Wide Area Monitoring of Interconnected Power Systems

Arturo Román Messina

ISBN 10: 1849198535 / ISBN 13: 9781849198530

Published by Institution Of Engineering & Technology Mai 2015, 2015

About this Item

Neuware - 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.

Seller Inventory # 9781849198530

Bibliographic Details

• Title: Wide Area Monitoring of Interconnected Power Systems
• Publisher: Institution Of Engineering & Technology Mai 2015
• Publication Date: 2015
• Language: English
• ISBN 10: 1849198535
• ISBN 13: 9781849198530
• Binding: Buch
• Condition: Neu
• Dimensions: 240W x 161H x 18D millimeters 240 millimeters width by 161 millimeters height by 18 millimeters depth
• Weight: 548 grams

About this title

Synopsis

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.

About the Author

Professor Messina is on the editorial and advisory boards of Electric Power Systems Research, IEEE Trans on Power Systems, and Electric Power Components and Systems. A Fellow of the IEEE, he is the editor of Advanced Wide-Area Angle Stability and Voltage Control (2011, Nova Science Publishers, Inc) and Interarea Oscillations in Power Systems: A Nonlinear and Nonstationary Perspective (Springer, 2009).