A sequential Bayesian approach to online power quality anomaly segmentation

Jiang, Xu and Stephen, Bruce and McArthur, Stephen (2020) A sequential Bayesian approach to online power quality anomaly segmentation. IEEE Transactions on Industrial Informatics. ISSN 1551-3203 (https://doi.org/10.1109/TII.2020.3003979)

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Abstract

Increased observability on power distribution networks can reveal signs of incipient faults which can develop into costly and unexpected plant failures. While low-cost sensing and communications infrastructure is facilitating this, it is also highlighting the complex nature of fault signals, a challenge which entails precisely extracting anomalous regions from continuous data streams before classifying the underlying fault signature. Doing this incorrectly will result in capture of uninformative data. Extraction processes can be confounded by operational noise on the network including harmonics produced by embedded generation. In this paper, an online model is proposed. Our Bayesian Changepoint Power Quality anomaly Segmentation allows automated segmentation of anomalies from continuous current waveforms, irrespective of noise. Demonstration of the effectiveness of the proposed technique is carried out with operational field data as well as a challenging simulated network, highlighting the ability to accommodate noise from typical network penetration levels of power electronic devices.

  • Item type:Article
    ID code:72866
    Dates:
    Date
    Event
    22 June 2020
    Published
    22 June 2020
    Published Online
    13 June 2020
    Accepted
    Notes:© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:24 Jun 2020 11:15
    Last modified:14 Apr 2024 00:52
    URI:https://strathprints.strath.ac.uk/id/eprint/72866
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