MOSELM approach for Voltage Stability Indicator using phasor measurement units

• Main Authors: Abidin I.Z., Yap K.S., Saadun N., Abdullah S.K.S., Mohd Sarmin M.K.N.
• Other Authors: 35606640500
• Format: Conference paper
• Published: 2023
• Subjects: Artificial Intelligence; Kalman Filter; Online Sequential Extreme Learning Machine; Phasor Measurement Units; Voltage Stability; Algorithms; Artificial intelligence; Electric power system interconnection; Kalman filters; Knowledge acquisition; Learning systems; Loading; Phasor measurement units; Voltage control; Current phasors; Extreme learning machine; Filter approach; Loading values; Online learning; Online sequential extreme learning machine; Thevenin equivalent; Voltage stability assessment; Voltage stability indicators; Voltage stabilizing circuits

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. � 2012 IEEE.