Abstract
Power system monitoring and control in real-time is a challenging task for modern power system due to large number of operational constraints involved. This paper proposes a method to find the real-time transient stability state and identification of the coherent generator groups by predicting the rotor angle values following a large disturbance through radial basis function neural network. The first six cycle data of rotor angles and voltages of generators from fault clearing obtained through synchrophasor measurements are taken as the input to the neural network. The proposed method is also able to determine synchronism state of the individual machine in real-time. The proposed scheme is investigated on IEEE-39 bus test system to show the effectiveness of the proposed scheme.
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