Identificaiton Method About Abnormal Synchronization of WAMS Data

The Wide-Area Measurement System (WAMS) demonstrates significant advantages in power grid monitoring through its high data acquisition density, excellent synchronization performance, and inclusion of phase-angle information. These features effectively support power grid security and stable operation. However, limitations in WAMS data quality have hindered its engineering applications. Current research focuses on data value anomalies and lacks effective methods for identifying time-synchronization errors. This paper proposes a time-stamp anomaly identification method for WAMS data based on disturbance occurrence time detection. By analyzing post-disturbance measurements from Phasor Measurement Units (PMUs), including frequency change rates, active power variations, and frequency deviations, the method identifies disturbance onset moments. Temporal inconsistencies in disturbance occurrence times across wide-area PMU measurements enable the detection of time-stamp anomalies at specific plants and substations. Validation through actual grid disturbance cases confirms the method's effectiveness. This approach provides a valuable reference for addressing time-synchronization anomalies in WAMS data, enhancing the reliability of WAMS for power system monitoring applications