15 citations · 19 across the 6 of their papers we have counts for
6 papers
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…
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…
Probabilistic Load Forecasting via Point Forecast Feature Integration
Qicheng Chang, Yishen Wang, Xiao Lu +4
Short-term load forecasting is a critical element of power systems energy management systems. In recent years, probabilistic load forecasting (PLF) has gained increased attention f…
Short-term Load Forecasting at Different Aggregation Levels with Predictability Analysis
Yayu Peng, Yishen Wang, Xiao Lu +4
Short-term load forecasting (STLF) is essential for the reliable and economic operation of power systems. Though many STLF methods were proposed over the past decades, most of them…
Bayesian Estimation Based Parameter Estimation for Composite Load
Chang Fu, Zhe Yu, Di Shi +4
Accurate identification of parameters of load models is essential in power system computations, including simulation, prediction, and stability and reliability analysis. Convention…
An Extended Kalman Filter Enhanced Hilbert-Huang Transform in Oscillation Detection
Zhe Yu, Di Shi, Haifeng Li +3
Hilbert-Huang transform (HHT) has drawn great attention in power system analysis due to its capability to deal with dynamic signal and provide instantaneous characteristics such as…