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.


  • 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

section Section I|27 pages

Overview of Modern Wide-Area Monitoring Systems

chapter 1|11 pages


chapter 2|13 pages

Data Mining and Data Fusion Architectures

section Section II|147 pages

Advanced Projection-Based Data Mining and Data Fusion Techniques

chapter 4|29 pages

Spatiotemporal Data Mining

chapter 5|25 pages

Multisensor Data Fusion

chapter 7|25 pages

Forecasting Decision Support Systems

section Section III|69 pages

Challenges and Opportunities in the Application of Data Mining and Data Fusion Techniques