首页|Researchers from North China Electric Power University Report Recent Findings in Machine Learning (Real-time Yaw-misalignment Calibration and Field-test Verification of Wind Turbine Via Machine Learning Methods)
Researchers from North China Electric Power University Report Recent Findings in Machine Learning (Real-time Yaw-misalignment Calibration and Field-test Verification of Wind Turbine Via Machine Learning Methods)
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NETL
NSTL
Elsevier
New research on Machine Learning is the subject of a report. According to news reporting originating in Beijing, People’s Republic of China, by NewsRx journalists, research stated, “It has become a general consensus that nacelle-mounted LiDAR can be used to calibrate the yaw misalignment or drive the real-time yaw motions for wind turbines, which would improve the power-generation efficiency. The advantage of LiDAR utilization is that the accuracy of inflow wind measurement would be greatly improved, while its disadvantage is that the cost remains high and the data validity is not sufficiently high.” Funders for this research include National Natural Science Foundation of China (NSFC), Research on the cooperative control technology through the wake redirection of Guodian New Energy Technology Research Institute Co., Ltd..
BeijingPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningNorth China Electric Power University
NETL
NSTL
Elsevier
