IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i22p9921-d1520768.html
   My bibliography  Save this article

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

Author

Listed:
  • José Antonio Moreira de Rezende

    (Academic Area of Electrical Engineering, Federal Institute of Minas Gerais (IFMG), Formiga 35570-000, MG, Brazil
    Institute of Systems Engineering and Information Technology, Federal University of Itajubá (UNIFEI), Itajubá 37500-903, 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)

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.

Suggested Citation

  • José Antonio Moreira de Rezende & Reginaldo Gonçalves Leão Junior & Otávio de Souza Martins Gomes, 2024. "Scientometric Analysis of Publications on Household Electricity Theft and Energy Consumption Load Profiling in a Smart Grid Context," Sustainability, MDPI, vol. 16(22), pages 1-19, November.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:9921-:d:1520768
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/22/9921/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/22/9921/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zaman Sajid & Asma Javaid, 2018. "A Stochastic Approach to Energy Policy and Management: A Case Study of the Pakistan Energy Crisis," Energies, MDPI, vol. 11(9), pages 1-18, September.
    2. Mingers, John & Leydesdorff, Loet, 2015. "A review of theory and practice in scientometrics," European Journal of Operational Research, Elsevier, vol. 246(1), pages 1-19.
    3. Ghimire, Sujan & Nguyen-Huy, Thong & AL-Musaylh, Mohanad S. & Deo, Ravinesh C. & Casillas-Pérez, David & Salcedo-Sanz, Sancho, 2023. "A novel approach based on integration of convolutional neural networks and echo state network for daily electricity demand prediction," Energy, Elsevier, vol. 275(C).
    4. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    5. Zhang, Xiaohai & Ramírez-Mendiola, José Luis & Li, Mingtao & Guo, Liejin, 2022. "Electricity consumption pattern analysis beyond traditional clustering methods: A novel self-adapting semi-supervised clustering method and application case study," Applied Energy, Elsevier, vol. 308(C).
    6. Mahmoud M. Badr & Mohamed I. Ibrahem & Hisham A. Kholidy & Mostafa M. Fouda & Muhammad Ismail, 2023. "Review of the Data-Driven Methods for Electricity Fraud Detection in Smart Metering Systems," Energies, MDPI, vol. 16(6), pages 1-18, March.
    7. William W. Hood & Concepción S. Wilson, 2001. "The Literature of Bibliometrics, Scientometrics, and Informetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 52(2), pages 291-314, October.
    8. Satre-Meloy, Aven & Diakonova, Marina & Grünewald, Philipp, 2020. "Cluster analysis and prediction of residential peak demand profiles using occupant activity data," Applied Energy, Elsevier, vol. 260(C).
    9. Junwen Zhu & Weishu Liu, 2020. "A tale of two databases: the use of Web of Science and Scopus in academic papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 321-335, April.
    10. Massaoudi, Mohamed & Refaat, Shady S. & Chihi, Ines & Trabelsi, Mohamed & Oueslati, Fakhreddine S. & Abu-Rub, Haitham, 2021. "A novel stacked generalization ensemble-based hybrid LGBM-XGB-MLP model for Short-Term Load Forecasting," Energy, Elsevier, vol. 214(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lutz Bornmann & Robin Haunschild & Sven E. Hug, 2018. "Visualizing the context of citations referencing papers published by Eugene Garfield: a new type of keyword co-occurrence analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 427-437, February.
    2. Juan F. Prados-Castillo & Miguel Ángel Solano-Sánchez & Pilar Guaita Fernández & José Manuel Guaita Martínez, 2023. "Potential of the Crypto Economy in Financial Management and Fundraising for Tourism," Sustainability, MDPI, vol. 15(6), pages 1-15, March.
    3. Ignacio Rodríguez-Rodríguez & José-Víctor Rodríguez & Niloofar Shirvanizadeh & Andrés Ortiz & Domingo-Javier Pardo-Quiles, 2021. "Applications of Artificial Intelligence, Machine Learning, Big Data and the Internet of Things to the COVID-19 Pandemic: A Scientometric Review Using Text Mining," IJERPH, MDPI, vol. 18(16), pages 1-29, August.
