Dynamic Wind Turbine Reference Calibration
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Solution Overview
Problem
Existing wind turbine icing detection systems rely on reference power curves that are not dynamically calibrated, leading to potential inaccuracies in detecting icing conditions and optimizing wind turbine operation.
Innovation Solution
A method for calibrating the reference of a wind turbine by monitoring its performance over a calibration period, divided into sub-periods, and updating the reference based on performance data that indicates better performance than the current reference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a static reference power curve is used for icing detection, then the system is simple to implement, but the detection accuracy deteriorates under changing operational conditions
Solution Approach 1:
The reference power curve is transformed from a static value to a dynamic, adaptive reference that automatically updates based on monitored performance data. The system continuously calibrates the reference by comparing actual performance against the evolving reference curve, allowing it to adapt to changing operational conditions while maintaining detection accuracy.
Solution Approach 2:
The calibration system uses the wind turbine's own performance data to self-calibrate the reference power curve without requiring external intervention or manual adjustments. The system monitors its own output and automatically updates the reference based on observed performance patterns, making the calibration process autonomous and eliminating the need for complex external calibration equipment.
2Measurement precision
If the reference is updated frequently to capture changing conditions, then the detection accuracy improves, but the system complexity and computational load increase
Solution Approach 1:
The calibration process operates periodically rather than continuously, updating the reference power curve at predetermined intervals or based on accumulated data thresholds. This periodic calibration approach maintains measurement precision by regularly refreshing the reference while avoiding the computational burden of continuous updates, thus balancing accuracy with system simplicity.
3Adaptability or versatility
If performance data from all conditions is used to update the reference, then the reference becomes more representative, but the risk of ice-contaminated data degrading the reference increases
Solution Approach 1:
The calibration process applies different treatment to different portions of the performance data based on local conditions. Performance data is segmented by operational conditions, and the reference update process selectively incorporates data from specific condition ranges while excluding data that shows signs of ice contamination. This local quality approach allows the reference to adapt to normal operational variations while remaining resistant to degradation from abnormal icing conditions.
Data Source
AI summary
A method of calibrating a reference of a wind turbine. The method comprises monitoring performance of the wind turbine over a calibration period to generate performance data, wherein the calibration period comprises a series of sub-periods. The reference is calibrated by: setting the reference on the basis of the performance data; and, for each sub-period: determining a sub-period value on the basis of the performance data generated during that sub-period, comparing the sub-period value with the reference, and updating the reference with the sub-period value if the comparison shows that a performance of the wind turbine indicated by the sub-period value is better than a performance of the wind turbine indicated by the reference. The comparison and updating steps enable the reference to more accurately reflect more recent performance of the wind turbine. The method can also be reliably used in freezing temperatures.