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المؤلفHimeur, Yassine
المؤلفAlsalemi, Abdullah
المؤلفBensaali, Faycal
المؤلفAmira, Abbes
تاريخ الإتاحة2022-12-29T07:34:40Z
تاريخ النشر2021
اسم المنشورInternational Journal of Intelligent Systems
المصدرScopus
معرّف المصادر الموحدhttp://dx.doi.org/10.1002/int.22292
معرّف المصادر الموحدhttp://hdl.handle.net/10576/37788
الملخصNonintrusive load monitoring (NILM) is the de facto technique for extracting device-level power consumption fingerprints at (almost) no cost from only aggregated mains readings. Specifically, there is no need to install an individual meter for each appliance. However, a robust NILM system should incorporate a precise appliance identification module that can effectively discriminate between various devices. In this context, this paper proposes a powerful method to extract accurate power fingerprints for electrical appliance identification. Rather than relying solely on time-domain (TD) analysis, this framework abstracts the phase encoding of the TD description of power signals using a two-dimensional (2D) representation. This allows mapping power trajectories to a novel 2D binary representation space, and then performing a histogramming process after converting binary codes to new decimal representations. This yields the final histogram of 2D phase encoding of power signals, namely, 2D-PEP. An empirical performance evaluation conducted with three realistic power consumption databases collected at distinct resolutions indicates that the proposed 2D-PEP descriptor achieves outperformance for appliance identification in comparison with other recent techniques. Accordingly, high identification accuracies are attained on the GREEND, UK-DALE, and WHITED data sets, where 99.54%, 98.78%, and 100% rates have been achieved, respectively, using the proposed 2D-PEP descriptor. 2020 The Authors. International Journal of Intelligent Systems published by Wiley Periodicals LLC
راعي المشروعThis paper was made possible by National Priorities Research Program (NPRP) Grant No. 10-0130-170288 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. Open Access funding provided by the Qatar National Library.
اللغةen
الناشرJohn Wiley and Sons Ltd
الموضوعappliance identification
classification
feature extraction
nonintrusive load monitoring
phase encoding
العنوانAn intelligent nonintrusive load monitoring scheme based on 2D phase encoding of power signals
النوعArticle
الصفحات72-93
رقم العدد1
رقم المجلد36
dc.accessType Open Access


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