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Large-Scale Detection of Non-Technical Losses in Imbalanced Data Sets
Glauner, Patrick; Boechat, Andre; Dolberg, Lautaro et al.
2016In Proceedings of the Seventh IEEE Conference on Innovative Smart Grid Technologies (ISGT 2016)
Peer reviewed
 

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Keywords :
Electricity Theft Detection; Fuzzy Logic; Imbalanced Classification; Non-Technical Losses; Support Vector Machine
Abstract :
[en] Non-technical losses (NTL) such as electricity theft cause significant harm to our economies, as in some countries they may range up to 40% of the total electricity distributed. Detecting NTLs requires costly on-site inspections. Accurate prediction of NTLs for customers using machine learning is therefore crucial. To date, related research largely ignore that the two classes of regular and non-regular customers are highly imbalanced, that NTL proportions may change and mostly consider small data sets, often not allowing to deploy the results in production. In this paper, we present a comprehensive approach to assess three NTL detection models for different NTL proportions in large real world data sets of 100Ks of customers: Boolean rules, fuzzy logic and Support Vector Machine. This work has resulted in appreciable results that are about to be deployed in a leading industry solution. We believe that the considerations and observations made in this contribution are necessary for future smart meter research in order to report their effectiveness on imbalanced and large real world data sets.
Disciplines :
Computer science
Author, co-author :
Glauner, Patrick ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Boechat, Andre;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Dolberg, Lautaro;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
State, Radu  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Bettinger, Franck;  CHOICE Technologies Holding Sàrl
Rangoni, Yves;  CHOICE Technologies Holding Sàrl
Duarte, Diogo;  CHOICE Technologies Holding Sàrl
External co-authors :
no
Language :
English
Title :
Large-Scale Detection of Non-Technical Losses in Imbalanced Data Sets
Publication date :
2016
Event name :
Seventh IEEE Conference on Innovative Smart Grid Technologies (ISGT 2016)
Event organizer :
IEEE
Event place :
Minneapolis, United States
Event date :
from 06-09-2016 to 09-09-2016
Audience :
International
Main work title :
Proceedings of the Seventh IEEE Conference on Innovative Smart Grid Technologies (ISGT 2016)
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
Available on ORBilu :
since 08 September 2016

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