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Using SHAP Values and Machine Learning to Understand Trends in the Transient Stability Limit
Machine learning (ML) for transient stability assessment has gained traction due to the significant increase in computational requirements as renewables connect to power systems.
Interpretable Machine Learning for Power Systems: Establishing Confidence in SHapley Additive exPlanations
To do so, we demonstrate that the Power Transfer Distribution Factors (PTDF) -- a physics-based linear sensitivity index -- can be derived from the SHAP values.
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