Monitoring of Voltage Stability Margin by Artificial Neural Network

In this paper, based on artificial neural network (ANN) a method is provided to estimate the long-term voltage stability margin. Reviews in this paper show that the amplitude of voltage nodes and phase angles are the best predictors for voltage stability margin. In addition, the paper shows that the proposed neural network-based methods successfully are able to estimate voltage stability margin in normal mode. If the voltage amplitude and phase angle in real time is obtained from phasor measurement units (PMU), in this case, using the proposed method, voltage stability margin can be estimated in real time and can be used to start actions related to stability control. Numerical examples of the proposed method are presented using IEEE 9-bus test systems.