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Efficient Learning of Power Grid Voltage Control Strategies via Model-based Deep Reinforcement Learning

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A Two-Stage Approach for PV Inverter Engagement in Power Factor Correction and Voltage Regulation

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Advanced Computing Is at the Forefront of a New “Moonshot” Revolutionizing the North American Power Grid

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An Open-Source Library of Phasor Measurement Unit Data Capturing Real Bulk Power Systems Behavior

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Physics-informed Deep Reinforcement Learning-based Adaptive Generator Out-of-step Protection for Power Systems

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Grid Strength Assessment for High Levels of Inverter-based Resources in the Puerto Rico Power

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Identifying Robust Decarbonization Pathways for the Western U.S. Electric Power System under Deep Climate Uncertainty

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Scalable Risk Assessment of Rare Events in Power Systems with Uncertain Wind Generation and Loads

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Impact of IBR Location and Parameters on Inter-Area Oscillation Modes in Bulk Power Grids

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Nature-GL: A Revolutionary Learning Paradigm Unleashing Nature’s Power in Real-World Spatial-Temporal Graph Learning