Big Data Application in Power Systems

<p>SECTION 1 Harness the Big Data From Power Systems<br>1. A Holistic Approach to Becoming a Data-Driven Utility<br>2. Emerging Security and Data Privacy Challenges for Utilities: Case Studies and Solutions<br>3. The Role of Big Data and Analytics in Utility Innovation<br>4. Frameworks for Big Data Integration, Warehousing, and Analytics </p> <p>SECTION 2 Harness the Power of Big data<br>5. Moving Toward Agile Machine Learning for Data Analytics in Power Systems<br>6. Unsupervised Learning Methods for Power System Data Analysis<br>7. Deep Learning for Power System Data Analysis<br>8. Compressive Sensing for Power System Data Analysis <br>9. Time-Series Classification Methods: Review and Applications to Power Systems Data</p> <p>SECTION 3 Put the Power of Big Data into Power Systems<br>10. Future Trends for Big Data Application in Power Systems<br>11. On Data-Driven Approaches for Demand Response<br>12. Topology Learning in Radial Distribution Grids<br>13. Grid Topology Identification via Distributed Statistical Hypothesis Testing<br>14. Supervised Learning-Based Fault Location in Power Grids<br>15. Data-Driven Voltage Unbalance Analysis in Power Distribution Networks<br>16. Predictive Analytics for Comprehensive Energy Systems State Estimation<br>17. Data Analytics for Energy Disaggregation: Methods and Applications<br>18. Energy Disaggregation and the Utility-Privacy Tradeoff</p>