Detection of inconspicuous power quality disturbances through step changes in rms voltage profile-Reference-Cited by-同舟云学术

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Detection of inconspicuous power quality disturbances through step changes in rms voltage profile

Published:2019-04-23 Issue:11 Volume:13 Page:2226-2235
ISSN:1751-8695
Container-title:IET Generation, Transmission & Distribution
language:en
Short-container-title:IET Generation, Transmission & Distribution

Author:

Furlani Bastos Alvaro¹²^ORCID,Freitas Walmir³,Todeschini Grazia⁴^ORCID,Santoso Surya¹

Affiliation:

1. Department of Electrical and Computer EngineeringThe University of Texas at AustinAustinTX78712USA

2. CAPES Foundation within the Ministry of EducationBrasilia70040–031Brazil

3. Department of Electrical Energy SystemsUniversity of Campinas13083–852CampinasSPBrazil

4. College of EngineeringSwansea UniversitySwanseaSA1 8ENUK

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-gtd.2018.6511

Reference50 articles.

1. Gapless Power-Quality Disturbance Recorder

2. A generic waveform abnormality detection method for utility equipment condition monitoring;Li B.;IEEE Trans. Power Deliv.,2017

3. Techniques and methodologies for power quality analysis and disturbances classification in power systems: a review;Lieberman D.G.;IET Gener. Transm. Distrib.,2011

4. Nationwide real-time monitoring system for electrical quantities and power quality of the electricity transmission system

5. Broshi A.:‘Monitoring power quality beyond EN 50160 and IEC 61000–4‐30’.Proc. IEEE Power Engineering Society Conf. and Exposition in Africa – PowerAfrica Johannesburg South Africa 2007 pp.1–7

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1. Dynamic Power Quality Disturbance Classification in Grid-Integrated PV Systems: Leveraging Clark Transformed Modal Voltage and Subspace Weighted KNN;IEEE Access;2024

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3. Optimization Techniques for Mining Power Quality Data and Processing Unbalanced Datasets in Machine Learning Applications;Energies;2021-01-16

4. IoT embedded cloud-based intelligent power quality monitoring system for industrial drive application;Future Generation Computer Systems;2020-11

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