Open AccessData-Dirven Method for Wake Effect Analysis on Nacelle Anemometer
Author(s) -
Bo Jing,
Qian Zheng,
Tianyang Chen,
Yan Pei,
Dahai Kang
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/555/1/012117
Subject(s) - nacelle , anemometer , wake , turbine , wind speed , meteorology , marine engineering , environmental science , wind power , acoustics , aerospace engineering , engineering , physics , electrical engineering
For most wind turbines, blade wakes affect the measurement of nacelle anemometer, result in the inconsistency between nacelle wind speed (NWS) and free stream wind speed, which seriously affects the power forecasting and performance evaluation of wind turbine. This paper proposes a data-driven method to analyse the wake effect on nacelle anemometer. At first, we use Relevance Vector Machine to establish a site calibration model between Lidar wind speed (LWS) and NWS. After that, we can use the calibrated LWS to replace the free stream wind speed, and wake effect on nacelle anemometer can be evaluated by comparing the calibrated LWS and NWS. Then, Wind Turbine Power Curve (WTPC) is applied to make a detail analysis of wake effect on nacelle anemometer. The experimental results show that wake effect accelerates the air velocity behind the impeller. Therefore, WTPC fitted by NWS is “lower” than the real one. However, SCADA system overcorrects the wake effect, thus WTPC fitted by SCADA data is “higher” than the real power curve.