"A Model-Free Reward\u2013Gradient\u2013Informed Deep Q-Learning (RG-DQL) for Adaptive Voltage Regulation in Hybrid AC\/DC Microgrid"
收藏DataCite Commons2026-04-18 更新2026-05-03 收录
下载链接：
https://ieee-dataport.org/documents/model-free-reward-gradient-informed-deep-q-learning-rg-dql-adaptive-voltage-regulation
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资源简介：
"This dataset provides the complete code and simulation framework supporting the paper \u201cA Model-Free Reward\u2013Gradient\u2013Informed Deep Q-Learning (RG-DQL) for Adaptive Voltage Regulation in Hybrid AC\/DC Microgrid.\u201d The repository includes Jupyter notebooks, Python scripts, and configuration files implementing the hybrid AC\/DC microgrid model, the reinforcement learning environment, and the proposed RG-DQL controller.The dataset also contains baseline implementations (PID and DDPG), evaluation scripts, and figure-generation tools to reproduce the results reported in the paper. It enables full reproducibility of the training process, performance evaluation, and comparative analysis.This dataset is intended for researchers and engineers working in power systems, power electronics, and reinforcement learning, providing a practical benchmark for model-free voltage control in inverter-dominated microgrids under unbalanced and time-varying conditions."
提供机构：
IEEE DataPort
创建时间：
2026-04-18
