Synchrophasor Data Analytics

Sensors are the eyes and ears of power grid. Synchrophasor data from PMUs collected over years has been widely used in wide area monitoring applications and provides an ample set of information regarding underlying grid dynamics. Recently, variety of algorithms have been proposed to understand the dynamical events, identify the characteristics of the PMU data under normal and abnormal scenarios and utilize the data for collecting actionable intelligence online using machine learning and deep learning algorithms and support situational awareness and control center operations. Through this panel, we would discuss major challenges associated with handling growing size of unlabeled PMU data, introduce utility deployed applications trained and tested using historical large PMU database, present recently introduced commercial software tools and discuss potential future applications of PMU data considering large scale integration of renewable energy resources. Presentation in this session: - Regional Inertia Estimation Using PMU Measurements (23PESGM3996) - Unleashing the value of Big Data from Power Systems by means of Data-centric AI (23PESGM3997)