基于机舱式激光测风雷达的尾流优化控制方法和系统
By acquiring wake point cloud and wind turbine status data using a nacelle-type laser wind radar, and combining historical data to predict wake trends, monitor control unit status, and generate optimized control strategies, the problem of poor wake model adaptability and unstable control execution is solved, achieving efficient and reliable wake avoidance control.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- STATE POWER INVESTMENT GRP LANXIAN NEW ENERGY CO LTD
- Filing Date
- 2025-10-16
- Publication Date
- 2026-07-17
AI Technical Summary
In existing technologies, the wake effect of upstream wind turbines in medium and large-sized wind farms leads to a decrease in wind speed and an increase in turbulence in downstream wind turbines. Existing analytical wake models have poor adaptability and are difficult to accurately characterize the asymmetric diffusion and dynamic drift of the wake in three-dimensional space. Control decisions lack closed-loop monitoring, and optimization commands are difficult to execute stably.
By acquiring wake point cloud data and wind turbine operating status data through nacelle-type laser wind radar, spatial coordinate transformation and grid division are performed. Combined with historical data, wake movement trends are predicted, control unit status is monitored, optimized control strategies are generated, and blade angles and yaw angles are adjusted.
It achieves high-precision perception of wake characteristics, improves the accuracy of wake range judgment and spatial targeting of control strategies, enhances the robustness and reliability of control, and reduces wind energy loss and equipment failure risks.
Smart Images
Figure CN121657065B_ABST