Wind Turbine Yaw Error Compensation via True Power Curve Fitting
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Solution Overview
Problem
Current methods for determining the yaw error angle in wind turbines rely on direct measurement, which can lead to significant errors due to mechanical issues and calibration inaccuracies, affecting the performance of the yaw system and overall wind power generation efficiency.
Innovation Solution
A method for identifying and compensating inherent yaw error deviations using data analysis, fitting true power curves within different yaw error intervals, and applying a compensation strategy to improve power generation output, incorporating outlier detection algorithms and B-spline fitting for accurate performance index calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct measurement method is used to determine yaw error angle, then the measurement process is simple, but the measurement precision deteriorates due to calibration inaccuracies and mechanical errors
Solution Approach 1:
The patent replaces the mechanical direct measurement system (anemometer-based) with a data analysis-based computational system. By using power curve fitting and outlier detection algorithms, the system calculates yaw error angle indirectly from operational data, eliminating mechanical calibration issues while achieving higher precision through mathematical modeling and statistical analysis.
2Manufacturing precision
If anemometer calibration is performed by experience or visual inspection, then the calibration process is simple and quick, but the manufacturing precision deteriorates leading to zero position errors
Solution Approach 1:
The system performs self-calibration by using its own operational data to identify and correct yaw error inherent deviations. Through automatic outlier detection and power curve analysis, the system continuously refines its measurements without external intervention, eliminating the need for manual calibration while maintaining high precision over time.
Solution Approach 2:
The patent implements a feedback mechanism where measured power data is continuously compared against fitted power curves, and detected deviations are used to adjust and compensate for yaw error measurements. This closed-loop feedback system automatically corrects calibration drift and mechanical errors, achieving high precision without manual intervention.
3Productivity
If traditional yaw control strategy is used without compensation, then the control system is simple, but the productivity deteriorates due to accumulated yaw errors affecting power generation
Solution Approach 1:
The system performs preliminary identification and compensation of yaw error inherent deviations before they significantly impact power generation. By continuously analyzing operational data and detecting outliers, the system proactively corrects measurement errors, preventing accumulated yaw errors from degrading productivity while maintaining relatively simple control architecture.
Data Source
AI summary
Provided is a method of identification and compensation of an inherent deviation of a yaw error of a wind turbine based on a true power curve. The method, based on a wind turbine data acquisition and monitoring control (SCADA) system includes a wind speed, an active power, and a yaw error and so on, runs data in real-time, first pre-processes the data to a certain degree, and then divides a power curve data according to a certain yaw error interval, fits the power curves according to different yaw error intervals through a true power curve fitting flow in connection with an outlier discrimination method, further quantitatively analyzes the different power curves and determines an interval scope of the yaw error inherent deviation value based on an interval determination criterion, and finally compensates the identified inherent deviation value to a yaw error measurement value.