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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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An environment-adaptive protection scheme with long-term reward for distribution networks
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An Efficient Framework for Multi-DER Integration in Distribution Networks With Time-Series Demand Flexibility
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Risk-Averse Cooperative Operation of PV and Hydrogen Systems in Active Distribution Networks
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Data-Driven Risk Analysis of Joint Electric Vehicle and Solar Operation in Distribution Networks
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An Online Feedback-Based Linearized Power Flow Model for Unbalanced Distribution Networks
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Convergence of Distributed Steinmetz Control for Balancing Distribution Network Voltages
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Online Voltage Control for Unbalanced Distribution Networks Using Projected Newton Method
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Unsupervised Impedance and Topology Estimation of Distribution Networks—Limitations and Tools
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Batch-Constrained Reinforcement Learning for Dynamic Distribution Network Reconfiguration
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Dynamic Temporal Graph Sequence Data for Resilience-Oriented Distribution Network Reconfiguration
This dataset comprises temporal dynamic graph sequences generated from power grid simulations focused on grid reconfiguration to enhance resilience. The simulations model failure propagation under varying conditions, with nodes assigned distinct failure probabilities. For each time step, the dataset captures the evolution of node states (functional or failed) and features critical to grid operations, such as pv_output, load_profile, load_dispatch, dg_output, loss, and voltage. Node types include sources, normal loads, and nodes with specific equipment like PVs, micro turbines, or shunt capacitors. The dataset is structured to support the training of dynamic graph neural networks, facilitating research on node feature prediction and edge dynamics under failure scenarios. Three distinct configurations are included, providing a robust foundation for modeling power grid resilience.
Machine Learning Embedded in Distribution Network Relays to Classify and Locate Faults.
Abstract not provided.
A Data Driven Approach for Resilience Analysis of Water Distribution Networks
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Synthetic Water Distribution Network Models: Challenges and Opportunities
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