Uzun Kısa Dönemli Bellek Ağına Dayalı Saatlik Güneş Işınımının Gelecek Ay Tahmini

Yıl 2023, , 225 - 232, 30.03.2023

İnayet Özge Aksu

https://doi.org/10.21605/cukurovaumfd.1273795

Cited By: 2

Öz

Günümüzde nüfus artışına ve teknolojinin ilerlemesine paralel olarak ülke yöneticileri açısından kalkınma kaygıları ortaya çıkmaya başlamıştır. Bu nedenle klasik enerji kaynaklarına alternatif çözümler aranmaktadır. Yenilenebilir enerji kaynakları günümüzde önerilen enerji kaynaklarından biridir. Güneş enerjisi de dahil olmak üzere yenilenebilir enerji kaynaklarının popülaritesi her geçen gün artmaktadır. Güneş enerjisi, diğer yenilenebilir enerji kaynaklarından daha hızlı yayılma potansiyeline ve erişilebilirliğine sahiptir. Türkiye genel olarak güneş kuşağı olarak adlandırılan güneş enerjisi potansiyeli yüksek bir bölgede yer aldığından bölgemizde enerji kaynağı olarak güneş enerjisini tercih etmek doğru bir karardır. Bu çalışmada, kısa dönem güneş ışınımı tahmini için Uzun Kısa Süreli Bellek (LSTM) Ağı yöntemi kullanılarak zaman serisi tahmini kullanılmıştır. Sonuçların başarısını ortaya koymak için Yapay Sinir Ağları (YSA) yöntemi ile karşılaştırma yapılmıştır. Son olarak güneş ışınımının tahmin sonuçları istatistiksel testlerle karşılaştırılmış ve hata analizleri sayısal olarak verilmiştir.

Anahtar Kelimeler

Uzun kısa süreli hafıza, Güneş ışınımı, Zaman serisi tahmini, Güneş enerjisi

Next-Month Prediction of Hourly Solar Irradiance based on Long Short-Term Memory Network

Öz

Today, in parallel with the population growth and the advancement of technology, development concerns have started to arise in terms of country administrators. Therefore, alternative solutions to classical energy sources are sought. Renewable energy sources are one of the preferred energy sources today. The popularity of renewable energy sources, including solar energy, is increasing day by day. Solar energy has the potential and accessibility to spread faster than other renewable energy sources. Since Türkiye is located in a region with a high potential in terms of solar energy, which is generally called the sun belt, it is a right decision to prefer solar energy as an energy source in our region. In this study, time series prediction using Long Short-Term Memory (LSTM) Network method is used for short-term solar irradiance estimation. In order to demonstrate the success of the results, a comparison was made with the Artificial Neural Network (ANN) method. Finally, prediction results of solar irradiance were compared with statistical tests and error analyzes were given in numerically.

Anahtar Kelimeler

Long short-term memory, Solar irradiance, Time series prediction, Solar energy

Kaynakça

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