Y. Wu, H. Badihi, L. Wen, X. Fu, and Y. Xue, “Reinforcement learning for reliable power allocation and load mitigation in wind farm,” Presented at the 7th International Conference on Renewable Energy and Power Engineering, Beijing, China, September 25-27, 2024.
Does reinforcement learning hold the key to reliable fatigue load mitigation in wind farms? New research unveiled!
A recent study introduces a novel reinforcement learning (RL) approach to enhance power allocation and reduce fatigue loads in offshore wind farms. By leveraging dynamic shaft torque and tower bending moment data, the RL-based controller optimizes power generation strategies while mitigating stress on critical components. Tested under extreme operational conditions, the controller demonstrates significant improvements in wind turbine reliability, cutting cumulative loading by up to 22.56%. These findings pave the way for more efficient and resilient wind farm operations.