Investigation of Near Shading Losses in Photovoltaic Systems with PVsyst Software
Öz
Anahtar Kelimeler
Kaynakça
- [1] I. Kayri and M. T. Gencoglu, "Predicting power production from a photovoltaic panel through artificial neural networks using atmospheric indicators," Neural Comput. Appl., vol. 31, no. 8, pp. 3573–3586, 2019.
- [2] A. Korfiati et al., "Estimation of the global solar energy potential and photovoltaic cost with the use of open data," Int J Sustain Energy Plan Manag, vol. 9, pp. 17–30, 2016.
- [3] E. Dupont, R. Koppelaar, and H. Jeanmart, "Global available solar energy under physical and energy return on investment constraints," Appl. Energy, vol. 257, no. 113968, p. 113968, 2020.
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- [6] İ. Kayri, M. T. Gençoğlu, and M. Kayri, "Batman İli Güneş Enerjisi Potansiyelinin Belirlenmesine Yönelik Deneysel Bir Çalışma," in 1st International Engineering and Technology Symposium (1st IETS), Batman, Türkiye, May 03-05, 2018, pp. 646–654.
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Ayrıntılar
Birincil Dil
İngilizce
Konular
Elektrik Mühendisliği (Diğer)
Bölüm
Araştırma Makalesi
Yazarlar
İsmail Kayri
*
0000-0002-4973-641X
Türkiye
Erken Görünüm Tarihi
23 Mart 2024
Yayımlanma Tarihi
1 Mart 2024
Gönderilme Tarihi
11 Ocak 2024
Kabul Tarihi
25 Ocak 2024
Yayımlandığı Sayı
Yıl 2024 Cilt: 12 Sayı: 1
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Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi
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