Verifying Machine Learning conclusions for securing Low Inertia systems

Machine Learning (ML) for real-time Dynamic Security Assessment (DSA) promises a probabilistic approach to secure lower safety margins and costs. However, future systems with a high share of renewables have low inertia and converter-interfaced devices resulting in faster dynamics. Past research on ML-based DSA used high inertia systems to...

Machine-learned security assessment for changing system topologies

Machine learning has been used in the past to construct predictors, also known as classifiers, for dynamic security assessment. Although accurate classifiers can be trained for a single topology, often they do not work for another. However, the power system topology can change frequently during operation due to maintenance and control actions...