PMU based disturbance analysis and fault localization of a large grid using wavelets and list processing

摘要

The present system used for the monitoring and control of grid is the Supervisory Control and Data Acquisition System (SCADA). It has been observed that dynamic visualization of power system cannot be achieved effectively by the use of the SCADA system because of the low sampling rate. But, paradigm shift in grid monitoring, online fault detection and offline post disturbance analysis can be achieved with the introduction of synchrophasor technology alternatively known as PMU. When the PMU is deployed in the grid, the grid dynamics can be monitored at sub-second level from the control centers. Power system faults is easily diagnosed by identifying the changes in PMU data using Wavelet based signal processing techniques. A new software tool has been developed to detect the PMU signal variations and to classify the disturbances based on the signatures associated with each disturbance. This information has been correlated with the Sequence of Event (SoE) message of SCADA to exactly locate the point of origin of the fault and time. This system provides a total solution for the analysis of power system disturbances.