15 citations · 19 across the 4 of their papers we have counts for
6 papers · 1 filter
AI-Based Autonomous Line Flow Control via Topology Adjustment for Maximizing Time-Series ATCs
Tu Lan, Jiajun Duan, Bei Zhang +4
This paper presents a novel AI-based approach for maximizing time-series available transfer capabilities (ATCs) via autonomous topology control considering various practical constr…
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…
Autonomous Voltage Control for Grid Operation Using Deep Reinforcement Learning
Ruisheng Diao, Zhiwei Wang, Di Shi +3
Modern power grids are experiencing grand challenges caused by the stochastic and dynamic nature of growing renewable energy and demand response. Traditional theoretical assumption…
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…
Adaptive Online Learning with Momentum for Contingency-based Voltage Stability Assessment
Zhijie Nie, Xiaohu Zhang, Xiaoying Zhao +4
Voltage stability refers to the ability of a power system to maintain acceptable voltages among all buses under normal operating conditions and after a disturbance. In this paper,…
Submodular Load Clustering with Robust Principal Component Analysis
Yishen Wang, Xiao Lu, Yiran Xu +4
Traditional load analysis is facing challenges with the new electricity usage patterns due to demand response as well as increasing deployment of distributed generations, including…