Wind Turbine Yaw Precision Control Under Variable Wind Conditions
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Solution Overview
Problem
Active yaw technology in large megawatt-scale wind turbines experiences yaw errors due to wind speed and direction fluctuations, leading to power loss and reduced efficiency.
Innovation Solution
A method and apparatus for dynamically determining yaw control precision by collecting and processing wind speed and direction data to establish models of correspondence relationships between wind conditions, yaw control precision, yaw fatigue, and power loss, allowing for real-time adjustments to optimize yaw control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If active yaw technology is used to track wind direction, then wind energy capture is improved, but yaw errors occur due to wind fluctuations and control precision limitations resulting in power loss
Solution Approach 1:
The patent implements dynamic adjustment of yaw control precision based on real-time wind conditions. The system transitions from static precision settings to dynamic adaptation, where the control precision is adjusted according to wind speed and direction variability. This resolves the contradiction by making the system flexible enough to capture wind energy effectively while minimizing power loss through adaptive precision control.
Solution Approach 2:
The patent changes the parameter of yaw control precision from a fixed value to a dynamically variable parameter. By establishing a correspondence model between wind conditions and optimal yaw precision, the system adjusts precision parameters in real-time. This allows the system to maximize energy capture when wind conditions are favorable while reducing power loss when wind fluctuations cause yaw errors.
2Measurement precision
If higher yaw control precision is maintained, then wind tracking accuracy is improved, but system complexity and control difficulty increase
Solution Approach 1:
Instead of maintaining constantly high precision which would increase complexity, the patent dynamically adjusts precision parameters based on wind conditions. The system uses a correspondence model to determine appropriate precision levels for different wind scenarios, achieving high tracking accuracy when needed while simplifying control during stable conditions.
Solution Approach 2:
The patent introduces dynamic adaptation in the control system, transitioning from static high-precision control to dynamic precision adjustment. This reduces overall system complexity by only applying high precision when wind conditions require it, while using lower precision during stable periods, thereby balancing accuracy with computational and operational simplicity.
3Loss of energy
If dynamic adjustment of yaw control precision is implemented, then power loss is reduced, but data processing and model establishment complexity increases
Solution Approach 1:
The patent performs preliminary data collection and model establishment during normal operation phases. By pre-processing wind data and establishing correspondence relationships between wind conditions and optimal yaw precision, the system reduces real-time computational complexity. The model is built in advance using historical data, allowing for faster real-time adjustments that reduce power loss without excessive processing complexity during critical control moments.
Solution Approach 2:
The patent implements a feedback mechanism where yaw control performance is continuously monitored and used to refine the correspondence model. This feedback loop allows the system to learn from actual operating conditions and improve precision adjustments over time, reducing power loss while managing data processing complexity through iterative optimization rather than complex real-time calculations.
Data Source
AI summary
A method and an apparatus for dynamically determining a yaw control precision. The method comprises: during a predetermined time period, collecting a plurality of wind speed data and a plurality of wind direction data, and processing the collected plurality of wind speed data and plurality of wind direction data; on the basis of the processed wind speed data and wind direction data, establishing a model of the corresponding relationship between wind speed, wind direction angle change, yaw control precision, yaw fatigue, and power loss; and, on the basis of the current wind speed data, wind direction data, predetermined yaw fatigue range, and predetermined power loss range, by means of the corresponding relationship model, determining the yaw control precision corresponding to the current wind speed and current wind direction angle change.