Screening Methodology of Correlated Wind Turbines for Wind Direction Prediction Based on Yawing Maneuver Data

The accurate prediction of wind direction is an effective way to improve wind energy utilization and extend the life of wind turbine yaw system. The "Measure-Share-Correlate- Predict-Verify" (MSCPV) wind parameter sensing technology based on the turbine network provides a new perspective for wind direction prediction, in which the screening of correlated wind turbines is a key step. This paper proposes a calculation method of wind direction spatial correlation and describes its process in detail. The correlated turbines are selected for the target turbine according to the calculations. The paper first introduces the principle of MSCPV wind prediction and proposes the concept of correlated turbine screening based on yawing correlation. Then, the modeling and calculation method of yawing correlation are analyzed. Case study shows that the screening of spatial correlated turbines based on yawing correlation has better effect than that directly based on wind direction. The prediction accuracy based on different correlated turbines is positively related with the degree of yawing correlation, indicating the proposed screening method is effective.