Energy–Climate Pre-Screening Of Rural PV Candidate Points In Türkiye: GHI And Model-Derived AC Specific-Yield Rankings and Shortlist Stability

Öz

Global horizontal irradiance (GHI) is useful for broad photovoltaic resource pre-screening, but it does not alone represent plane-of-array irradiance, operating temperature, wind cooling, inverter conversion, and system losses embedded in alternating-current (AC) yield models. This study compares GHI-based and climate-adjusted, model-derived AC specific-yield rankings as an energy–climate pre-screening exercise; it neither identifies investment-ready sites nor independently validates energy yield. One rural candidate point was algorithmically selected in each of Türkiye’s 81 provinces. Hourly NASA POWER inputs for 2001–2025 were processed through a common south-facing Perez–SAPM–PVWatts chain with a fixed 30° tilt and 1 MWp DC capacity. The GHI-only descriptive auxiliary model yielded an adjusted R²=0.940, and adding air temperature, wind, and elevation reduced in-sample RMSE by 50.61%. Pearson and Spearman coefficients were r=0.9697 and ρ=0.9283, respectively; however, the mean absolute rank difference was 6.12 positions, the maximum difference was 27, and the Top-10 replacement rate was 40%. Nevertheless, the mean model-derived AC specific yield of the GHI-selected Top-10 was only 0.70% below that of the AC-selected Top-10. A common-year bootstrap produced Top-10 inclusion frequencies of at least 99.3% for six candidates, whereas leave-one-region-out sensitivity results were heterogeneous. These frequencies describe model-conditional stability under resampling of the observed 2001–2025 meteorological years, not probabilities of future investment success. The findings support GHI for broad pre-screening while indicating that shortlists should be supplemented with climate-adjusted model outputs, ranking uncertainty, and site-specific assessment of grid, land, legal, environmental, geotechnical, access, permitting, and economic conditions.

Anahtar Kelimeler

• Photovoltaic energy
• NASA POWER
• AC specific yield
• Ranking stability
• Energy–climate pre-screening

Destekleyen Kurum

No specific external funding was received for this study.

Etik Beyan

Ethics committee approval is not required for the prepared article because the study does not involve human participants, personal data, or animal experiments. The author declares that there is no conflict of interest with any person or institution.

Teşekkür

NASA POWER, ESA WorldCover, Copernicus DEM, geoBoundaries, and the pvlib community are acknowledged for providing open data and software infrastructure.

Türkiye’de Kırsal GES Aday Noktalarının Enerji–Iklim Ön Taraması: GHI ve Model-Türevi AC Özgül Üretim Sıralamaları Ile Kısa Liste Kararlılığı

Öz

Küresel yatay ışınım (GHI), fotovoltaik kaynak ön taramasında yararlı olmakla birlikte, alternatif akım (AC) üretim modellerinde temsil edilen panel düzlemi ışınımı, çalışma sıcaklığı, rüzgârla soğuma, inverter dönüşümü ve sistem kayıplarını yansıtmaz. Bu çalışma, GHI’ye dayalı ve iklim-düzeltilmiş model-türevi AC özgül üretim sıralamalarını enerji–iklim ön taramasında karşılaştırmaktadır; yatırım yapmaya hazır sahalar belirlememekte ve enerji üretimini bağımsız saha verileriyle doğrulamamaktadır. Türkiye’nin 81 ilinin her birinde algoritmik olarak 1 kırsal aday nokta seçilmiş; 2001–2025 dönemine ait saatlik NASA POWER girdileri, 30° sabit eğimli ve 1 MWp DC gücündeki ortak bir Perez–SAPM–PVWatts zincirinde işlenmiştir. GHI’yi içeren betimsel yardımcı model için ayarlanmış R²=0,940 bulunmuş; hava sıcaklığı, rüzgâr ve yükseltinin eklenmesi örneklem içi RMSE’yi %50,61 azaltmıştır. Pearson ve Spearman katsayıları sırasıyla r=0,9697 ve ρ=0,9283 olmasına karşın, ortalama mutlak sıra farkı 6,12, en büyük fark 27 basamak ve ilk 10 adaylık listedeki üye değişim oranı %40’tır. GHI ile seçilen ilk 10 adayın ortalama model-türevi AC özgül üretimi, AC sıralamasıyla seçilen listenin yalnızca %0,70 altında kalmıştır. Ortak-yıl bootstrap analizi 6 aday için ilk 10’a dâhil edilme sıklığını en az %99,3 olarak verirken, bölgeyi dışarıda bırakan duyarlılık sonuçları heterojen bulunmuştur. Bu sıklıklar, gözlenen 2001–2025 meteorolojik yıllarının yeniden örneklenmesi altında model zincirine koşullu kararlılığı göstermekte olup gelecekteki yatırım başarısı olasılıkları değildir. Bulgular, GHI’nin geniş ölçekli ön taramada kullanılabileceğine; kısa listelerin ise iklim-düzeltilmiş model çıktıları, sıralama belirsizliği ve şebeke, arazi, hukuk, çevre, zemin, erişim, izin ve ekonomi açısından yerel incelemelerle desteklenmesi gerektiğine işaret etmektedir.

Anahtar Kelimeler

• Anahtar kelimeler: Fotovoltaik enerji
• NASA POWER
• AC özgül üretim
• Sıralama kararlılığı
• Enerji–iklim ön taraması

Destekleyen Kurum

Bu çalışma için herhangi bir dış finansman desteği alınmamıştır.

Etik Beyan

Çalışma insan katılımcıları, kişisel verileri veya hayvan deneylerini içermediğinden, hazırlanan makale için etik kurul onayı gerekmemektedir. Yazar, herhangi bir kişi veya kurumla çıkar çatışması olmadığını beyan eder.

Teşekkür

NASA POWER, ESA WorldCover, Copernicus DEM, geoBoundaries ve pvlib topluluğu, açık veri ve yazılım altyapısı sağladıkları için teşekkür ederim.

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