Photovoltaic Panel Efficiency Estimation with Artificial Neural Networks: Samples of Adiyaman, Malatya, and Sanliurfa
المؤلفون المشاركون
Mamiş, Mehmet Salih
Icel, Yasin
Bugutekin, Abdulcelil
Gursoy, Mehmet Ismail
المصدر
International Journal of Photoenergy
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-04-10
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
The amount of electric energy produced by photovoltaic panels depends on air temperature, humidity rate, wind velocity, photovoltaic module temperature, and particularly solar radiation.
Being aware of the behaviour patterns of the panels to be used in project and planning works regarding photovoltaic applications will set forth a realistic expense form; therefore, erroneous investments will be avoided, and the country budget will benefit from added value.
The power ratings obtained from the photovoltaic panels and the environmental factors were measured and recorded for a year by the measurement stations established in three diverse regions (Adiyaman-Malatya-Sanliurfa).
In the developed artificial neural network models, the estimation accuracy was 99.94%.
Furthermore, by taking the data of the General Directorate of Meteorology as a reference, models of artificial neural networks were developed using the data from Adiyaman province for training; by using Malatya and Sanliurfa as test data, 99.57% estimation accuracy was achieved.
With the artificial neural network models developed as a result of the study, the energy efficiency for the photovoltaic energy systems desired to be established by using meteorological parameters such as temperature, humidity, wind, and solar radiation of various regions anywhere in the world can be estimated with high accuracy.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Icel, Yasin& Mamiş, Mehmet Salih& Bugutekin, Abdulcelil& Gursoy, Mehmet Ismail. 2019. Photovoltaic Panel Efficiency Estimation with Artificial Neural Networks: Samples of Adiyaman, Malatya, and Sanliurfa. International Journal of Photoenergy،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1167295
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Icel, Yasin…[et al.]. Photovoltaic Panel Efficiency Estimation with Artificial Neural Networks: Samples of Adiyaman, Malatya, and Sanliurfa. International Journal of Photoenergy No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1167295
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Icel, Yasin& Mamiş, Mehmet Salih& Bugutekin, Abdulcelil& Gursoy, Mehmet Ismail. Photovoltaic Panel Efficiency Estimation with Artificial Neural Networks: Samples of Adiyaman, Malatya, and Sanliurfa. International Journal of Photoenergy. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1167295
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1167295
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر