Extraction of dynamic patterns from wide-area measurements using empirical orthogonal functions

An approach based on the empirical mode decomposition (EMD) technique and proper orthogonal decomposition is proposed to examine dynamic trends and phase relationships between key system signals from measured data. Drawing on the EMD approach, and the method of snapshots, a technique based on the notion of proper orthogonal modes, is used to express an ensemble of measured data as a linear combination of basis functions or modes. This approach improves the ability of the EMD technique to capture abrupt changes in the observed data. Analytical criteria to describe the energy relationships in the observed oscillations are derived and a physical interpretation of the system modes is suggested. It is shown that in addition to providing estimates of time dependent mode shapes, the analysis also provides a method to identify the modes with the most energy embedded in the underlying signals. The method is applied to conduct post-mortem analysis of measured data of a real event in northern Mexico and to transient stability data.