Wide Area Monitoring of Interconnected Power Systems

This expanded and updated second edition covers advanced data-driven signal processing techniques for the analysis of power system data and transient oscillations in power grids. New content includes new architectures for smart grids and microgrids, multitemporal data fusion, deep learning, multichannel phasor measurement.

Power systems are becoming increasingly complex, handling rising shares of distributed intermittent renewable generation, EV charging stations, and storage. To ensure power availability and quality, the grid needs to be monitored as a whole, by wide area monitoring (WAM), not just in small sections separately. Parameter oscillations need to be detected and acted upon. This requires sensors, data assimilation and visualization, comparison with models, modelling, and system architectures for different grid types.

This hands-on reference for researchers in power systems, professionals at grid operators and grid equipment manufacturers, as well as for advanced students, offers a comprehensive treatment of advanced data-driven signal processing techniques for the analysis and characterization of system data and transient oscillations in power grids. Algorithms and examples help readers understand the material. Challenges involved in realistic monitoring, visualization, and analysis of actual disturbance events are emphasized.

Chapters in this second edition cover WAM and analysis systems, WAM system architectures, modelling of power system dynamic processes, data processing and feature extraction, multi-sensor multitemporal data fusion, WAM of power systems with high penetration of distributed generation, distributed wide-area oscillation monitoring, near real-time analysis and monitoring, and interpretation and visualization of wide-area PMU measurements.

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