Empirical models for estimating the daily and monthly global solar radiation for Mediterranean and Central Anatolia region of Turkey

Üstün, İsmail; Karakuş, Cuma; Yağlı, Hüseyin

doi:10.1504/ijgw.2020.106597

Cited by 24 publications

(8 citation statements)

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“…Güneş enerjisi, en yüksek potansiyele sahip yenilenebilir enerji türüdür [9][10]. Dünyanın yenilenebilir enerji ihtiyacının çoğunluğu güneş tarafından sağlanmaktadır [11].…”

Section: Güneş Enerjisine Genel Bir Bakışunclassified

Gaziantep Bölgesi İçin Güneş Enerjisinden Elektrik Üretiminde Kurulacak Panellerin Optimum Eğim Açılarının Belirlenmesi

Yağlı¹,

Koç²

2020

European Journal of Science and Technology

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Öz Dünyada ilerleyen teknolojiye paralel olarak enerjiye duyulan ihtiyaçta giderek artmaktadır. Güneş enerjisi, yenilenebilir olması ve çevreyi tehdit eden unsurları minimum seviyelere çekmesi bakımından enerji üretiminde ön plana çıkmaktadır. Güneş enerji sistemi kurulurken ortam koşulları büyük bir önem teşkil etmektedir. Bu çalışmanın amacı transpozisyon faktörü yardımıyla, kurulacak olan güneş panellerinin maksimum kapasitede enerji üretebilmeleri panellerin optimum açılarının belirlenmesidir. Optimum açının belirlenmesinde yapılmış olan önceki literatür çalışmalarında realiteye daha yakın sonuçlar verdiği görülen Perez transpozisyon modeli yardımıyla elde edilen transpozisyon faktörleri kullanılmıştır. Elde edilen transpozisyon faktörleri göz önünde bulundurulduğu zaman optimum açı değeri 31° olarak elde edilmiştir. PVSyst programı kullanılarak açılara göre üretim değerleri karşılaştırılmış ve 30° panel eğim açısında üretilen enerji miktarının 31° panel eğim açısına göre farkının kayda değer olmadığı belirlenmiştir. Son olarak üretim maliyetini düşürmek için, yerleştirilecek olan panellerin 30° açıda yerleştirilebileceğine karar verilmiştir.

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Section: Güneş Enerjisine Genel Bir Bakışunclassified

Gaziantep Bölgesi İçin Güneş Enerjisinden Elektrik Üretiminde Kurulacak Panellerin Optimum Eğim Açılarının Belirlenmesi

Yağlı¹,

Koç²

2020

European Journal of Science and Technology

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“…The empirical model has become one of the most widely used ones to predict daily global solar radiation due to its relatively high computational accuracy and efficient computational capacity. Hence, it is particularly suitable for large-scale solar radiation calculation tasks (Ustun et al, 2020). Empirical models can be divided into four types according to their input parameters, which include models based on sunshine, temperature, cloud cover, and other meteorological parameters (Mohammadi et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

The applicability of sunshine-based global solar radiation models modified with meteorological factors for different climate zones of China

et al. 2023

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With the development of renewable energy, the exploitation and utilization of solar energy resources also need continuous progress, but solar radiation data shortage has become a serious concern. A method for estimating global solar radiation has been developed to address this issue. The sunshine-based model is currently the most widely used model due to its high calculation accuracy and few input parameters. This paper will first review 13 subcategories (8 categories in total) of the global solar radiation prediction model based on sunshine. Subsequently, the astronomical factors were introduced to modify empirical coefficients, and 8 new categories of models based on sunshine rate were introduced. The radiation data from 83 meteorological stations in China was used to train and validate the model, and the performance of the model was evaluated by using evaluation indicators, such as coefficient of determination (R2), root mean square error (RMSE), mean absolute bias error (MABE), mean bias error (MBE), and global performance index (GPI). The results show that the R2 value of the unmodified empirical model is in a range of 0.82–0.99, and the RMSE value is in a range of 0.018–3.09. In contrast, with the introduction of the astronomical factor, the model accuracy improves significantly, and the modified power function model (N3) gains its best performance. The R2 of model N3 is in a range of 0.86–0.99, and the RMSE value is in a range of 0.018–2.62. The R2 increases by 0.49%, while the RMSE value 6.44%. Above all, it does not require the input of other meteorological parameters for predicting the value of global solar radiation.

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“…Further, various meteorological factors, such as precipitation and relative humidity, have been applied to improve the model accuracy ( 29 – 33 ). In addition to empirical models, machine learning models have been used for global solar radiation prediction to address non-linear and multidimensional relationships between solar radiation and meteorological factors in noisy environments ( 34 – 38 ).…”

Section: Introductionmentioning

confidence: 99%

Estimation of Daily Ground-Received Global Solar Radiation Using Air Pollutant Data

Zhang

Zhang²,

Cui

et al. 2022

Front. Public Health

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Ground-received solar radiation is affected by several meteorological and air pollution factors. Previous studies have mainly focused on the effects of meteorological factors on solar radiation, but research on the influence of air pollutants is limited. Therefore, this study aimed to analyse the effects of air pollution characteristics on solar radiation. Meteorological data, air quality index (AQI) data, and data on the concentrations of six air pollutants (O3, CO, SO2, PM10, PM2.5, and NO2) in nine cities in China were considered for analysis. A city model (model-C) based on the data of each city and a unified model (model-U) based on national data were established, and the key pollutants under these conditions were identified. Correlation analysis was performed between each pollutant and the daily global solar radiation. The correlation between O3 and daily global solar radiation was the highest (r = 0.575), while that between SO2 and daily global solar radiation was the lowest. Further, AQI and solar radiation were negatively correlated, while some pollution components (e.g., O3) were positively correlated with the daily global solar radiation. Different key pollutants affected the solar radiation in each city. In Shenyang and Guangzhou, the driving effect of particles on the daily global solar radiation was stronger than that of pollutants. However, there were no key pollutants that affect solar radiation in Shanghai. Furthermore, the prediction performance of model-U was not as good as that of model-C. The model-U showed a good performance for Urumqi (R2 = 0.803), while the difference between the two models was not particularly significant in other areas. This study provides significant insights to improve the accuracy of regional solar radiation prediction and fill the gap regarding the absence of long-term solar radiation monitoring data in some areas.

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Empirical models for estimating the daily and monthly global solar radiation for Mediterranean and Central Anatolia region of Turkey

Cited by 24 publications

References 0 publications

Gaziantep Bölgesi İçin Güneş Enerjisinden Elektrik Üretiminde Kurulacak Panellerin Optimum Eğim Açılarının Belirlenmesi

Gaziantep Bölgesi İçin Güneş Enerjisinden Elektrik Üretiminde Kurulacak Panellerin Optimum Eğim Açılarının Belirlenmesi

The applicability of sunshine-based global solar radiation models modified with meteorological factors for different climate zones of China

Estimation of Daily Ground-Received Global Solar Radiation Using Air Pollutant Data

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