
Sensitivity analysis for evaluation of the effect of sensors error on the wind turbine variables using Monte Carlo simulation
Author(s) -
Biazar Dariush,
Khaloozadeh Hamid,
Siahi Mehdi
Publication year - 2022
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/rpg2.12468
Subject(s) - turbine , monte carlo method , sensitivity (control systems) , wind power , wind speed , power (physics) , computer science , control theory (sociology) , simulation , engineering , statistics , mathematics , meteorology , aerospace engineering , electronic engineering , physics , electrical engineering , control (management) , quantum mechanics , artificial intelligence
The dynamics of the wind turbine behaviour and identifying the factors that change turbine performance are very complex and challenging. Quantifying the impact of these factors on improving the wind turbine performance is invaluable. Many attempts have been made to describe the behaviour of the wind turbine variables. Sensitivity analysis and Monte Carlo simulation are methods to identify important parameters affecting modelbehavior. Here, with these methods, the authors investigate the effect of error in sensors on output power and measured variables of the wind turbine in partial load region and full load region. Then, using the importance factor, the effect of error in the different sensors on the output power of the wind turbine is ranked in the two operating regions, so that, in practice, the sensors that have the greatest impact on the output power are designed as redundant.