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|Title:||Synchrophasor-Based online coherency identification in voltage stability assessment||Authors:||Adewole, Adeyemi Charles
|Keywords:||Clustering method;machine learning;phasor measurement unit;power system stability;voltage stability||Issue Date:||2015||Publisher:||Ștefan cel Mare University of Suceava||Source:||Adewole, A.C. & Tzoneva, R. 2015. Synchrophasor-Based online coherency identification in voltage stability assessment. Advances in Electrical and Computer Engineering, 15(4): 33-42. [http://doi.org/10.4316/AECE.2015.04005]||Journal:||Advances in Electrical and Computer Engineering||Abstract:||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-inthe-loop configuration with the Real-Time Digital Simulator (RTDS) and Phasor Measurement Units (PMUs).||URI:||http://hdl.handle.net/11189/7788||ISSN:||1582-7445||DOI:||http://doi.org/10.4316/AECE.2015.04005|
|Appears in Collections:||Eng - Journal articles (DHET subsidised)|
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