کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6765027 1431587 2018 32 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Comparing Mamdani Sugeno fuzzy logic and RBF ANN network for PV fault detection
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
پیش نمایش صفحه اول مقاله
Comparing Mamdani Sugeno fuzzy logic and RBF ANN network for PV fault detection
چکیده انگلیسی
The obtained results indicate that the fault detection algorithm can detect and locate accurately different types of faults such as, faulty PV module, two faulty PV modules and partial shading conditions affecting the PV system. In order to achieve high rate of detection accuracy, four various ANN networks have been tested. The maximum detection accuracy is equal to 92.1%. Furthermore, both examined fuzzy logic systems show approximately the same output during the experiments. However, there are slightly difference in developing each type of the fuzzy systems such as the output membership functions and the rules applied for detecting the type of the fault occurring in the PV plant.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Renewable Energy - Volume 117, March 2018, Pages 257-274
نویسندگان
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