A hierarchical RL-MPC framework for dynamic wake steering in wind farms delivers 23% power gain over baseline on a three-turbine case while outperforming idealized MPC with perfect state knowledge and offering safer training than direct RL.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SY 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Hierarchical RL-MPC Control for Dynamic Wake Steering in Wind Farms
A hierarchical RL-MPC framework for dynamic wake steering in wind farms delivers 23% power gain over baseline on a three-turbine case while outperforming idealized MPC with perfect state knowledge and offering safer training than direct RL.