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Fast preventive transient stability control based on distributional deep reinforcement learning and graph isomorphism network
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DOI：10.1016/j.ijepes.2025.111455.png)
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Abstract
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• Propose a fast preventive transient stability control method using distributional deep reinforcement learning and graph isomorphism network. • Develop a graph isomorphism network-based transient stability index predictor to capture grid structural features and improve stability assessment. • Design a distributional soft actor-critic reinforcement learning algorithm for enhanced policy robustness under uncertainties. • Validate the method on 39-bus, 189-bus and 300-bus systems, showing improved stability and efficiency.
Keywords:
Transient stability
Preventive control
Graph isomorphism networks
Distributional deep reinforcement learning
Return distribution quantiles
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