کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10392438 | 885263 | 2005 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Prediction of the daily performance of solar collectors
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
جریان سیال و فرایندهای انتقال
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Prediction of the daily performance of solar collectors Prediction of the daily performance of solar collectors](/preview/png/10392438.png)
چکیده انگلیسی
This paper presents the application of an online identification neural technique to the prediction of the in-situ daily performance of solar collectors. First, it is shown that the use of the Laplace transform helps to find the order of an approximated model; the input of the studied system being the solar radiation. Then it is shown that a Neural Network Output Error (NNOE) model can be accurate using the right size of the regression vector; the learning database consisting of the data obtained during a half day. Finally, it is shown that a Multiple Inputs Single Output (MISO) NNOE model can be accurate; the inputs being the solar radiation and the thermal heat loss conductance that varies with the wind velocity. In any case the differential between the actual value of the daily energy and the value computed by a neural model (SISO-Single Input Single Output) or MISO) is less than 0.5%.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Communications in Heat and Mass Transfer - Volume 32, Issue 5, April 2005, Pages 603-611
Journal: International Communications in Heat and Mass Transfer - Volume 32, Issue 5, April 2005, Pages 603-611
نویسندگان
S. Lecoeuche, S. Lalot,