Power system corrective control considering topology adjustment: An evolution-enhanced reinforcement learning method
Effective corrective control is critical for maintaining secure power system operations. Conventional corrective control methods often struggle to balance computational speed with control optimality. In contrast, deep reinforcement learning facilitates faster control. However, significant uncertaint...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | International Journal of Electrical Power & Energy Systems |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0142061525004272 |
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