15 citations · 26 across the 11 of their papers we have counts for
5 papers · 1 filter
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…
The Power Grid Library for Benchmarking AC Optimal Power Flow Algorithms
Sogol Babaeinejadsarookolaee, Adam Birchfield, Richard D. Christie +20
In recent years, the power systems research community has seen an explosion of novel methods for formulating the AC power flow equations. Consequently, benchmarking studies using t…
Adaptive Robust Energy Management Strategy for Campus-Based Commercial Buildings Considering Comprehensive Comfort Levels
Zheming Liang, Desong Bian, Dawei Su +4
Neglecting consumers' comfort always leads to failure or slow-response to demand response request. In this paper, we propose several comprehensive comfort level models for various…
Optimal Energy Management for Commercial Buildings Considering Comprehensive Comfort Levels in a Retail Electricity Market
Zheming Liang, Desong Bian, Xiaohu Zhang +3
Demand response has been implemented by distribution system operators to reduce peak demand and mitigate contingency issues on distribution lines and substations. Specifically, the…