Traditionally, disturbance detection relies on customer calls to the utility and through the SCADA (Supervisory Control and Data Acquisition) system. A major disadvantage of SCADA is that the measurements are not synchronized, which means that the fault detection process is not precise or timely. Furthermore, due to an inherently low scanning rate, the SCADA system is incapable of providing sufficient information about the dynamic state of the power system. In other words, the SCADA method may not be able to provide immediate event detection at the onset of an unstable event. With the ever increasing deployment of Phasor Measurement Units (PMU’s) in the power system, the dynamic has shifted towards situational awareness through wide area monitoring systems using synchronous measurement data generated by a network of PMU’s. While the main objective of PMU deployment is to improve monitoring and dynamic control of the power grid, a new opportunity has recently emerged in utilizing the PMU measurement data for power quality assessment that can identify the source of instability. Since voltage instability is a local phenomenon, the main objective of this project is to locate the proximity of the problem.
Here PMU’s have been considered for detecting disturbances and degradation in the grid. Considering that the source of instability mainly impacts neighboring areas, we have designed a simple and yet efficient algorithm that can identify affected areas. We embedded our real-time Virtual PMU (VPU) design into our software in the loop testbed to verify the performance of the proposed schemes. For the IEEE 39-bus transmission system, it is shown that the proposed space-time synchrophasor data classification scheme is capable of detecting and isolating area of grid instabilities.