کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
388467 660926 2011 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Maximum power point tracking (MPPT) system of small wind power generator using RBFNN approach
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Maximum power point tracking (MPPT) system of small wind power generator using RBFNN approach
چکیده انگلیسی

A novel approach of combination of radial basis function neural network (RBFNN) and particle swarm optimization (PSO) is proposed to achieve the maximum power point tracking (MPPT) in this study. The measured data of the small wind generator (250 W), including wind speed, generator speed and output power of wind power generator, are applied to estimate the wind speed and output power by the proposed wind speed ANNwind and power estimation ANNPe-PSO modules, respectively. Using the predicted results by the two modules of Matlab/Simulink, the MPPT point can be obtained by manipulating the generator speeds. The experimental results show that the proposed RBFNN-based approach can increase the maximum output power of the wind power generator even if the wind speed and load varies.


► A 250W wind generator was adopted in the experiment.
► Two modules was proposed to estimate the wind speed and output power.
► Maximum output power of the wind power generator can be increased even if the wind speed and load varies.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 38, Issue 10, 15 September 2011, Pages 12058–12065
نویسندگان
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