Power systems are increasingly complex, integrating growing shares of distributed intermittent renewable generation, EV charging infrastructure, and energy storage. To maintain power quality and availability, grids must be monitored holistically through wide-area monitoring (WAM), rather than in isolated sections. Detecting and responding to parameter oscillations requires advanced sensors, data assimilation and visualization, model comparison, system modeling, and architectures suited to different grid types.
This hands-on reference is designed for researchers, grid operators, equipment manufacturers, and advanced students. It provides a comprehensive overview of data-driven signal processing techniques for analyzing and characterizing system data and transient oscillations in power grids. Algorithms and practical examples are included to aid understanding, with emphasis on the challenges of monitoring, visualization, and analysis of real disturbance events.
The second edition covers WAM systems and architectures, modeling of dynamic processes, data processing and feature extraction, multi-sensor and multi-temporal data fusion, monitoring of grids with high distributed generation penetration, distributed wide-area oscillation monitoring, near real-time analysis, and interpretation and visualization of wide-area PMU measurements.
