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Optimal battery control for smart grid nodes

  • Energy storages can be of great value when added to power grids. They introduce the possibility to store and release energy whenever this is favorable. This is particularly relevant, for example, if power supply is volatile (as is the case with renewable energy) and the network is small (so that there are few other nodes that might balance fluctuations in consumption or production). We present models and methods from mathematical optimization for computing an optimized storage schedule for this purpose. We look at alternative optimization objectives, such as smallest possible peak load, low energy costs, or the close approximation of a prescribed load curve. The optimization needs to respect general operational and economic constraints as well as limitations in the use of storage, which are imposed by the chosen storage technology. We therefore introduce alternative approaches for modeling the non-linear properties of energy storages and study their impact on the efficiency of the optimization process. Finally, we present a computational study with batteries as storage devices. We use this to highlight the trade-off between solution quality and computational tractability. A version of the model for the purpose of leveling peaks and instabilities has been implemented into a control system for an office-building smart grid scenario.

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Metadaten
Verfasserangaben:Andreas Draegert, Andreas Eisenblätter, Inken Gamrath, Axel Werner
Herausgeber:in:Katsuki Fujisawa, Yuji Shinano, Hayato Waki
Dokumentart:Konferenzbeitrag
Titel des übergeordneten Werkes (Englisch):Optimization in the Real World - Towards Solving Real-World Optimization Problems
Band:13
Erste Seite:97
Letzte Seite:113
Serie:Mathematics for Industry
Verlag:Springer
Jahr der Erstveröffentlichung:2015
Preprint:urn:nbn:de:0297-zib-53550
DOI:https://doi.org/10.1007/978-4-431-55420-2_6
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