Rensselaer Polytechnic Institute, Electrical, Computer, and Systems Engineering
With the increasing complexity of power systems, the need for control equipment monitoring and performance evaluation becomes important. This presentation describes a signal-processing algorithm for utilizing synchrophasor measurement data to examine the reactive-power versus voltage regulation and the active-power versus frequency regulation for control equipment such as generators and static compensators (STATCOMs). The method is designed for both ambient and disturbance phasor data. Disturbance data are those measured during upsets such as generator, load and line trips. Ambient data are those captured during normal system operation, in which the power system is constantly adapting to new load condition and generation dispatch. To isolate the control system response amidst system operation condition changes, an empirical modal decomposition (EMD) is performed to extract the quasi-steady state. Intrinsic modal functions are used to further characterize the control response. This signal processing technique also includes some additional filtering requirements. The algorithm is demonstrated on synchrophasor data obtained from the interconnection point of a STATCOM during ambient and disturbance operation. It is also illustrated with synchrophasor data obtained from a hydraulic generator.
Joe Chow obtained his MS and PhD degrees in Electrical Engineering from the University of Illinois, Urbana-Champaign. He worked in the General Electric power system business before joining Rensselaer Polytechnic Institute in 1987, where he is Institute Professor, Electrical, Computer, and Systems Engineering. He is currently the campus director of the NSF/DOE Engineering Research Center on Ultra-Wide-Area Resilient Electric Energy Transmission Networks (CURENT). His research interests include modeling and control of power systems, control of renewable resources, and synchrophasor data analysis. He is a life fellow of IEEE and a member of the US National Academy of Engineering. He is a recipient of the Donald Eckman award from the American Automatic Control Council, the Control Systems Technology Award from the IEEE Control Systems Society, and the Charles Concordia Power System Engineering Award from the IEEE Power and Energy
