Photovoltaic Nonlinear Characteristics Se—Out for Maximum Power Point Tracking based on Neural Network Algorithm

توجه : به همراه فایل word این محصول فایل پاورپوینت (PowerPoint) و اسلاید های آن به صورت هدیه ارائه خواهد شد

 Photovoltaic Nonlinear Characteristics Se—Out for Maximum Power Point Tracking based on Neural Network Algorithm دارای ۱۸ صفحه می باشد و دارای تنظیمات در microsoft word می باشد و آماده پرینت یا چاپ است

فایل ورد Photovoltaic Nonlinear Characteristics Se—Out for Maximum Power Point Tracking based on Neural Network Algorithm  کاملا فرمت بندی و تنظیم شده در استاندارد دانشگاه  و مراکز دولتی می باشد.

توجه : در صورت  مشاهده  بهم ریختگی احتمالی در متون زیر ،دلیل ان کپی کردن این مطالب از داخل فایل ورد می باشد و در فایل اصلی Photovoltaic Nonlinear Characteristics Se—Out for Maximum Power Point Tracking based on Neural Network Algorithm،به هیچ وجه بهم ریختگی وجود ندارد

بخشی از متن Photovoltaic Nonlinear Characteristics Se—Out for Maximum Power Point Tracking based on Neural Network Algorithm :

تعداد صفحات :۱۸

چکیده مقاله:

MPPT algorithm are necessary because PV arrays have a non-linear voltage-current characteristic with a unique point where the power produces is maximum. In this paper we present a PV generator composed by four PV panel kaneka (60Watt) placed in series, and a neural network model developed by the authors. The aim of this study focuses on the application of the artificial neural network to extract the maximum power point of a photovoltaic generator the feeds a motor –pump group unit through a PWM inverter installed in the laboratory. The output of the ANN is the optimal voltage Vopt which is compared to the PV generator Vpv, then passed through an integrator to extract the stator frequency fs that are given to the PWM control of the DC-AC inverter to find out the sinusoidal reference voltage and the sampled wave. The training of the ANN is done and the whole technique is being simulated and studied using MATLAB software.