A Novel Graph Reinforcement Learning-Based Approach for Dynamic Reconfiguration of Active Distribution Networks with Integrated Renewable Energy

A Novel Graph Reinforcement Learning-Based Approach for Dynamic Reconfiguration of Active Distribution Networks with Integrated Renewable Energy

The dynamic reconfiguration of active distribution networks (ADNDR) essentially belongs to a complex high-dimensional mixed-integer nonlinear stochastic optimization problem. Traditional mathematical optimization algorithms tend to encounter issues like slow computational speed and difficulties in s...

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Bibliographic Details
Main Authors: Hua Zhan, Changxu Jiang, Zhen Lin
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Energies
Subjects:
active distribution network
distribution network dynamic reconfiguration
graph convolutional network
deep deterministic policy gradient
deep reinforcement learning
Online Access:https://www.mdpi.com/1996-1073/17/24/6311
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