دانلود مقاله ISI انگلیسی شماره 53932
ترجمه فارسی عنوان مقاله

شناسایی پارامتری ماشین القایی دوسو تغذیه

عنوان انگلیسی
Parametric Identification of the Doubly Fed Induction Machine
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
53932 2012 10 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Energy Procedia, Volume 18, 2012, Pages 177–186

ترجمه کلمات کلیدی
ژنراتور بادی؛ ماشین القایی دوسو تغذیه ؛ مدل سازی؛ پارامترهای شناسایی
کلمات کلیدی انگلیسی
wind generator; doubly fed Induction machine; Modeling; parameters Identification
پیش نمایش مقاله
پیش نمایش مقاله  شناسایی پارامتری ماشین القایی دوسو تغذیه

چکیده انگلیسی

Wind Energy is a very promising energy for the future. It is well known that the power delivered by wind turbines directly coupled to the grid is not constant as a result of the wind variability. In the absence of storage systems, a fluctuating power supply produced, can lead to voltage variations in the grid and flicker. Another disadvantage of most induction machines utilized in the wind turbines is that the required reactive power varies with wind speed and time. These problems can make the use of double fed induction generators attractive for wind turbine applications. Doubly-fed induction machines (DFIMs) are beginning to dominate the wind generation market, particularly for the larger sizes of turbine. This work is dedicated to the identification of the parametric double-fed induction machine. We propose a model of the DFIG based on the method of vector space. This model is used to validate the experimental results of identified parameters of the machine. After considering several methods of parameter identification of induction machines, provided with the results of the experiments, we are particularly interested in standardized testing. The proposed approach allows determining the electrical parameters of the machine using conventional methods static and dynamic, mechanical parameters are estimated using a digital channel, following the curve of smoothed experimental slowdown. The identified model parameters are verified by comparing their simulated stator and rotor currents responses against the measured currents. It is again observed that the estimated model responses match the measured responses well.