کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5451131 1513074 2017 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Prediction of I-V characteristics for a PV panel by combining single diode model and explicit analytical model
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
پیش نمایش صفحه اول مقاله
Prediction of I-V characteristics for a PV panel by combining single diode model and explicit analytical model
چکیده انگلیسی
Manufacturers of photovoltaic panels typically only provide electrical parameters under standard reference condition (SRC) that is not sufficient to determine their overall performance. It is important for designers to find a flexible and reliable method to model and accurately predict I-V characteristics under varying operating conditions. This paper proposes a method to predict the I-V characteristics of a PV panel under varying operating conditions by combining the single diode model and explicit analytical model. The method takes temperature and solar irradiance as inputs and produces I-V characteristics under any operating condition as outputs, including the maximum power point, fill-factor, and entire I-V curve. Considering the aging effect, the parameters under the measured reference condition (MRC) are used for calculation instead of the manufacturer data at SRC where the process is as follows: (1) the shape parameters in the explicit analytical model were calculated from measurements at MRC; (2) the physical parameters in the single diode model were identified from the measured data at MRC and used for the prediction; (3) the physical parameters under any operating condition were calculated based on the dependence of the physical parameters on the temperature and solar irradiance; (4) the I-V characteristics were described and analyzed using the explicit analytical model because of its simplicity and explicit expression. Outdoor experiments were performed to validate the proposed method. Our calculated results show reasonable agreement with the experimental results.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Solar Energy - Volume 144, 1 March 2017, Pages 349-355
نویسندگان
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