Scientometric Analysis of Publications on Household Electricity Theft and Energy Consumption Load Profiling in a Smart Grid Context

José Antonio Moreira de Rezende (), Reginaldo Gonçalves Leão Junior and Otávio de Souza Martins Gomes
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José Antonio Moreira de Rezende: Academic Area of Electrical Engineering, Federal Institute of Minas Gerais (IFMG), Formiga 35570-000, MG, Brazil
Reginaldo Gonçalves Leão Junior: Basic Academic Division, Federal Institute of Minas Gerais (IFMG), Arcos 35600-306, MG, Brazil
Otávio de Souza Martins Gomes: Institute of Systems Engineering and Information Technology, Federal University of Itajubá (UNIFEI), Itajubá 37500-903, MG, Brazil

Sustainability, 2024, vol. 16, issue 22, 1-19

Abstract: This study provides a scientometric analysis of research focused on energy theft detection and load profiling in smart grid networks. Data were retrieved from the Web of Science and Scopus databases, covering publications from 2003 to April 2024. Using the Bibliometrix package and VOSviewer software, we analyzed trends in publications, author productivity, collaborative networks, and key journals. The study highlights significant growth in the research field, with China and the USA emerging as the most productive countries, with strong international collaboration. Nadeem Javaid is identified as a leading author, contributing to publications with a strong focus on the application of deep learning techniques for energy consumption analysis in smart grids. Key journals such as IEEE Access, Applied Energy, and Energies were found to be central to this research area. Our findings highlighted the importance of this area, as smart grid technologies continue to evolve, requiring advanced methodologies to detect non-technical losses and analyze consumption patterns. This research supports the United Nations’ (UN) Sustainable Development Goals (SDGs), particularly goals related to sustainable energy and infrastructure development, by emphasizing the importance of technological innovation and collaboration in tackling energy theft.

Keywords: scientometric analysis; Web of Science database; Scopus database; Bibliometrix; VOSViewer; electricity theft; energy consumption categorization; household units (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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