This book provides a compact yet comprehensive treatment of advanced
data-driven signal processing techniques for the analysis and
characterization of both ambient power system data and transient
oscillations resulting from major disturbances. Inspired by recent
developments in multi-sensor data fusion, multi-temporal data
assimilation techniques for power system monitoring are proposed and
tested in the context of modern wide-area monitoring system
architectures. Recent advances in understanding and modeling nonlinear,
time-varying power system processes are reviewed and factors affecting
the performance these techniques are discussed.
A number of algorithms and examples are presented throughout the text as
an aid to understanding the basic material provided. Challenges involved
in realistic monitoring, visualization and analysis of actual
disturbance events are emphasized and examples of applications to a wide
range of power networks are provided. Topics covered include: wide-area
monitoring and analysis systems; wide-area monitoring system
architectures; spatio-temporal modeling of power system dynamic
processes; advanced data processing and feature extraction; multi-sensor
multitemporal data fusion; monitoring the status of the system; near
real-time analysis and monitoring; and interpretation and visualization
of wide-area PMU measurements.
This book will be of interest to students, researchers and engineers
involved in the study, design, analysis and control of power systems.
