Title :
Model-based Fault Detection and Isolation for V47/660kW wind turbine
Author :
Asgari, Shadi ; Yazdizadeh, Alireza ; Kazemi, Mohammad G. ; Kamarzarrin, Mehrnoosh
Author_Institution :
Dept. of Electr. Eng., Shahid Beheshti Univ., Tehran, Iran
Abstract :
In this paper, in order to increase the efficiency, to reduce cost and to prevent the failures of wind turbine, which leads to extensive break down, a fault diagnosis system is proposed for V47/660kW wind turbine operated in Manjil wind farm. According to the acquired data of Iran wind turbine industry, common faults of the wind turbine are identified and considered in Fault Detection and Isolation (FDI) system design. Various Faults in different types can be detected and isolated using the indicators of faults, namely residuals, that are derived based on Unknown Input Observer (UIO). Moreover, some thresholds are exploited to evaluate the produced residuals. Simulations are performed in Matlab/Simulink environment to demonstrate the effectiveness of the proposed method using actual parameters derived for turbine model.
Keywords :
fault diagnosis; wind power plants; wind turbines; FDI; Iran wind turbine industry; Manjil wind farm; UIO; fault detection and isolation; fault diagnosis system; fault indicators; model-based fault detection; model-based fault isolation; power 660 kW; unknown input observer; Conferences; Decision support systems; Electrical engineering; Erbium; Fault Detection and Isolation(FDI); Renewable Energy; Unknown Input Observer(U IO); Wind Turbine;
Conference_Titel :
Electrical Engineering (ICEE), 2015 23rd Iranian Conference on
Conference_Location :
Tehran
Print_ISBN :
978-1-4799-1971-0
DOI :
10.1109/IranianCEE.2015.7146470