Data-driven Demand Response Characterization and Quantification

Guillaume Le Ray, Pierre Pinson, Emil Mahler Larsen

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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    Abstract

    Analysis of load behavior in demand response (DR) schemes is important to evaluate the performance of participants. Very few real-world experiments have been carried out and quantification and characterization of the response is a difficult task. Nevertheless it will be a necessary tool for portfolio management of consumers in a DR framework. In this paper we develop methods to quantify and characterize the amount of DR in a load. The contribution to the aggregated load from each household is quantified on a daily basis, showing the potential variability of the response in time. Clustering on the average values and standard deviation of the contribution regroups households with the same average response. Independent Component Analysis (ICA) is used to characterize different DR delivery profiles.
    Original languageEnglish
    Title of host publicationProceedings of 12th IEEE Power and Energy Society PowerTech Conference
    Number of pages6
    PublisherIEEE
    Publication date2017
    Publication statusPublished - 2017
    Event12th IEEE Power and Energy Society PowerTech Conference: Towards and Beyond Sustainable Energy Systems - University Place, University of Manchester., Manchester, United Kingdom
    Duration: 18 Jun 201722 Jun 2017

    Conference

    Conference12th IEEE Power and Energy Society PowerTech Conference
    LocationUniversity Place, University of Manchester.
    Country/TerritoryUnited Kingdom
    CityManchester
    Period18/06/201722/06/2017

    Keywords

    • Demand Response (DR)
    • DR characterization
    • DR quantification
    • Smart grid
    • Energy analytics

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