Machine-Learning-Driven Identification of Electrical Phases in Low-Sampling-Rate Consumer Data
Machine-Learning-Driven Identification of Electrical Phases in Low-Sampling-Rate Consumer Data
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Publisher
Basel: MDPI AG
Journal title
Language
English
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Publisher
Basel: MDPI AG
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Scope and Contents
Contents
Accurate electrical phase identification (PI) is essential for efficient grid management, yet existing research predominantly focuses on high-frequency smart meter data, not adequately addressing phase identification with low sampling rates using energy consumption data. This study addresses this gap by proposing a novel method that employs a fully...
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Full title
Machine-Learning-Driven Identification of Electrical Phases in Low-Sampling-Rate Consumer Data
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TN_cdi_doaj_primary_oai_doaj_org_article_1d595922e0874630ab6aa0fae6f3c329
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_1d595922e0874630ab6aa0fae6f3c329
Other Identifiers
ISSN
1996-1073
E-ISSN
1996-1073
DOI
10.3390/en18010128
