Towards Flexibility Detection in Device-Level Energy Consumption

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

20 Citations (Scopus)


The increasing drive towards green energy has boosted the installation of Renewable Energy Sources (RES). Increasing the share of RES in the power grid requires demand management by flexibility in the consumption. In this paper, we perform a state-of-the-art analysis on the flexibility and operation patterns of the devices in a set of real households. We propose a number of specific pre-processing steps such as operation stage segmentation, and aberrant operation duration removal to clean device level data. Further, we demonstrate various device operation properties such as hourly and daily regularities and patterns and the correlation between operating different devices. Subsequently, we show the existence of detectable time and energy flexibility in device operations. Finally, we provide various results providing a foundation for load- and flexibility-detection and -prediction at the device level.
Original languageEnglish
Title of host publicationData Analytics for Renewable Energy Integration : Proceedings of the Second ECML PKDD Workshop, DARE 2014
EditorsWei Lee Woon, Zeyar Aung, Stuart Madnick
PublisherSpringer Publishing Company
Publication date2014
ISBN (Print)978-3-3191-3289-1
Publication statusPublished - 2014
EventData Analytics for Renewable Energy Integration: Second ECML PKDD Workshop, DARE 2014 - Centre Prouvé, Nancy, France
Duration: 19 Sep 2014 → …
Conference number: Second


WorkshopData Analytics for Renewable Energy Integration
LocationCentre Prouvé
Period19/09/2014 → …
SeriesLecture Notes in Computer Science


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