Graph Neural Networks in Power Systems - Literature Review
Welcome to our comprehensive review of Graph Neural Networks (GNNs) applications in power systems. This blog presents our findings from the DRACOS GNN study, analyzing the latest research and developments in this emerging field.
🚧 Companion Web Page Under Construction
🚧 Companion Web Page Under Construction
This page is being developed to accompany our research review. Features and content may be updated as development continues.
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About This Review
Our study examines the application of Graph Neural Networks in power systems, covering topics such as:
- Power Flow Analysis - Using GNNs for efficient grid calculations
- Fault Detection - Identifying and diagnosing system failures
- Grid Stability - Assessing and maintaining system reliability
- Load Forecasting - Predicting energy demand patterns
- Network Optimization - Improving grid efficiency and performance
Research Methodology
We conducted a systematic literature review, analyzing papers from major conferences and journals in power systems and machine learning. Each paper was evaluated based on:
- Technical contribution
- Application domain
- Methodology effectiveness
- Citation impact
- Practical applicability
Stay tuned for more detailed analysis and insights from our comprehensive review!