DocumentCode
3246201
Title
MOSELM approach for Voltage Stability Indicator using phasor measurement units
Author
Abidin, I.Z. ; Keem Siah Yap ; Saadun, Nira ; Abdullah, Sheikh Kamar Sheikh ; Mohd Sarmin, M.K.N.
Author_Institution
Univ. Tenaga Nasional (UNITEN), Kajang, Malaysia
fYear
2012
fDate
2-5 Dec. 2012
Firstpage
510
Lastpage
514
Abstract
Voltage stability assessment is important in order to ensure a stable power system. Two algorithms were discussed in this paper which looks into estimating voltage stability based upon Thevenin Equivalent values in a system using Voltage and Current Phasors for different loading values. The first algorithm uses a Kalman filter based formulation. The second method uses an Online Learning approach known as the Modified Online Sequence Extreme Learning Machine (MOSELM). Results show that the Kalman Filter approach is capable of analyzing voltage stability but it requires some user specified information for tuning. On the other hand, the MOSELM approach show that it is capable of producing the same result as the Kalman Filter approach but require less amount of user specified information.
Keywords
Kalman filters; learning (artificial intelligence); phasor measurement; power engineering computing; power system stability; Kalman filter; MOSELM approach; Thevenin equivalent values; current phasors; modified online sequence extreme learning machine; online learning approach; phasor measurement units; power system; voltage phasors; voltage stability assessment; voltage stability indicator; Kalman filters; Learning systems; Power system stability; Reactive power; Stability analysis; Voltage measurement; Artificial Intelligence; Kalman Filter; Online Sequential Extreme Learning Machine; Phasor Measurement Units; Voltage Stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy (PECon), 2012 IEEE International Conference on
Conference_Location
Kota Kinabalu
Print_ISBN
978-1-4673-5017-4
Type
conf
DOI
10.1109/PECon.2012.6450267
Filename
6450267
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