Search Results for author:
Found 3 papers, 1 papers with code
Review of Learning-Assisted Power System Optimization
With dramatic breakthroughs in recent years, machine learning is showing great potential to upgrade the toolbox for power system optimization.
Systems and Control Systems and Control Optimization and Control
Evaluation of Look-ahead Economic Dispatch Using Reinforcement Learning
In this paper, we propose an evaluation approach to analyze the performance of RL agents in a look-ahead economic dispatch scheme.
Look-Ahead AC Optimal Power Flow: A Model-Informed Reinforcement Learning Approach
With the increasing proportion of renewable energy in the generation side, it becomes more difficult to accurately predict the power generation and adapt to the large deviations between the optimal dispatch scheme and the day-ahead scheduling in the process of real-time dispatch.
