Classification of electricity customer groups towards individualized price scheme design

Tao Chen, Kun Qian, Antti Mutanen, Björn Schuller, Pertti Järventausta, Wencong Su

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    7 Citations (Scopus)
    128 Downloads (Pure)

    Abstract

    This paper introduces classification of electricity residential customers into different groups associated with individualized electricity price schemes, such as time-of-use (TOU) or critical peak pricing (CPP). We use an unsupervised learning method, K-means, assisted by a dimensionality reduction technique and an innovative supervised learning method, extreme learning machine (ELM), to cluster daily load profiles based on hourly AMI measurements. Then, the achieved typical daily load profiles are analyzed and utilized for the design of an electricity price scheme for every subgroup based on symbolic aggregate approximation (SAX). These carefully designed and customized retail price schemes can provide a potential tool for price-based and incentive-based demand response in the Smart Grid context.
    Original languageEnglish
    Title of host publication2017 North American Power Symposium (NAPS)
    PublisherIEEE
    Pages1-4
    Number of pages4
    ISBN (Electronic)978-1-5386-2699-3
    DOIs
    Publication statusPublished - 16 Nov 2017
    Publication typeA4 Article in a conference publication
    EventNorth American Power Symposium -
    Duration: 1 Jan 1900 → …

    Conference

    ConferenceNorth American Power Symposium
    Period1/01/00 → …

    Keywords

    • Aggregates
    • Load management
    • Pricing
    • Principal component analysis
    • Smart grids
    • Smart meters

    Publication forum classification

    • Publication forum level 1

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