Resilient dispatching optimization of power system driven by deep reinforcement learning model

Resilient dispatching optimization of power system driven by deep reinforcement learning model

Abstract Power systems face many complex and severe challenges in today's power sector. Within the system, the stability and reliability of the power supply are affected by the rapid adjustment of the energy structure. Outside the system, the frequent occurrence of extreme weather events also p...

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Bibliographic Details
Main Authors: Haifeng Zhang, Yifu Zhang, Jiajun Zhang, Xiangdong Meng, Jiazu Sun
Format: Article
Language:English
Published: Springer 2025-07-01
Series:Discover Artificial Intelligence
Subjects:
Deep reinforcement learning
Power mobilization
Scheduling resilience
System optimization
Online Access:https://doi.org/10.1007/s44163-025-00451-1
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https://doi.org/10.1007/s44163-025-00451-1

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