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Synapse
May 2, 2026

Voltage Stability for Power Systems deploying Physics-Grounded ML: Fast Risk Mapping with MATPOWER for Sustainable Future in Smart Grids

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Authors

RWRajitha WattegamaMSMichael ShortGAGeetika Aggarwal

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Overview

Randomized trial demonstrates improved voltage stability mapping in smart grids, suggesting enhanced risk management capabilities.

Key Points

  • This research aims to address voltage stability challenges in smart grids by using a physics-informed machine learning approach.
  • Combined MATPOWER simulations with an ensemble classifier for risk mapping.
  • Created operating scenarios by varying load levels and renewable penetration.
  • Trained the model on a balanced dataset comprising 40% unstable cases.
  • Achieved ROC-AUC = 0.973 and PR-AUC = 0.715 through five-fold cross-validation.
  • Identified load level and renewable penetration as primary instability causes.
  • Model provides results thousands of times faster than traditional methods while maintaining high accuracy.

Cite This Study

Wattegama et al. (2026) studied this question.

synapsesocial.com/papers/69f5951171405d493affff6bhttps://doi.org/10.1051/epjconf/202636703012/pdf
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