Fault Analysis and Recovery in Power Grids Using Synchro-Phasor Technology and Phasor Measurement Units

This research proposes a comprehensive synchrophasor-based fault analysis framework for power grids, aimed at enhancing fault detection, localization, and system recovery. The framework models a real-world power network using Simulink, incorporating essential components such as buses, generators, three-phase transmission lines, and load systems. Phasor Measurement Units (PMUs) are strategically deployed across the network to provide synchronized measurements of voltage and current phasors, including magnitude, phase angle, and frequency, referenced to a common GPS-based time signal. This setup enables precise monitoring and analysis of system behavior under steady-state and fault conditions. The study examines two fault scenarios: single-line-to-ground (SLG) and three-phase faults, introduced at Bus B4. The results reveal significant deviations in system parameters during fault conditions, including voltage collapse, current surges, phase angle shifts, and frequency disturbances. Single-line-to-ground faults exhibited faster recovery times for voltage (0.8 s), frequency (0.6 s), and phase angle (0.7 s) compared to three-phase faults, where recovery times extended to 2.5 s, 2.8 s, and 3.0 s, respectively. The rate of change of phase angle (ROCOA) was identified as a key indicator for fault detection and localization, with PMUs capturing sharp ROCOA spikes at the fault location. The proposed framework successfully validates the effectiveness of PMU-based synchro-phasor technology in detecting and localizing faults in real time. The analysis highlights the differences in system response between single-line-to-ground and three-phase faults, demonstrating the severity of the latter. The findings underscore the need for rapid recovery strategies, especially for severe faults, to ensure system stability and reliability. This framework contributes to the development of Wide Area Monitoring Systems (WAMS) for modern smart grids, offering enhanced situational awareness, faster fault response, and improved system resilience.