Federated Learning Forecasting for Strengthening Grid Reliability and Enabling Markets for Resilience

2024-07-16 · Lucas Pereira, Vineet Jagadeesan Nair, Bruno Dias, Hugo Morais, Anuradha Annaswamy

We propose a comprehensive approach to increase the reliability and resilience of future power grids rich in distributed energy resources. Our distributed scheme combines federated learning-based attack detection with a local electricity market-based attack mitigation method. We validate the scheme by applying it to a real-world distribution grid rich in solar PV. Simulation results demonstrate that the approach is feasible and can successfully mitigate the grid impacts of cyber-physical attacks.

📄 PDF Abstract BibTeX arXiv:2407.11571

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