Distribution Network Reconfiguration Based on NoisyNet Deep Q-Learning Network

The distribution network reconfiguration (DNR) aims at minimizing the power losses and improving the voltage profile. Traditional model-based methods exactly need the network parameters to derive the optimal configuration of the distribution network. This paper proposes a DNR method based on model-f...

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Veröffentlicht in:	IEEE access 2021, Vol.9, p.90358-90365
Hauptverfasser:	Wang, Beibei, Zhu, Hong, Xu, Honghua, Bao, Yuqing, Di, Huifang
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science Computer Science, Information Systems Deep Q-learning network (DQN) Distribution network reconfiguration Distribution networks Encoding Engineering Engineering, Electrical & Electronic Machine learning Mathematical model Mathematical models Noise measurement NoisyNet Optimization Parameters Reconfiguration Science & Technology Switches Technology Telecommunications Topology
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