Yaw parameter optimization method, device and equipment based on wind farm and storage medium
By using an automated yaw parameter optimization method, deep learning and particle swarm optimization are employed to generate the optimal yaw angle sequence for wind farms, solving the problem of low efficiency in manual operation and achieving efficient automated optimization and stability improvement for wind farms.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- LANZHOU JIAOTONG UNIV
- Filing Date
- 2026-04-25
- Publication Date
- 2026-07-17
AI Technical Summary
Existing methods for optimizing yaw parameters in wind farms rely on manual operation, resulting in long acquisition times and low efficiency in obtaining the optimal yaw angle sequence for wind farms.
By acquiring data from each wind turbine in the wind farm, a yaw angle sequence is generated using a deep learning network and an improved particle swarm optimization algorithm. Combined with a power prediction model and an optimization function, the yaw angle sequence of the wind farm is automatically optimized.
The optimal yaw angle sequence can be quickly obtained without manual operation, which improves the acquisition efficiency of wind farms and enhances power generation efficiency and operational stability through collaborative optimization.
Smart Images
Figure CN122407458A_ABST