    4. Ali Najmi & Taha H. Rashidi & Alireza Abbasi & S. Travis Waller, 2017. "Reviewing the transport domain: an evolutionary bibliometrics and network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 843-865, February.
    5. Yuxue Yang & Xuejiao Tan & Yafei Shi & Jun Deng, 2023. "What are the core concerns of policy analysis? A multidisciplinary investigation based on in-depth bibliometric analysis," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    6. Abidin Kemeç & Ayşenur Tarakcıoglu Altınay, 2023. "Sustainable Energy Research Trend: A Bibliometric Analysis Using VOSviewer, RStudio Bibliometrix, and CiteSpace Software Tools," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    7. Zhigao Liu & Yimei Yin & Weidong Liu & Michael Dunford, 2015. "Visualizing the intellectual structure and evolution of innovation systems research: a bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 135-158, April.
    8. Mohadab, Mohamed El & Bouikhalene, Belaid & Safi, Said, 2020. "Bibliometric method for mapping the state of the art of scientific production in Covid-19," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    9. Dušan Nikolić & Dragan Ivanović & Lidija Ivanović, 2024. "An open-source tool for merging data from multiple citation databases," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(7), pages 4573-4595, July.
    10. Margarida Rodrigues & Cidália Oliveira & MárioFranco & Ana Daniel, 2024. "A Bibliometric Study About the Rural Creative Class: Proposal of a Conceptual Framework and Future Agenda," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 15278-15303, September.
    11. Md. Nazmus Sakib & Shah Ridwan Chowdhury & Mohammad Younus & Nehad Laila Sanju & Farhana Foysal Satata & Mahafuza Islam, 2024. "How HR analytics evolved over time: a bibliometric analysis on Scopus database," Future Business Journal, Springer, vol. 10(1), pages 1-22, December.
    12. Magdalena Mucowska, 2021. "Trends of Environmentally Sustainable Solutions of Urban Last-Mile Deliveries on the E-Commerce Market—A Literature Review," Sustainability, MDPI, vol. 13(11), pages 1-26, May.
    13. Rita Rodríguez‐Arrojo & Manuel Luna & Camilo J. Vázquez‐Ordás & Myriam García‐Olalla, 2024. "Mapping research on corporate misconduct in banking: Lessons from literature on preventive and punitive actions," Global Policy, London School of Economics and Political Science, vol. 15(S1), pages 62-75, March.
    14. Andrzej Lis & Agata Sudolska & Mateusz Tomanek, 2020. "Mapping Research on Sustainable Supply-Chain Management," Sustainability, MDPI, vol. 12(10), pages 1-26, May.
    15. Md Abu Helal & Nathaniel Anderson & Yu Wei & Matthew Thompson, 2023. "A Review of Biomass-to-Bioenergy Supply Chain Research Using Bibliometric Analysis and Visualization," Energies, MDPI, vol. 16(3), pages 1-32, January.
    16. Caputo, Andrea & Pizzi, Simone & Pellegrini, Massimiliano M. & Dabić, Marina, 2021. "Digitalization and business models: Where are we going? A science map of the field," Journal of Business Research, Elsevier, vol. 123(C), pages 489-501.
    17. Jie Xue & Genserik Reniers & Jie Li & Ming Yang & Chaozhong Wu & P.H.A.J.M. van Gelder, 2021. "A Bibliometric and Visualized Overview for the Evolution of Process Safety and Environmental Protection," IJERPH, MDPI, vol. 18(11), pages 1-29, June.
    18. Batista-Canino, Rosa M. & Santana-Hernández, Lidia & Medina-Brito, Pino, 2024. "A holistic literature review on entrepreneurial Intention: A scientometric approach," Journal of Business Research, Elsevier, vol. 174(C).
    19. Huixin Wang & Jing Xie & Shixian Luo & Duy Thong Ta & Qian Wang & Jiao Zhang & Daer Su & Katsunori Furuya, 2023. "Exploring the Interplay between Landscape Planning and Human Well-Being: A Scientometric Review," Land, MDPI, vol. 12(7), pages 1-24, June.
    20. Eugenio Petrovich & Sander Verhaegh & Gregor Bös & Claudia Cristalli & Fons Dewulf & Ties Gemert & Nina IJdens, 2024. "Bibliometrics beyond citations: introducing mention extraction and analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(9), pages 5731-5768, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:9921-:d:1520768. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.