Estimating Global Solar Radiation with Multiple Meteorological Predictors for Abu Dhabi and Al Ain, UAE

2014 ◽  
pp. 623-632
Author(s):  
Jamal Hassan
Keyword(s):  
Solar Radiation ◽  
Global Solar Radiation ◽  
Abu Dhabi ◽  
Al Ain

scholarly journals Prediction of Global Solar Radiation in Abu Dhabi

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Ali Assi ◽  
Mohammed Jama ◽  
Maitha Al-Shamisi
Keyword(s):  
Solar Radiation ◽  
Goodness Of Fit ◽  
Global Radiation ◽  
Quadratic Function ◽  
Global Solar Radiation ◽  
Abu Dhabi ◽  
Percentage Error ◽  
Third Order ◽  
Al Ain ◽  
The City

Mathematical expressions have been employed to estimate global solar radiation on horizontal from relative sunshine duration for two weather stations in the United Arab Emirates (UAE), which are Abu Dhabi and Al Ain. These expressions include the original Angstrom-Prescott regression function (linear), quadratic function, third-order function, single-term exponential function, power function, logarithmic, and linear-logarithmic function. The predicted values were compared to the measured values using number of statistical methods to validate the goodness of the fits, such as residual analysis and goodness of fit statistics. All the used mathematical models performed generally well in both cities of Abu Dhabi and Al Ain, with all values of the coefficient of determination (R2) higher than 75%. Specifically, the linear Angstrom-Prescott model estimated the average monthly global radiation on horizontal best for the city of Abu Dhabi, providing the second lowest mean absolute percentage error (MAPE) of 1.89% and the highest value of R2, which is approximately 94%, while the third-order model proved to be the best estimator for the city of Al Ain, providing the lowest MAPE value (3.06%) and a corresponding R2 of 83%.

scholarly journals Time-Series Regression Model for Prediction of Mean Daily Global Solar Radiation in Al-Ain, UAE

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Hassan A. N. Hejase ◽  
Ali H. Assi
Keyword(s):  
Time Series ◽  
Solar Radiation ◽  
Global Solar Radiation ◽  
Bias Error ◽  
Time Series Regression ◽  
Weather Model ◽  
Al Ain ◽  
Using Data ◽  
Long Term Prediction

The availability of short-term forecast weather model for a particular country or region is essential for operation planning of energy systems. This paper presents the first step by a group of researchers at UAE University to establish a weather model for the UAE using the weather data for at least 10 years and employing various models such as classical empirical models, artificial neural network (ANN) models, and time-series regression models with autoregressive integrated moving-average (ARIMA). This work uses time-series regression with ARIMA modeling to establish a model for the mean daily and monthly global solar radiation (GSR) for the city of Al-Ain, United Arab Emirates. Time-series analysis of solar radiation has shown to yield accurate average long-term prediction performance of solar radiation in Al-Ain. The model was built using data for 10 years (1995–2004) and was validated using data of three years (2005–2007), yielding deterministic coefficients (R2) of 92.6% and 99.98% for mean daily and monthly GSR data, respectively. The low corresponding values of mean bias error (MBE), mean absolute bias error (MABE), mean absolute percentage error (MAPE), and root-mean-square error (RMSE) confirm the adequacy of the obtained model for long-term prediction of GSR data in Al-Ain, UAE.

Estimation of Global Solar Radiation Using Artificial Neural Networks in Abu Dhabi City, United Arab Emirates

2013 ◽  
Vol 136 (2) ◽  
Author(s):  
Maitha Al-Shamisi ◽  
Ali Assi ◽  
Hassan Hejase
Keyword(s):  
Solar Radiation ◽  
United Arab Emirates ◽  
Meteorological Data ◽  
Geographical Location ◽  
Global Solar Radiation ◽  
Abu Dhabi ◽  
Accurate Estimation ◽  
Data Set ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

The geographical location (Latitude: 24 deg 28′ N and Longitude: 54 deg 22′ E) of Abu Dhabi city in the United Arab Emirates (UAE) favors the development and utilization of solar energy. This paper presents an artificial neural network (ANN) approach for the estimation of monthly mean global solar radiation (GSR) on a horizontal surface in Abu Dhabi. The ANN models are presented and implemented on a 16-yr measured meteorological data set for Abu Dhabi comprising the maximum daily temperature, mean daily wind speed, mean daily sunshine hours, and mean daily relative humidity between 1993 and 2008. The meteorological data between 1993 and 2003 are used for training the ANN and data between 2004 and 2008 are used for testing the estimated values. Multilayer perceptron (MLP) and radial basis function (RBF) are used as ANN learning algorithms. The results attest to the capability of ANN techniques and their ability to produce accurate estimation models.

scholarly journals Prediction of Global Solar Radiation from Sunrise Duration Using Regression Functions

2021 ◽  
Author(s):  
A. Haj Ismail ◽  
Keyword(s):  
Solar Radiation ◽  
United Arab Emirates ◽  
Theoretical Models ◽  
Global Solar Radiation ◽  
Abu Dhabi ◽  
Coefficient Of Determination ◽  
Sunshine Hours ◽  
The Mean ◽  
Statistical Indicators ◽  
Good Agreement

The paper estimates the global solar radiation in Dubai and Abu Dhabi meteorological stations in the United Arab Emirates. Theoretical models based on Angstrom-Prescott have been applied on data of sunshine hours for the period from 2010 to 2019. The models are developed using 2010 - 2018 data and validated by comparing to the 2019 data. Theoretical solar radiation estimates the maximum of global solar radiation to be in June for both stations, which is in good agreement with the actual data. The performance of the model is tested using statistical indicators such as the coefficient of determination R2 and the Mean Root Square RMSE. The results show that the models were effective enough to describe the global solar radiation with overall R2 of 0.8874 and 0.8706, RMSE of 0.0258 and 0.0241, MBE of 0.0412 and 0.0376, and MPE of 0.2371 and 0.2318, for Abu Dhabi and Dubai meteorological stations, respectively.

Global solar radiation: Multiple on-site assessments in Abu Dhabi, UAE

2010 ◽  
Vol 35 (7) ◽  
pp. 1596-1601 ◽  
Author(s):  
Lana El Chaar ◽  
Lisa A. Lamont
Keyword(s):  
Solar Radiation ◽  
Global Solar Radiation ◽  
Abu Dhabi

Analysis of Spatial Smoothing Effect of Short-term Fluctuation of Global Solar Radiation based on the Data Including Quantization Error

2011 ◽  
Vol 131 (5) ◽  
pp. 413-420 ◽  
Author(s):  
Yosuke Ue ◽  
Ryoichi Hara ◽  
Hiroyuki Kita ◽  
Yutaka Saito ◽  
Katsuyuki Takitani ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Global Solar Radiation ◽  
Quantization Error ◽  
Smoothing Effect ◽  
Spatial Smoothing ◽  
Short Term ◽  
Term Fluctuation
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