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Identification of Typical and Anomalous Patterns in Electricity Consumption

Title
Identification of Typical and Anomalous Patterns in Electricity Consumption
Type
Article in International Scientific Journal
Year
2022
Authors
José Nuno Fidalgo
(Author)
FEUP
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Pedro Macedo
(Author)
Other
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Journal
Title: Applied SciencesImported from Authenticus Search for Journal Publications
Vol. 209
Pages: 1-3317
Publisher: MDPI
Indexing
Publicação em ISI Web of Knowledge ISI Web of Knowledge - 0 Citations
Publicação em Scopus Scopus - 0 Citations
Other information
Authenticus ID: P-00W-ARQ
Resumo (PT):
Abstract (EN): Nontechnical losses in electricity distribution networks are often associated with a countries' socioeconomic situation. Although the amount of global losses is usually known, the separation between technical and commercial (nontechnical) losses will remain one of the main challenges for DSO until smart grids become fully implemented and operational. The most common origins of commercial losses are energy theft and deliberate or accidental failures of energy measuring equipment. In any case, the consequences can be regarded as consumption anomalies. The work described in this paper aims to answer a request from a DSO, for the development of tools to detect consumption anomalies at end-customer facilities (HV, MV and LV), invoking two types of assessment. The first consists of the identification of typical patterns in the set of consumption profiles of a given group or zone and the detection of atypical consumers (outliers) within it. The second assessment involves the exploration of the load diagram evolution of each specific consumer to detect changes in the consumption pattern that could represent situations of probable irregularities. After a representative period, typically 12 months, these assessments are repeated, and the results are compared to the initial ones. The eventual changes in the typical classes or consumption scales are used to build a classifier indicating the risk of anomaly.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 16
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