Big Data Application in Power Systems

Big Data Application in Power Systems brings together experts from academia, industry and regulatory agencies who share their understanding and discuss the big data analytics applications for power systems diagnostics, operation and control. Recent developments in monitoring systems and sensor networks dramatically increase the variety, volume and velocity of measurement data in electricity transmission and distribution level. The book focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data. The book chapters discuss challenges, opportunities, success stories and pathways for utilizing big data value in smart grids.

• Provides expert analysis of the latest developments by global authorities
• Contains detailed references for further reading and extended research
• Provides additional cross-disciplinary lessons learned from broad disciplines such as statistics, computer science and bioinformatics
• Focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data

Engineers, scientists, future electric grid professionals, researchers, graduate students, lecturers in electricity network and smart grid, data analysis experts, developers in electricity networks and advanced technologies for smart grids

SECTION 1 Harness the Big Data From Power Systems
1. A Holistic Approach to Becoming a Data-Driven Utility
John D. McDonald, GE Energy Connections-Grid Solutions, Atlanta, GA, United States
2. Emerging Security and Data Privacy Challenges for Utilities: Case Studies and Solutions
Carol L. Stimmel, Manifest Mind, LLC, Canaan, NY, United States
3. The Role of Big Data and Analytics in Utility Innovation
Jeffrey S. Katz, IBM, Hartford, CT, United States
4. Frameworks for Big Data Integration, Warehousing, and Analytics 
Feng Gao, Tsinghua University Energy Internet Research Institute, Beijing, China

SECTION 2 Harness the Power of Big data
5. Moving Toward Agile Machine Learning for Data Analytics in Power Systems
Yuxun Zhou, and Reza Arghandeh, UC Berkeley and Florida State University, Tallahassee, FL, United States
6. Unsupervised Learning Methods for Power System Data Analysis
Thierry Zufferey, Andreas Ulbig†, Stephan Koch†, Gabriela Hug
 ETH Zurich, Power Systems Laboratory, Zurich, Switzerland, Adaptricity AG, c/o ETH Zurich, Power Systems Laboratory, Zurich, Switzerland
7. Deep Learning for Power System Data Analysis
 Elena Mocanu, Phuong H. Nguyen, Madeleine Gibescu, Eindhoven University of Technology, Eindhoven, The Netherlands
8. Compressive Sensing for Power System Data Analysis 
Mohammad Babakmehr, Mehrdad Majidi†, Marcelo G. Simoes
Colorado School of Mines, Golden, CO, United States
University of Nevada, Reno, NV, United States
9. Time-Series Classification Methods: Review and Applications to Power Systems Data
Gian Antonio Susto, Angelo Cenedese, Matteo Terzi, University of Padova, Padova, Italy

SECTION 3 Put the Power of Big Data into Power Systems
10. Future Trends for Big Data Application in Power Systems
Ric