Intelligent Sensing for Smart Grid and Smart City. 3 credits, 3 contact hours

Catalog description

This course introduces the fundamentals and applications of intelligent sensing technology to smart grid and smart city. The course covers the fundamental sensing principles, types and selection of sensors including electromagnetic field sensors, amplifiers and bridge circuits, and sensing system architecture. Estimation and evaluation of sensor calibration and their responses by using finite element method, sensor noise and shielding design will be addressed. Signal analysis techniques such as wavelet analysis and sensor fusion will be discussed. Anomaly detection, fault classification and prediction and decision making on sensor data by machine learning, and the applications of electromagnetic sensing in power systems will be covered. Advanced sensor applications topics in IoT, smart grid and smart city will also be included. Prior undergraduate trainings in basic electromagnetics and circuit theories are necessary.