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000903587 1001_ $$0P:(DE-Juel1)176842$$aHoffmann, Maximilian$$b0$$eCorresponding author$$ufzj
000903587 245__ $$aTypical periods or typical time steps? A multi-model analysis to determine the optimal temporal aggregation for energy system models
000903587 260__ $$aAmsterdam [u.a.]$$bElsevier Science$$c2021
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000903587 520__ $$aEnergy system models are challenged by the need for high temporal and spatial resolutions in order to appropriately depict the increasing share of intermittent renewable energy sources, storage technologies, and the growing interconnectivity across energy sectors.This study compares different temporal aggregation strategies, which reduce the number of considered time steps, to maintain computational viability of these models. The work focuses on the representation of time series by a subset of single time steps (i.e., typical time steps), or by groups of consecutive time steps (i.e., typical periods), which are commonly applied in the literature using clustering. We test these techniques for two different energy system models and benchmark the optimization results based on aggregation to those of the fully resolved models. Further, centroids and medoids are used to represent the clustered datasets and it is investigated whether the optimal aggregation method can be determined based on clustering indicators only.
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000903587 7001_ $$0P:(DE-HGF)0$$aPriesmann, Jan$$b1
000903587 7001_ $$0P:(DE-HGF)0$$aNolting, Lars$$b2
000903587 7001_ $$0P:(DE-HGF)0$$aPraktiknjo, Aaron$$b3
000903587 7001_ $$0P:(DE-Juel1)168451$$aKotzur, Leander$$b4$$ufzj
000903587 7001_ $$0P:(DE-Juel1)129928$$aStolten, Detlef$$b5$$ufzj
000903587 773__ $$0PERI:(DE-600)2000772-3$$a10.1016/j.apenergy.2021.117825$$gVol. 304, p. 117825 -$$p117825 -$$tApplied energy$$v304$$x0306-2619$$y2021
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