37 citations · 85 across the 9 of their papers we have counts for
4 papers · 1 filter
Online Reinforcement Learning Control by Direct Heuristic Dynamic Programming: from Time-Driven to Event-Driven
Qingtao Zhao, Jennie Si, Jian Sun
In this paper time-driven learning refers to the machine learning method that updates parameters in a prediction model continuously as new data arrives. Among existing approximate…
Gauss-Newton Unrolled Neural Networks and Data-driven Priors for Regularized PSSE with Robustness
Qiuling Yang, Alireza Sadeghi, Gang Wang +2
Distributed renewable generation, elastic loads, and purposeful manipulation of meter readings challenge the monitoring and control of today's power systems (PS). In this context,…
A Statistical Learning Approach to Reactive Power Control in Distribution Systems
Qiuling Yang, Alireza Sadeghi, Gang Wang +2
Pronounced variability due to the growth of renewable energy sources, flexible loads, and distributed generation is challenging residential distribution systems. This context, moti…
Two-Timescale Voltage Control in Distribution Grids Using Deep Reinforcement Learning
Qiuling Yang, Gang Wang, Alireza Sadeghi +2
Modern distribution grids are currently being challenged by frequent and sizable voltage fluctuations, due mainly to the increasing deployment of electric vehicles and renewable ge…