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Outlining Ensemble K-Nearest Neighbors Approach for Low-Voltage Power Demand Forecasting


Oleg Valgaev, Friederich Kupzog, Hartmut Schmeck



Published: 2017 Mai

Buchtitel: e-Energy '17 Proceedings of the Eighth International Conference on Future Energy Systems
Seiten: 268-270
Verlag: ACM
Erscheinungsort: New York
Organisation: ACM
Nicht-referierte Veröffentlichung
BibTeX

Kurzfassung
Following the ongoing transformation of the European power system, in the future, it will be necessary to locally balance the increasing share of decentralized renewable energy supply. Therefore, a reliable short-term load forecast down to the level of single low-voltage end-consumers might be required. In this work, we outline how to improve the K-Nearest Neighbors forecaster that we have proposed earlier for the low voltage load forecasting. We motivate the usage of the, so called, Ensemble K-Nearest Neighbors indicating a significant improvement by combining the forecasts obtained using different numbers of nearest neighbors.

ISBN: 978-1-4503-5036-5
DOI Link: 10.1145/3077839.3081681



Forschungsgruppe

Effiziente Algorithmen


Forschungsgebiet
Energieinformatik