Şanlıurfa ilinde yatay yüzeye gelen anlık global güneş ışınımının modellenmesi

Karakaya, Hakan; Avcı, Ali; Ercan, Umut; Kallioğlu, Mehmet Ali

doi:10.24012/dumf.430522

Cited by 4 publications

(3 citation statements)

References 5 publications

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“…Solar energy constitutes the basis of life on earth and is an abundant and clean resource. The sun is a natural fusion reactor that emits energy in the form of electromagnetic radiation into space (Karakaya et al, 2019). The basic input in solar energy systems is the amount of radiation from the sun.…”

Section: Introductionmentioning

confidence: 99%

“…This model had R 2 of 0.887, RMSE of 2.046, MBE of -0.080 and MPE of -2.481. Karakaya et al (2019) statistically compared the data of global solar radiation prediction models using 5 models, namely Veeren and Kumar, Cheegar and Chibani, Ampratwum and Dorvlo, Bahel, Luhanga and Andringa, in this study they conducted in the Şanlıurfa region. They reported that the closest value to the measurement results was Cheegar and Chibani Model with a value of 0.9912 R 2 .…”

Section: Introductionmentioning

confidence: 99%

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Empirical Modelling of Global Solar Radiation in Hatay (Turkey) Province

Külcü

Ersan

2021

Tekirdağ Ziraat Fakültesi Dergisi

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There are many models used in global solar radiation prediction. However, these prediction models vary according to the climate and geographic characteristics of the region involved. When the prediction model determined for a region is used in a different region, the prediction model may not work. In order to gain absolute and stable results from these models, the studies should be either custom-made or tested.In this study, 7 different models were examined, comparison charts were created and statistical interpretations were made in order to determine the monthly average global solar radiation coming to the horizontal plane taking into account the climatic characteristics of Hatay province, located in the eastern 39.92º latitude and northern longitude 36.16º, covering an area of 5403 km, and has a humid climate with a value of 41.3, based on De Martonne-Gottmann's drought index and 50.6 based on Erinç's rainfall efficiency index.Under the scope of this study, the most ideal global solar radiation prediction model was selected by making a statistical evaluation according to the parameters of determination coefficient (R²), mean percentage error (MPE), mean deviation error (MBE), root mean square error (RMSE).A general assessment of the graphics and statistical parameters of the predictions obtained by using the models and the measured data has indicated Model 4 as the most successful model by an RMSE value of 0.17306, and the least successful model was Model 3 by an RMSE value of 2.11851.When the models are interpreted according to the determination coefficient, it has been observed that other models are generally successful. However, this situation does not coincide with the comparison charts of the predicted and measured data. For this reason, it was seen that the determination coefficient was not sufficient in the statistical evaluation of the prediction models. In the interpretation of the models, it was observed that the interpretation of root mean square error, mean percentage error and mean deviation error values together gave more accurate results.In conclusion, it has been suggested that Model 4 should be preferred for the global solar radiation forecast of Hatay province.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Empirical Modelling of Global Solar Radiation in Hatay (Turkey) Province

Külcü

Ersan

2021

Tekirdağ Ziraat Fakültesi Dergisi

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“…Another study used empirical models is done in Şanlıurfa which is located in South-East in Turkey. 5 different models has applied and one of them has selected based on statistical evaluation metrics [8]. Empirical correlations were developed to build models for calculating monthly average daily solar radiation on the horizontal surface in Isparta, Turkey.…”

Section: Introductionmentioning

confidence: 99%

A comparison of machine learning algorithms for forecasting solar irradiance in Eskişehir, Turkey

AYKO¹,

Keser²

2021

International Journal of Applied Mathematics Electronics and Computers

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This work compares the efficiency of 45 different machine learning (ML) algorithms to provide a comprehensive and most accurate model for global horizontal solar irradiance (GHSI) prediction in Eskişehir, Turkey. The dataset is provided by NASA Prediction of Worldwide Energy Resource (POWER) as satellite data that involves some characteristic weather condition variables such as temperature, precipitation, humidity etc. over 35 years. Some ML algorithms such as Extra Trees, LightGBM, HistGB, Random Forest (RF), Bagging and Decision Tree exhibit better performance among the others with commonly used statistical evaluation metrics in literature such as coefficient of determination (R²), root mean squared error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE). In addition, Extra Tress regression slightly outperformed the rest of ensemble learning methods with R² of 0.99, RMSE of 8.05, MAE of 5.67, MAPE of 4%. Finally, the outcome demonstrates that the ML algorithms belonging to ensemble learning family achieved great results in GHSI prediction at specific location.

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Türkiye’nin Güneş Enerjisi Potansiyeli ve İskenderun için Örnek Üretim Projeksiyonu

Kumruoğlu

ATEŞ

2022

Çukurova Üniversitesi Mühendislik Fakültesi Dergisi

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Kişi başına düşen enerji tüketiminin artmasıyla beraber, arz-talep dengesinin sağlıklı bir şekilde devam ettirebilmesi için enerji santrallerine olan yatırımlar devam etmektedir. Oluşan temiz enerji bilinci, çevreci ve uzun ömürlü Güneş Enerji Santrallerine (GES) olan yatırımları gün geçtikçe artırmaktadır. Yaşanan Kovid-19 pandemisi süresince, enerji tüketimlerinin çoğu yenilenebilir santrallerinden karşılanmış ve GES’den üretilen elektrik, büyük paya sahip olmuştur. Yapılan bu çalışmada, özellikle Türkçe kaynaklar içerisinde GES’in hammadde kaynağı olan güneş ışınımları ve ülkemizin güneş potansiyeline dair yapılan araştırmalar incelenmiştir. Güneş potansiyelinin, üretim potansiyeline dönüştürülmesinde oluşan kayıplar ve üretim potansiyelin artırılmasına yönelik konular araştırılmıştır. Ayrıca İskenderun Teknik Üniversitesi Kampüsü içinde bulunan bina çatısına 60 kWp GES tasarlanarak, PVGIS, PVsyst, SMA Web Desing yazılımları ile tahmini elektrik üretimleri hesaplanmıştır.

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Şanlıurfa ilinde yatay yüzeye gelen anlık global güneş ışınımının modellenmesi

Cited by 4 publications

References 5 publications

Empirical Modelling of Global Solar Radiation in Hatay (Turkey) Province

Empirical Modelling of Global Solar Radiation in Hatay (Turkey) Province

A comparison of machine learning algorithms for forecasting solar irradiance in Eskişehir, Turkey

Türkiye’nin Güneş Enerjisi Potansiyeli ve İskenderun için Örnek Üretim Projeksiyonu

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