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Synchrophasor-Based Online Coherency Identification in Voltage Stability AssessmentADEWOLE, A. C. , TZONEVA, R.
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clustering method, machine learning, phasor measurement unit, power system stability, voltage stability
power(45), systems(20), system(17), voltage(13), stability(13), tpwrs(11), reactive(9), dynamic(8), analysis(7), real(6)
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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
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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 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.
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Stefan cel Mare University of Suceava, Romania
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