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Graph neural network-guided topology ranking with 24-h physical screening for distribution network reconfiguration

https://doi.org/10.2139/ssrn.7269428
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Outgoing claims: the papers this work cites, builds on, or argues with.

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A Comparative Study of Reinforcement Learning Algorithms for Distribution Network Reconfiguration With Deep Q-Learning-Based Action Sampling
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Comprehensive Review on Static and Dynamic Distribution Network Reconfiguration Methodologies
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Topology-Transferable Physics-Guided Graph Neural Network for Real-Time Optimal Power Flow
inferredcites →https://doi.org/10.1109/tpwrd.2021.3107534openalex-snapshot
Many-Objective Distribution Network Reconfiguration Via Deep Reinforcement Learning Assisted Optimization Algorithm
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Imposing Radiality Constraints in Distribution System Optimization Problems
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Minimum Loss Network Reconfiguration Using Mixed-Integer Convex Programming
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Feeder Reconfiguration in Distribution Networks Based on Convex Relaxation of OPF
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A New Formulation of Distribution Network Reconfiguration for Reducing the Voltage Volatility Induced by Distributed Generation
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A Two-Stage Multi-Agent Deep Reinforcement Learning Method for Urban Distribution Network Reconfiguration Considering Switch Contribution
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Coordinated Distribution Network Reconfiguration and Power Flow Optimization Based on Optimal Policy Tree and Constraint Learning
inferredcites →https://doi.org/10.1109/tsg.2019.2963696openalex-snapshot
MDP-Based Distribution Network Reconfiguration With Renewable Distributed Generation: Approximate Dynamic Programming Approach
inferredcites →https://doi.org/10.1109/tsg.2020.2985087openalex-snapshot
Radiality Constraints for Resilient Reconfiguration of Distribution Systems: Formulation and Application to Microgrid Formation
inferredcites →https://doi.org/10.1109/tsg.2020.3005270openalex-snapshot
Batch-Constrained Reinforcement Learning for Dynamic Distribution Network Reconfiguration
inferredcites →https://doi.org/10.1109/tsg.2021.3097330openalex-snapshot
Distribution Network Reconfiguration for Short-Term Voltage Stability Enhancement: An Efficient Deep Learning Approach
inferredcites →https://doi.org/10.1109/tsg.2023.3324474openalex-snapshot
Real-Time Coordination of Dynamic Network Reconfiguration and Volt-VAR Control in Active Distribution Network: A Graph-Aware Deep Reinforcement Learning Approach
inferredcites →https://doi.org/10.1109/tsg.2024.3404859openalex-snapshot
Dynamic Distribution Network Reconfiguration With Generation and Load Uncertainty
inferredcites →https://doi.org/10.52202/068431-2319openalex-snapshot
Learning to Compare Nodes in Branch and Bound with Graph Neural Networks
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