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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  4/2015 - 5


Synchrophasor-Based Online Coherency Identification in Voltage Stability Assessment

ADEWOLE, A. C. See more information about ADEWOLE, A. C. on SCOPUS See more information about ADEWOLE, A. C. on IEEExplore See more information about ADEWOLE, A. C. on Web of Science, TZONEVA, R. See more information about TZONEVA, R. on SCOPUS See more information about TZONEVA, R. on SCOPUS See more information about TZONEVA, R. on Web of Science
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,528 KB) | Citation | Downloads: 490 | Views: 2,333

Author keywords
clustering method, machine learning, phasor measurement unit, power system stability, voltage stability

References keywords
power(45), systems(20), system(17), voltage(13), stability(13), tpwrs(11), reactive(9), dynamic(8), analysis(7), real(6)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2015-11-30
Volume 15, Issue 4, Year 2015, On page(s): 33 - 42
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2015.04005
Web of Science Accession Number: 000368499800005
SCOPUS ID: 84949981200

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This paper presents and investigates a new measurement-based approach in the identification of coherent groups in load buses and synchronous generators for voltage stability assessment application in large interconnected power systems. A hybrid Calinski-Harabasz criterion and k-means clustering algorithm is developed for the determination of the cluster groups in the system. The proposed method is successfully validated by using the New England 39-bus test system. Also, the performance of the voltage stability assessment algorithm using wide area synchrophasor measurements from the key synchronous generator in each respective cluster was tested online for the prediction of the system's margin to voltage collapse using a testbed comprising of a Programmable Logic Controller (PLC) in a hardware-in-the-loop configuration with the Real-Time Digital Simulator (RTDS) and Phasor Measurement Units (PMUs).

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Cited-By ISI Web of Science

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Cited-By CrossRef

SCOPUS® Times Cited: 8
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Cited-By CrossRef

[1] A Phasor Estimation Algorithm based on Hilbert Transform for P-class PMUs, RAZO-HERNANDEZ, J. R., VALTIERRA-RODRIGUEZ, M., GRANADOS-LIEBERMAN, D., TAPIA-TINOCO, G., RODRIGUEZ-RODRIGUEZ, J. R., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 3, Volume 18, 2018.
Digital Object Identifier: 10.4316/AECE.2018.03013
[CrossRef] [Full text]

[2] Adaptive under-voltage load shedding scheme for large interconnected smart grids based on wide area synchrophasor measurements, Tzoneva, Raynitchka, Adewole, Adeyemi Charles, Apostolov, Alexander, IET Generation, Transmission & Distribution, ISSN 1751-8687, Issue 8, Volume 10, 2016.
Digital Object Identifier: 10.1049/iet-gtd.2015.1250

[3] Extended synchrophasor-based online voltage stability assessment using synchronous generator-derived indices, Adewole, Adeyemi Charles, Tzoneva, Raynitchka, International Transactions on Electrical Energy Systems, ISSN 2050-7038, Issue 1, Volume 27, 2017.
Digital Object Identifier: 10.1002/etep.2236

[4] Surrogate-splits ensembles for real-time voltage stability assessment in the presence of missing synchrophasor measurements, Adewole, Adeyemi Charles, Tzoneva, Raynitchka, IET Science, Measurement & Technology, ISSN 1751-8822, Issue 5, Volume 11, 2017.
Digital Object Identifier: 10.1049/iet-smt.2016.0431

[5] A Novel Method of Coherency Identification for Multi-Machine Power System, Rahman, Shaikh Rashedur, Ullah, Md. Shahid, 2019 IEEE 6th International Conference on Engineering Technologies and Applied Sciences (ICETAS), ISBN 978-1-7281-4082-7, 2019.
Digital Object Identifier: 10.1109/ICETAS48360.2019.9117540

[6] A Machine Learning Approach to the Identification of Voltage Control Area Using Synchrophasor Measurements, Kibriya, Fazle, Mahto, Dinesh Kumar, Mohanta, Dusmanta Kumar, 2019 20th International Conference on Intelligent System Application to Power Systems (ISAP), ISBN 978-1-7281-3192-4, 2019.
Digital Object Identifier: 10.1109/ISAP48318.2019.9065931

[7] Physically Meaningful Grid Analytics on Voltage Measurements using Graph Spectra, Bariya, Mohini, Moffat, Keith, Von Meier, Alexandra, 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), ISBN 978-1-7281-3103-0, 2020.
Digital Object Identifier: 10.1109/ISGT45199.2020.9087671

[8] Voltage stability assessment using synchrophasor measurements: Trends and development, Pinzon, Jaime D., Colome, Delia G., 2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America), ISBN 978-1-5386-3312-0, 2017.
Digital Object Identifier: 10.1109/ISGT-LA.2017.8126724

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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania

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