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
Link To Document :
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