Abstract
Solar radiation is considered the main renewable energy source which reshapes the global sustainability plan for future development. Due to the lack of solar radiation measurements, this work investigates the performance of several temperature-based hybrid solar radiation models combining the parametric, statistical and satellite data approaches to estimate the global solar radiation on a horizontal surface. Over 35 years of meteorological data in the new location, Arar City, KSA (Latitude 30°96′ N and longitude 41°05′ E) are employed to establish and validate the models. These models are validated using two datasets with different averaging time spans to investigate the accuracy and reliability of different models as forecasting tools for the solar radiation. The mostly common statistical indicators are calculated to identify the most accurate model. The results show that Model (1) has the best performance among all models with high reliability as a solar radiation forecasting tool in this new location. This model is also validated against the widely-used datasets, namely NASA, On-Site measurements and PVGIS-SARAH data. The model shows excellent values for statistical indicators with high values of coefficient of determination, R2 > 0.955, presenting the best performance regardless of the time span of the validation datasets.
Highlights
Publisher’s Note: MDPI stays neutralDue to the expanding consumption of fossil fuels because of the population increase and economic activities along with instability of oil prices and the contamination of the air pollution and greenhouse gas emissions, the interest in sustainable sources of energy, solar energy, is continuously increasing [1,2,3,4,5]
To check the applicability and the accuracy of the selected models in predicting monthly average daily global solar radiation values, a long-term of recorded data of daily global solar radiation are employed. This data of global solar radiation is divided into two sets and averaged to obtain the values of monthly average
The first one is the average data of three years for the monthly-average-daily-global solar radiation, from January 2017 to December 2019, and the second validation set is the data of one year, 2019 for the monthly-average-dailyglobal solar radiation
Summary
Due to the expanding consumption of fossil fuels because of the population increase and economic activities along with instability of oil prices and the contamination of the air pollution and greenhouse gas emissions, the interest in sustainable sources of energy, solar energy, is continuously increasing [1,2,3,4,5]. The aim of this work is to study the performance of four different empirical solar radiation models based on ambient temperature data to predict the monthly average daily global solar radiation values on a horizontal surface. These four temperature-based solar radiation models are selected due to their high accuracy and good performance based on the literature, [28]. To investigate the stability and reliability of these models as temperature-based forecasting tools for the global solar radiation providing accurate predictions of solar radiation values for engineers and designers, which can be employed in the design and evaluation of performance for different solar applications in this region. A comparison between the accuracy of the current work and the previous studies are achieved showing good enhancement by the current work
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