Deep Reinforcement Learning Based Approach for Optimal Power Flow of Distribution Networks Embedded with Renewable Energy and Storage Devices

Deep Reinforcement Learning Based Approach for Optimal Power Flow of Distribution Networks Embedded with Renewable Energy and Storage Devices

This study proposes a deep reinforcement learning (DRL) based approach to analyze the optimal power flow (OPF) of distribution networks (DNs) embedded with renewable energy and storage devices. First, the OPF of the DN is formulated as a stochastic nonlinear programming problem. Then, the multi-peri...

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Bibliographic Details
Main Authors: Di Cao, Weihao Hu, Xiao Xu, Qiuwei Wu, Qi Huang, Zhe Chen, Frede Blaabjerg
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:Journal of Modern Power Systems and Clean Energy
Subjects:
Deep reinforcement learning (DRL)
optimal power flow (OPF)
wind turbine
distribution network
Online Access:https://ieeexplore.ieee.org/document/9465777/

Internet

https://ieeexplore.ieee.org/document/9465777/

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