Big Data Application in Power Systems

<p>Section One: Harness the Big data from Power Systems<br>1. A Holistic Approach to Becoming a Data-driven Utility<br>2. Security and Data Privacy Challenges for Data-driven Utilities<br>3. The Role of Big Data and Analytics in Utilities Innovation<br>4. Big Data integration for the digitalisation and decarbonisation of distribution grids<br><br>Section Two: Put the Power of Big data into Power Systems<br>5. Topology Detection in Distribution Networks with Machine Learning<br>6. Grid Topology Identification via Distributed Statistical Hypothesis Testing<br>7. Learning Stable Volt/Var Controllers in Distribution Grids<br>8. Grid-edge Optimization and Control with Machine Learning<br>9. Fault Detection in Distribution Grid with Spatial-Temporal Recurrent Graph Neural Networks<br>10. Distribution Networks Events Analytics using Physics-Informed Graph Neural Networks<br>11. Transient Stability Predictions in Power Systems using Transfer Learning<br>12. Misconfiguration Detection of Inverter-based Units in Power Distribution Grids using Machine Learning<br>13. Virtual Inertia Provision from Distribution Power Systems using Machine Learning<br>14. Electricity Demand Flexibility Estimation in Warehouses using Machine Learning<br>15. Big Data Applications in Electric Power Systems: The Role of Explainable Artificial Intelligence (XAI) in Smart Grids<br>16. Photovoltaic and Wind Power Forecasting Using Data-Driven Techniques: an overview and a distribution-level case study<br>17. Grid resilience against wildfire with Machine Learning</p>