Phasor Measurement Sensor-Assisted Time-to-Collapse Estimation Under Long-Term Voltage Instability of Smart Grids

The synchrophasor measurement sensors are the state-of-the-art measuring devices available in the modern smart grids (SGs), which are capable of providing fast and accurate phasor measurements in the system. This phasor information has been exploited in this article to develop a model-free technique to accurately assess the long-term voltage stability (VS) of the system. The proposal first makes the system observable with minimum number of sensors, and the phasor measurements obtained from these optimal number of sensors are then used in the regression theorem of the Ornstein–Uhlenbeck process to assemble a scaled Jacobian in real-time. After carrying out the modal analysis on the measurement-based Jacobian, two novel stability indices are proposed. The performance of the proposed technique is tested on the benchmark IEEE 14-bus and the New England 39-bus system under various scenarios such as dynamic load increase under base conditions, critical line outage, and critical generator outage. The efficacy of the proposed method is also accredited by its real-time implementation using real time digital simulator (RTDS). The results demonstrate that the proposed method achieves an accurate and an early prediction of the emanating system collapse conditions while exploiting information from the minimum number of sensors in the field.