Distribution System Resilience Under Asynchronous Information Using Deep Reinforcement Learning

• Published in: IEEE transactions on power systems Vol. 36; no. 5; pp. 4235 - 4245
• Main Authors: Bedoya, Juan Carlos, Wang, Yubo, Liu, Chen-Ching
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial intelligence; Asynchronous information; Decision making; Deep learning; deep reinforcement learning; distribution system restoration; Mathematical models; Monte Carlo methods; Monte Carlo tree search; Optimization; Power system restoration; Reinforcement learning; Resilience; resilient distribution systems; Restoration

Resilience of a distribution system can be enhanced by efficient restoration of critical load following a major outage. Existing models include optimization approaches that consider available information without incorporating the inherent asynchrony of data arrival during execution of the restoratio...