Zobrazeno 1 - 10
of 418
pro vyhledávání: '"Weng, Yang"'
Recent advancements in research have shown the efficacy of employing sensor measurements, such as voltage and power data, in identifying line outages within distribution grids. However, these measurements inadvertently pose privacy risks to electrici
Externí odkaz:
http://arxiv.org/abs/2309.05140
Publikováno v:
IEEE Transactions on Power Systems 2023
Line outage identification in distribution grids is essential for sustainable grid operation. In this work, we propose a practical yet robust detection approach that utilizes only readily available voltage magnitudes, eliminating the need for costly
Externí odkaz:
http://arxiv.org/abs/2309.07157
We articulate the design imperatives for machine-learning based digital twins for nonlinear dynamical systems subject to external driving, which can be used to monitor the ``health'' of the target system and anticipate its future collapse. We demonst
Externí odkaz:
http://arxiv.org/abs/2210.06144
Learning the underlying equation from data is a fundamental problem in many disciplines. Recent advances rely on Neural Networks (NNs) but do not provide theoretical guarantees in obtaining the exact equations owing to the non-convexity of NNs. In th
Externí odkaz:
http://arxiv.org/abs/2206.00257
Autor:
Saleem, Bilal, Weng, Yang
Distributed energy resources are better for the environment but may cause transformer overload in distribution grids, calling for recovering meter-transformer mapping to provide situational awareness, i.e., the transformer loading. The challenge lies
Externí odkaz:
http://arxiv.org/abs/2205.09874
This paper addresses the problem of real-time monitoring of long-term voltage instability (LTVI) by using local field measurements. Existing local measurement-based methods use Thevenin equivalent parameter estimation that is sensitive to the noise i
Externí odkaz:
http://arxiv.org/abs/2203.12857
Autor:
Chen, Zequn, Li, Xiaojing, Tang, Yiheng, Huang, Zhanchao, Huang, Ji, Liu, Haoran, Weng, Yang, Zhu, Yue, Zhao, Jingyang, Tang, Renjie, Liu, Zhu, Bao, Kangjian, Jian, Jialing, Ye, Yuting, Yun, Yiting, Wang, Lichun, Guo, Chengchen, Lin, Hongtao, Jiang, Hanqing, Si, Ke, Gong, Wei, Li, Lan
Publikováno v:
In Cell Reports Physical Science 16 October 2024 5(10)
Autor:
Matavalam, Amarsagar Reddy Ramapuram, Guddanti, Kishan Prudhvi, Weng, Yang, Ajjarapu, Venkataramana
This paper describes how domain knowledge of power system operators can be integrated into reinforcement learning (RL) frameworks to effectively learn agents that control the grid's topology to prevent thermal cascading. Typical RL-based topology con
Externí odkaz:
http://arxiv.org/abs/2112.09996
Artificial Intelligence (AI) techniques continue to broaden across governmental and public sectors, such as power and energy - which serve as critical infrastructures for most societal operations. However, due to the requirements of reliability, acco
Externí odkaz:
http://arxiv.org/abs/2111.02026
Publikováno v:
In Materials Today Communications March 2024 38