5 citations · 6 across the 3 of their papers we have counts for
5 papers
Rethink AI-based Power Grid Control: Diving Into Algorithm Design
Xiren Zhou, Siqi Wang, Ruisheng Diao +3
Recently, deep reinforcement learning (DRL)-based approach has shown promisein solving complex decision and control problems in power engineering domain.In this paper, we present a…
On Training Effective Reinforcement Learning Agents for Real-time Power Grid Operation and Control
Ruisheng Diao, Di Shi, Bei Zhang +6
Deriving fast and effectively coordinated control actions remains a grand challenge affecting the secure and economic operation of today's large-scale power grid. This paper presen…
Evaluating Load Models and Their Impacts on Power Transfer Limits
Xinan Wang, Yishen Wang, Di Shi +4
Power transfer limits or transfer capability (TC) directly relate to the system operation and control as well as electricity markets. As a consequence, their assessment has to comp…
Global Sensitivity Analysis in Load Modeling via Low-rank Tensor
You Lin, Yishen Wang, Jianhui Wang +2
Growing model complexities in load modeling have created high dimensionality in parameter estimations, and thereby substantially increasing associated computational costs. In this…
A Deep Reinforcement Learning Based Approach for Optimal Active Power Dispatch
Jiajun Duan, Haifeng Li, Xiaohu Zhang +6
The stochastic and dynamic nature of renewable energy sources and power electronic devices are creating unique challenges for modern power systems. One such challenge is that the c…