Jun 26, 2023 · This is the first work that proposes an Adaptive and Safe-Certified DRL (AdapSafe) algorithm for frequency control to simultaneously address the aforementioned ...
In particular , a novel self-tuning control barrier function is designed to actively compensate the unsafe frequency control strategies under variational safety ...
Feb 7, 2023 · AdapSafe: adaptive and safe-certified deep reinforcement learning-based frequency control for carbon-neutral power systems. AUTHORs: Xu Wan.
Experiments are conducted based on GB 2030 power system, and the results demonstrate that the proposed AdapSafe exhibits superior performance in terms of its ...
(1) To the best of the authors' knowledge, this is the first work that proposes an Adaptive and Safe-Certified DRL. (AdapSafe) algorithm for power system ...
AdapSafe: Adaptive and Safe-Certified Deep Reinforcement Learning-Based Frequency Control for Carbon-neutral Power Systems. X Wan, M Sun, B Chen, Z Chu, F Teng.
AdapSafe: Adaptive and Safe-Certified Deep Reinforcement Learning-Based Frequency Control for Carbon-Neutral Power Systems. Proceedings of the AAAI ...
Teng, “AdapSafe: Adaptive and Safe-Certified Deep Reinforcement Learning-Based Frequency Control for Carbon-Neutral Power Systems,” Proceedings of the AAAI ...
AdapSafe: Adaptive and Safe-Certified Deep Reinforcement Learning-Based Frequency Control for Carbon-Neutral Power Systems. 27 Jun 2023Proceedings of the ...
AdapSafe: Adaptive and Safe-Certified Deep Reinforcement Learning-Based Frequency Control for Carbon-Neutral Power Systems. In AAAI, 5294–5302. Wan, Zeng ...