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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Κύριοι συγγραφείς:	Yuhong Wang, Xu Zhou, Yunxiang Shi, Zongsheng Zheng, Qi Zeng, Lei Chen, Bo Xiang, Rui Huang
Μορφή:	Artigo
Γλώσσα:	Inglês
Έκδοση:	MDPI AG 2021-09-01
Σειρά:	Energies
Θέματα:	transmission network expansion planning (TNEP) deep reinforcement learning uncertainty wind power multi-agent DDQN
Διαθέσιμο Online:	https://www.mdpi.com/1996-1073/14/19/6073
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