Application of reflectometry in the identification of similar electrical loads: a bibliometric analysis

Authors

  • André Silva Universidade Federal do Espírito Santo
  • Wanderley Cardoso Celeste Universidade Federal do Espírito Santo

DOI:

https://doi.org/10.33448/rsd-v8i2.523

Keywords:

Identification of loads; reflectometry; similar loads; bibliometric analysis.

Abstract

Energy is an essential good for development, and its rational use is necessary to minimize environmental impacts and costs. Load monitoring has a very important role in this context, because it is necessary to know which devices are consuming the electric energy, how much, and at which moment it is consumed. The objective of this article is to perform a bibliometric research for qualitative and quantitative analysis on the identification of loads, especially the highly similar ones, including through of the use of reflectometry in this process. In the analyzes made in this work, it is verified that China is the country with the largest number of publications, followed by the United States. There is also a recent increase in publications on load identification, demonstrating that the topic has gained increasing relevance in the world scenario.

References

ABBOUD, Layane; COZZA, Andrea; PICHON, Lionel. A Matched-Pulse Approach for Soft-Fault Detection in Complex Wire Networks. IEEE Transactions on Instrumentation and Measurement, v. 61, n. 6, p. 1719–1732, jun. 2012. Disponível em: <http://ieeexplore.ieee.org/document/6183514/>. Acesso em: 11 jul. 2018.

ABUBAKAR, I. et al. Application of load monitoring in appliances’ energy management – A review. Renewable and Sustainable Energy Reviews, v. 67, p. 235–245, 1 jan. 2017. Disponível em: <https://www.sciencedirect.com/science/article/pii/S136403211630555X?via%3Dihub>. Acesso em: 11 jul. 2018.

CHANG, Hsueh-Hsien et al. Power-Spectrum-Based Wavelet Transform for Nonintrusive Demand Monitoring and Load Identification. IEEE Transactions on Industry Applications, v. 50, n. 3, p. 2081–2089, maio 2014. Disponível em: <http://ieeexplore.ieee.org/document/6607153/>. Acesso em: 13 jul. 2018.

COMINOLA, A. et al. A Hybrid Signature-based Iterative Disaggregation algorithm for Non-Intrusive Load Monitoring. Applied Energy, v. 185, p. 331–344, 1 jan. 2017. Disponível em: <https://www.sciencedirect.com/science/article/pii/S030626191631488X?via%3Dihub>. Acesso em: 11 jul. 2018.

EGARTER, Dominik; BHUVANA, Venkata Pathuri; ELMENREICH, Wilfried. PALDi: Online Load Disaggregation via Particle Filtering. IEEE Transactions on Instrumentation and Measurement, v. 64, n. 2, p. 467–477, fev. 2015. Disponível em: <http://ieeexplore.ieee.org/document/6881709/>. Acesso em: 11 jul. 2018.

GILLIS, Jessie M.; ALSHAREEF, Sami M.; MORSI, Walid G. Nonintrusive Load Monitoring Using Wavelet Design and Machine Learning. IEEE Transactions on Smart Grid, v. 7, n. 1, p. 320–328, jan. 2016. Disponível em: <http://ieeexplore.ieee.org/document/7110380/>. Acesso em: 11 jul. 2018.

GOLDEMBERG, José. Energia e desenvolvimento. Estudos Avançados, v. 12, n. 33, p. 7–15, ago. 1998. Disponível em: <http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-40141998000200002&lng=pt&tlng=pt>. Acesso em: 13 jul. 2018.

HASSAN, Taha; JAVED, Fahad; ARSHAD, Naveed. An Empirical Investigation of V-I Trajectory Based Load Signatures for Non-Intrusive Load Monitoring. IEEE Transactions on Smart Grid, v. 5, n. 2, p. 870–878, mar. 2014. Disponível em: <http://ieeexplore.ieee.org/document/6575197/>. Acesso em: 11 jul. 2018.

HE, Dawei et al. Front-End Electronic Circuit Topology Analysis for Model-Driven Classification and Monitoring of Appliance Loads in Smart Buildings. IEEE Transactions on Smart Grid, v. 3, n. 4, p. 2286–2293, dez. 2012. Disponível em: <http://ieeexplore.ieee.org/document/6378417/>. Acesso em: 11 jul. 2018.

HE, Kanghang et al. Non-Intrusive Load Disaggregation Using Graph Signal Processing. IEEE Transactions on Smart Grid, v. 9, n. 3, p. 1739–1747, maio 2018. Disponível em: <https://ieeexplore.ieee.org/document/7539273/>. Acesso em: 11 jul. 2018.

