Data Fusion and Data Mining for Power System Monitoring

Arturo Roman (The Center for Research and Advanced Studies of the National Polytechnic Institute of Mexico Messina

ISBN 10: 0367333678 / ISBN 13: 9780367333676

Editore: Taylor & Francis Ltd Mai 2020, 2020

Neuware - Data Fusion and Data Mining for Power System Monitoring provides a comprehensive treatment of advanced data fusion and data mining techniques for power system monitoring with focus on use of synchronized phasor networks. Relevant statistical data mining techniques are given, and efficient methods to cluster and visualize data collected from multiple sensors are discussed. Both linear and nonlinear data-driven mining and fusion techniques are reviewed, with emphasis on the analysis and visualization of massive distributed data sets. Challenges involved in realistic monitoring, visualization, and analysis of observation data from actual events are also emphasized, supported by examples of relevant applications. Codice articolo 9780367333676

Riassunto:

Data Fusion and Data Mining for Power System Monitoring provides a comprehensive treatment of advanced data fusion and data mining techniques for power system monitoring with focus on use of synchronized phasor networks. Relevant statistical data mining techniques are given, and efficient methods to cluster and visualize data collected from multiple sensors are discussed. Both linear and nonlinear data-driven mining and fusion techniques are reviewed, with emphasis on the analysis and visualization of massive distributed data sets. Challenges involved in realistic monitoring, visualization, and analysis of observation data from actual events are also emphasized, supported by examples of relevant applications.

Features

• Focuses on systematic illustration of data mining and fusion in power systems Covers issues of standards used in the power industry for data mining and data analytics
• Applications to a wide range of power networks are provided including distribution and transmission networks
• Provides holistic approach to the problem of data mining and data fusion using cutting-edge methodologies and technologies
• Includes applications to massive spatiotemporal data from simulations and actual events

Informazioni sull?autore:

Arturo Messina earned his PhD from Imperial College, London, UK, in 1991. Since 1997, he has been a professor in the Center for Research and Advanced Studies, Guadalajara, Mexico. He is on the editorial and advisory boards of Electric Power Systems Research, and Electric Power Components and Systems. From 2011 to 2018 he was Editor of the IEEE Trans. on Power Systems and Chair of the Power System Stability Control Subcommittee of the Power Systems Dynamic Committee of IEEE (2015-2018). A Fellow of the IEEE, he is the editor of Inter-Area Oscillations in Power Systems – A Nonlinear and Non-stationary Perspective (Springer, 2009) and the author of Robust Stability and Performance Analysis of Large-Scale Power Systems with Parametric Uncertainty: A Structured Singular Value Approach (Nova Science Publishers, 2009), and Wide-Area Monitoring of Interconnected Power Systems (IET, 2015).

Dati bibliografici

Titolo: Data Fusion and Data Mining for Power System...
Casa editrice: Taylor & Francis Ltd Mai 2020
Data di pubblicazione: 2020
Legatura: Buch
Condizione: Neu