Power system low frequency oscillations monitoring and generator coherency determination in real time

Real time monitoring and control of low frequency oscillations is an important issue to be taken into consideration in modern interconnected power systems operation. A method to find the system small signal stability and coherent generators following a disturbance in real-time is proposed in this work The synchronously sampled data available from Phasor Measurement Units (PMUs) at a high sampling rate provides an opportunity to observe the system operation near to real-time. The first four cycles of post disturbance data comprising of bus voltage magnitudes and angles is measured from optimally placed PMUs. This data is fed to different Artificial Neural Networks to determine the damping index and coherent groups. The dimensionality reduction is performed using Principal Component Analysis. The suggested method is very fast and accurate in predicting the system damping and coherent groups in real-time for different operating conditions including topological variations and 3-phase faults. The efficiency of the proposed methodology is investigated on IEEE 39-bus test system.