arXiv Machine Learning August 17, 2026 By Lukas Zetto, Benjamin Sch\"afer, Qiong Huang

Learning to Run Power Networks: Effective AlphaZero-inspired Topological Control

Read the original on arXiv Machine Learning →

arXiv:2608. 14114v1 Announce Type: new Abstract: As the integration of volatile renewable energy sources increases the strain on modern power grids, the use of Reinforcement Learning (RL) for autonomous topological reconfiguration has emerged as a promising research field to keep strained grids stable and operational.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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