JANNUZZI, Gilberto De Martino. AUMENTANDO A EFICIÊNCIA NOS USOS FINAIS DE ENERGIA NO BRASIL. 2002. Disponível em: <https://www.researchgate.net/profile/Gilberto_Jannuzzi/publication/239813211_AUMENTANDO_A_EFICIENCIA_NOS_USOS_FINAIS_DE_ENERGIA_NO_BRASIL/links/02e7e52de3e821174e000000.pdf>. Acesso em: 10 jul. 2018.

KAFAL, Moussa; COZZA, Andrea; PICHON, Lionel. Locating Faults With High Resolution Using Single-Frequency TR-MUSIC Processing. IEEE Transactions on Instrumentation and Measurement, v. 65, n. 10, p. 2342–2348, out. 2016. Disponível em: <http://ieeexplore.ieee.org/document/7495017/>. Acesso em: 11 jul. 2018.

MARDOOKHY, Minoo et al. A study of energy efficiency in residential buildings in Knoxville, Tennessee. Journal of Cleaner Production, v. 85, p. 241–249, 15 dez. 2014. Disponível em: <https://www-sciencedirect.ez120.periodicos.capes.gov.br/science/article/pii/S0959652613006288?via%3Dihub#!>. Acesso em: 9 jul. 2018.

MARIANI PRIMIANI, V. et al. Fault location on shielded cables: Electromagnetic modelling and improved measurement data processing. IEE Proceedings - Science, Measurement and Technology, v. 152, n. 5, p. 217–226, 1 set. 2005. Disponível em: <http://digital-library.theiet.org/content/journals/10.1049/ip-smt_20045035>. Acesso em: 11 jul. 2018.

MOAYEDI, Sam et al. Real Time Power Monitoring Detection Based on Sequence Time Domain Reflectometry Approach. Journal of Computer and Communications, v. 06, n. 01, p. 92–103, 29 dez. 2018. Disponível em: <http://www.scirp.org/journal/doi.aspx?DOI=10.4236/jcc.2018.61010>. Acesso em: 13 jul. 2018.

SHI, Qinghai; KANOUN, Olfa. A New Algorithm for Wire Fault Location Using Time-Domain Reflectometry. IEEE Sensors Journal, v. 14, n. 4, p. 1171–1178, abr. 2014. Disponível em: <http://ieeexplore.ieee.org/document/6678706/>. Acesso em: 11 jul. 2018.

SMITH, P.; FURSE, C.; GUNTHER, J. Analysis of spread spectrum time domain reflectometry for wire fault location. IEEE Sensors Journal, v. 5, n. 6, p. 1469–1478, dez. 2005. Disponível em: <http://ieeexplore.ieee.org/document/1532290/>. Acesso em: 11 jul. 2018.

TABATABAEI, Seyed Mostafa; DICK, Scott; XU, Wilsun. Toward Non-Intrusive Load Monitoring via Multi-Label Classification. IEEE Transactions on Smart Grid, v. 8, n. 1, p. 26–40, jan. 2017. Disponível em: <http://ieeexplore.ieee.org/document/7498597/>. Acesso em: 11 jul. 2018.

TUBALLA, Maria Lorena; ABUNDO, Michael Lochinvar. A review of the development of Smart Grid technologies. Renewable and Sustainable Energy Reviews, v. 59, p. 710–725, 1 jun. 2016. Disponível em: <https://www.sciencedirect.com/science/article/pii/S1364032116000393>. Acesso em: 10 jul. 2018.

ZHANG, Jian Guo et al. Wiring fault detection with Boolean-chaos time-domain reflectometry. Nonlinear Dynamics, v. 80, n. 1–2, p. 553–559, 8 abr. 2015. Disponível em: <http://link.springer.com/10.1007/s11071-014-1888-x>. Acesso em: 11 jul. 2018.

ZHANG, Junmin; ZHANG, Yubo; GUAN, Yonggang. Analysis of Time-Domain Reflectometry Combined With Wavelet Transform for Fault Detection in Aircraft Shielded Cables. IEEE Sensors Journal, v. 16, n. 11, p. 4579–4586, jun. 2016. Disponível em: <http://ieeexplore.ieee.org/document/7442073/>. Acesso em: 11 jul. 2018.

Published

01/01/2019

How to Cite

SILVA, A.; CELESTE, W. C. Application of reflectometry in the identification of similar electrical loads: a bibliometric analysis. Research, Society and Development, [S. l.], v. 8, n. 2, p. e282523, 2019. DOI: 10.33448/rsd-v8i2.523. Disponível em: https://www.rsdjournal.org/index.php/rsd/article/view/523. Acesso em: 18 apr. 2024.

Issue

Section

Review Article