Transmission Network Expansion Planning Considering Wind Power and Load Uncertainties Based on Multi-Agent DDQN

This paper presents a multi-agent Double Deep Q Network (DDQN) based on deep reinforcement learning for solving the transmission network expansion planning (TNEP) of a high-penetration renewable energy source (RES) system considering uncertainty. First, a K-means algorithm that enhances the extracti...

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Bibliographic Details
Published in:Energies
Main Authors: Yuhong Wang, Xu Zhou, Yunxiang Shi, Zongsheng Zheng, Qi Zeng, Lei Chen, Bo Xiang, Rui Huang
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Subjects:
transmission network expansion planning (TNEP)
deep reinforcement learning
uncertainty
wind power
multi-agent DDQN
Online Access:https://www.mdpi.com/1996-1073/14/19/6073

Internet

https://www.mdpi.com/1996-1073/14/19/6073

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