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001     878533
005     20230531203011.0
024 7 _ |a 10.1109/ACCESS.2020.3016477
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037 _ _ |a FZJ-2020-02896
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100 1 _ |a Kruse, Johannes
|0 P:(DE-Juel1)179250
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245 _ _ |a Predictability of power grid frequency
260 _ _ |a New York, NY
|c 2020
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500 _ _ |a Aaditional funding not listed by the system: European Union’s Horizon 2020 Research and Innovation Programme through the Marie Skłodowska-Curie Grant under Agreement 840825
520 _ _ |a The power grid frequency is the central observable in power system control, as it measures thebalance of electrical supply and demand. A reliable frequency forecast can facilitate rapid control actions andmay thus greatly improve power system stability. Here, we develop a weighted-nearest-neighbour (WNN) predictor to investigate how predictable the frequency trajectories are. Our forecasts for up to one hourare more precise than averaged daily profiles and could increase the efficiency of frequency control actions.Furthermore, we gain an increased understanding of the specific properties of different synchronous areas byinterpreting the optimal prediction parameters (number of nearest neighbours, the prediction horizon, etc.)in terms of the physical system. Finally, prediction errors indicate the occurrence of exceptional externalperturbations. Overall, we provide a diagnostics tool and an accurate predictor of the power grid frequencytime series, allowing better understanding of the underlying dynamics.
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700 1 _ |a Schäfer, Benjamin
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700 1 _ |a Witthaut, Dirk
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773 _ _ |a 10.1109/ACCESS.2020.3016477
|g Vol. 8, p. 149435 - 149446
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