Wind Turbine Yaw Misalignment Calibration From Power Differences
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Solution Overview
Problem
Existing wind turbine yaw systems often suffer from misalignment due to inaccurate wind direction measurements, leading to reduced power production, increased structural loads, and noise emissions, which current calibration methods fail to adequately address.
Innovation Solution
A method and device that calibrate the yaw system by performing yaw events in both clockwise and counter-clockwise directions, recording and averaging data before the event, calculating performance differences, and determining yaw misalignment based on theoretical and experimental power parameters to minimize errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wind direction measurement is slightly off, then yaw misalignment occurs, but power production significantly decreases and structural loads increase
Solution Approach 1:
The patent implements a feedback mechanism where the controller continuously monitors performance parameters (power production, loads) and compares them with expected values based on wind direction measurements. When deviations are detected, the system automatically adjusts the yaw misalignment compensation, creating a closed-loop control system that corrects measurement errors in real-time
Solution Approach 2:
The patent replaces direct mechanical measurement of wind direction with an indirect measurement approach using performance parameters (power output, structural loads) as proxies. By analyzing the relationship between performance metrics and wind direction, the system calculates compensated wind direction values that account for sensor inaccuracies, substituting mechanical sensing with performance-based inference
2Productivity
If controller settings are not optimized, then setup is simpler, but power production is reduced and noise emissions increase
Solution Approach 1:
The patent enables the controller to automatically optimize its own settings by utilizing the turbine's operational data and performance parameters. The system self-calibrates the yaw misalignment compensation without requiring external intervention or complex manual tuning, making the optimization process autonomous and eliminating the need for specialized calibration equipment
Solution Approach 2:
The patent dynamically adjusts controller parameters (yaw misalignment compensation values) based on observed performance deviations. By continuously modifying these parameters in response to measured performance changes, the system adapts to varying operating conditions and maintains optimal power production without fixed, pre-determined settings
3Manufacturing precision
If model simplifications are used, then calculations are faster, but calibration accuracy decreases due to tolerances and deviations
Solution Approach 1:
The patent uses feedback from actual turbine performance measurements to correct for model simplifications and manufacturing tolerances. By comparing predicted performance (from simplified models) with actual measured performance, the system calculates correction factors that compensate for deviations, achieving high calibration accuracy without requiring complex models
Solution Approach 2:
The patent performs preliminary calibration using simplified models and available performance data before final deployment. This preliminary action establishes initial compensation values that are then refined through operational feedback, reducing the impact of manufacturing tolerances and model simplifications from the outset
Data Source
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AI summary
It is described a method of calibrating a yaw system of a wind turbine, the method comprising steps of performing a yaw event at a yaw event time (T0) in a clockwise direction and a counter-clockwise direction, calculating absolute errors (Ecw, Eccw) which are the differences between an experimental performance parameter difference (P2 - P1) and a theoretical performance parameter difference (Py +WD1 - Py +WD2) of the yaw events in the clockwise direction and a counter-clockwise direction; adding up the absolute errors to obtain a total error; determining a minimum (idx) of the total error; and determining a yaw misalignment based on the minimum error.