Search Results for author: Tianzhixi Yin

Found 8 papers, 0 papers with code

Toward Intelligent Emergency Control for Large-scale Power Systems: Convergence of Learning, Physics, Computing and Control

no code implementations8 Oct 2023 Qiuhua Huang, Renke Huang, Tianzhixi Yin, Sohom Datta, Xueqing Sun, Jason Hou, Jie Tan, Wenhao Yu, YuAn Liu, Xinya Li, Bruce Palmer, Ang Li, Xinda Ke, Marianna Vaiman, Song Wang, Yousu Chen

Our developed methods and platform based on the convergence framework have been applied to a large (more than 3000 buses) Texas power system, and tested with 56000 scenarios.

Efficient Learning of Voltage Control Strategies via Model-based Deep Reinforcement Learning

no code implementations6 Dec 2022 Ramij R. Hossain, Tianzhixi Yin, Yan Du, Renke Huang, Jie Tan, Wenhao Yu, YuAn Liu, Qiuhua Huang

We propose a novel model-based-DRL framework where a deep neural network (DNN)-based dynamic surrogate model, instead of a real-world power-grid or physics-based simulation, is utilized with the policy learning framework, making the process faster and sample efficient.

Imitation Learning reinforcement-learning +1

Physics-informed Evolutionary Strategy based Control for Mitigating Delayed Voltage Recovery

no code implementations29 Nov 2021 Yan Du, Qiuhua Huang, Renke Huang, Tianzhixi Yin, Jie Tan, Wenhao Yu, Xinya Li

Reinforcement learning methods have been developed for the same or similar challenging control problems, but they suffer from training inefficiency and lack of robustness for "corner or unseen" scenarios.

Scalable Voltage Control using Structure-Driven Hierarchical Deep Reinforcement Learning

no code implementations29 Jan 2021 Sayak Mukherjee, Renke Huang, Qiuhua Huang, Thanh Long Vu, Tianzhixi Yin

We exploit the area-wise division structure of the power system to propose a hierarchical DRL design that can be scaled to the larger grid models.

reinforcement-learning Reinforcement Learning (RL)

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