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Building power demand forecasting using K-nearest neighbours model – practical application in Smart City Demo Aspern project


Building power demand forecasting using K-nearest neighbours model – practical application in Smart City Demo Aspern project



Veröffentlicht: 2017 Oktober

Journal: CIRED-Open Access Proceedings Journal
Nummer: 1
Seiten: 1601-1604

Volume: 2017


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 decentralised renewable energy supply. Therefore, a reliable short-term load forecast at the level of single buildings is required. In this study, we use a forecaster, which is based on K -nearest neighbours approach and was introduced in an earlier publication, on three buildings of Smart City Demo Aspern project. The authors demonstrate how this forecaster can be applied on different buildings without any manual setup or parametrisation, showing that it is viable to replace load-profiling solutions for predicting electricity consumption at the level of single buildings.e



Forschungsgruppe

Effiziente Algorithmen/en„Effiziente Algorithmen/en“ befindet sich nicht in der Liste (Effiziente Algorithmen, Komplexitätsmanagement, Betriebliche Informationssysteme, Wissensmanagement, Angewandte Technisch-Kognitive Systeme, Information Service Engineering, Critical Information Infrastructures, Web Science und Wissensmanagement, Web Science, Ökonomie und Technologie der eOrganisation, ...) zulässiger Werte für das Attribut „Forschungsgruppe“.


Forschungsgebiet

Energieinformatik, Sicherheit