A dual-policy PPO agent with graph neural networks survives extreme N-k contingencies on a simulated IEEE 14-bus grid far longer than a no-action baseline.
A deep reinforcement learning framework for automatic operation control of power system considering extreme weather events,
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Robust Defense Against Extreme Grid Events Using Dual-Policy Reinforcement Learning Agents
A dual-policy PPO agent with graph neural networks survives extreme N-k contingencies on a simulated IEEE 14-bus grid far longer than a no-action baseline.