Open AccessStudy and Application of Wind Turbine Power Loss Assessment based on GD-BIN Algorithm
Author(s) -
Yangyan Zhan,
Minqiang Zhou,
Danyuan Ren
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/782/3/032075
Subject(s) - bin , wind power , turbine , power (physics) , algorithm , gaussian , moment (physics) , production (economics) , computer science , unit (ring theory) , mathematical optimization , mathematics , engineering , electrical engineering , mechanical engineering , physics , mathematics education , quantum mechanics , classical mechanics , economics , macroeconomics
In order to accurately assess the lost production of each wind turbine, a fusion method, which is the combination of Gaussian Distribution and bins of method (GD-BIN), was established. Firstly, Complete the first cleaning of operation data according to the operation characteristics and status logs of the unit. Further, GD-BIN algorithm is employed to establish the Wind Power Curve Model (WPCM), which can reflect the real performance of each unit. Thus, the operation data of the unit is delivered to WPCM to calculate theoretical power and lost power at each statistical moment. To verify the accuracy, it is applied in a wind farm in Northeast China and is compared to the other three current methods in the industry. Result shows that the proposed algorithm could effectively estimate lost production with a high accuracy.