SYNCHROPHASOR DATA BASED INTELLIGENT ALGORITHM FOR REAL TIME EVENT DETECTION IN POWER SYSTEM

The wide area measurement system (WAMS) has been installed at several locations in power system. Phasor measurements units (PMU) are considered as the building blocks of WAMS are being installed at various locations of power system. PMU is sending very large volume of data to Power system control center with the sampling rate of 50 or 25 samples per second. However there are always several events per day occurring in the system but the rate at which data is received and the volume of data to be analyzed is a big challenge for power system engineer. There is a need for developing an intelligent system to handle large volume of Synchrophasor data and identify Power system event in the present context. This paper presents an intelligent algorithm to automatically detect such events using wide area measurements in real time. In this work, Synchrophasor measurements received from PMU are fed to KNN based pattern recognition algorithm which is used to identify the Power system events. The severity and the type of the event can be judged through the change in voltage magnitude and phase angle at various buses. The developed algorithm is tested for IEEE 14 bus system and results are verified.