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Electricity Theft Detection Techniques

TopicLeading institutions, researchers & key papers

Electricity Theft Detection Techniques is a topic indexed in ScholarIQ from OpenAlex.

What is known about Electricity Theft Detection Techniques?

ScholarIQrecord summary

This cluster of papers focuses on the detection and prevention of electricity theft in smart grids, particularly through the use of advanced metering infrastructure, machine learning, deep learning, and anomaly detection techniques. The research explores methods such as support vector machines, decision trees, convolutional neural networks, and feature engineering to address non-technical losses and improve the security of electricity distribution systems.

How many works does Electricity Theft Detection Techniques have?

ScholarIQindexed works

Electricity Theft Detection Techniques has 26 works in the ScholarIQ index. The count is the OpenAlex total, not the number of papers listed on this page.

What is the OpenAlex record for Electricity Theft Detection Techniques?

ScholarIQopenalex

The OpenAlex for Electricity Theft Detection Techniques is on the source record.

What are the most-cited papers on Electricity Theft Detection Techniques?

ScholarIQmost cited works
Ensemble Bagged Tree Based Classification for Reducing Non-Technical Losses in Multan Electric Power Company of Pakistan
Muhammad Salman Saeed, Mohd Wazir Mustafa, Usman Ullah Sheikh, Touqeer Ahmed Jumani, Nayyar Hussain Mirjat
Electronics. 201990 CitationsOPEN ACCESS
Machine learning approach of detecting anomalies and forecasting time-series of IoT devices
Amer Malki, El‐Sayed Atlam, Ibrahim Gad
Alexandria Engineering Journal. 202270 CitationsOPEN ACCESS
Detection of Non-Technical Losses in Power Utilities—A Comprehensive Systematic Review
Muhammad Salman Saeed, Mohd Wazir Mustafa, Nawaf N. Hamadneh, Nawa Alshammari, Usman Ullah Sheikh, Touqeer Ahmed Jumani, S.N. Khalid, Ilyas Khan
Energies. 202067 CitationsOPEN ACCESS
Data-driven intelligent method for detection of electricity theft
Junde Chen, Yaser A. Nanehkaran, Weirong Chen, Yajun Liu, Defu Zhang
International Journal of Electrical Power & Energy Systems. 202334 Citations
A multi-tier architecture for data analytics in smart metering systems
Juan Carlos Olivares, Enrique Reyes‐Archundia, José Antonio Gutiérrez Gnecchi, Johan W. González-Murueta, Jaime Cerda-Jacobo
Simulation Modelling Practice and Theory. 201927 Citations

Where is Electricity Theft Detection Techniques research published, and who funds it?

ScholarIQvenues & funding sources

TOP FUNDERS

National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
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How much of the research on Electricity Theft Detection Techniques is open access?

ScholarIQopen access share
50%OPEN ACCESS
Gold
50%
Green
0%
Hybrid
0%
Bronze
0%
Closed
50%

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