that describes, models and optimises various processes with exible electrical demands, there is no unified notation. Additionally, most descriptions are very process-specific and cannot be generalised. In this paper, we develop a comprehensive modelling framework to mathematically describe demand side exibility in smart grids while integrating a majority of constraints from different existing models. We provide a universally applicable modelling framework for demand side exibility and evaluate its practicality by looking at how well Mixed-Integer Linear Program (MIP) solvers are able to optimise the resulting models, if applied to artificially generated instances. From the evaluation, we derive that our model improves the performance of previous models while in ... mehr


Zugehörige Institution(en) am KIT Institut für Theoretische Informatik (ITI)
Institut für Angewandte Informatik (IAI)
Institut für Informationswirtschaft und Marketing (IISM)
Publikationstyp Zeitschriftenaufsatz
Jahr 2018
Sprache Englisch
Identifikator ISSN: 1865-2034, 1865-2042, 0178-3564, 0949-2925
URN: urn:nbn:de:swb:90-753530
KITopen ID: 1000075353
HGF-Programm 37.06.01; LK 01
Erschienen in Computer science - research and development
Band 33
Heft 1-2
Seiten 13-23
Bemerkung zur Veröffentlichung Special Issue Paper
Vorab online veröffentlicht am 30.08.2017
Schlagworte demand side management, exibility scheduling, process modelling, smart grids
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