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.

scholarly journals Time Series and Empirical Orthogonal Transformation Using Meteorological Parameters across the Climatic Zones in Nigeria

2019 ◽  
pp. 257-272
Author(s):  
D. O. Akpootu ◽  
B. I. Tijjani ◽  
U. M. Gana
Keyword(s):  
Time Series ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Meteorological Parameters ◽  
Orthogonal Transformation ◽  
Global Solar Radiation ◽  
Climatic Zones ◽  
Sunshine Hours ◽  
Dry Seasons ◽  
The Mean

Time series and empirical orthogonal transformation analysis was carried out for four (4) selected tropical sites, which are situated across the four different climatic zones, viz. Sahelian, Midland, Guinea savannah and Coastal region in Nigeria using measured monthly average daily global solar radiation, maximum and minimum temperatures, sunshine hours, rainfall, wind speed, cloud cover and relative humidity meteorological data during the period of thirty one years (1980-2010). Seasonal Auto Regressive Integrated Moving Average (ARIMA) models were developed along with their respective statistical indicators of coefficient of determination (R2), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE). The results indicated that the models were found suitable for one step ahead global solar radiation forecast for the studied locations. Furthermore, the results of the time series analysis revealed that the model type for all the meteorological parameters show a combination of simple seasonal with one or more of either ARIMA, winter’s additive and winter’s multiplicative with the level been more significant as compared to the trend and seasonal variations for the exponential smoothing model parameters in all the locations. The results of the correlation matrix revealed that the global solar radiation is more correlated to the mean temperature except for Akure where it is more correlated to the sunshine hours; the mean temperature is more correlated to the global solar radiation; the rainfall is more correlated to the relative humidity and the relative humidity is more correlated to the rainfall in all the locations. The results of the component matrix revealed that three seasons are identified in Nguru located in the Sahelian region namely, the rainy, the cool dry (harmattan) and the hot dry seasons while in Zaria, Makurdi and Akure located in the Midland, Guinea savannah and Coastal zones two distinct seasons are identified namely, the rainy and dry seasons.

scholarly journals Performance Evaluation of Temperature-Based Global Solar Radiation Models—Case Study: Arar City, KSA

2021 ◽  
Vol 14 (1) ◽  
pp. 35
Author(s):  
Nejib Ghazouani ◽  
Abdulhakim Bawadekji ◽  
Alaa A. El-Bary ◽  
Mahmoud M. Elewa ◽  
Nidhal Becheikh ◽  
...  
Keyword(s):  
Solar Radiation ◽  
High Reliability ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Coefficient Of Determination ◽  
Averaging Time ◽  
Statistical Indicators ◽  
New Location ◽  
Radiation Measurements

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.

scholarly journals Solar radiation forecasting in nigeria based on hybrid PSO-ANFIS and WT-ANFIS approach

2019 ◽  
Vol 9 (5) ◽  
pp. 3916 ◽  
Author(s):  
Sani Salisu ◽  
Mohd Wazir Mustafa ◽  
Mamunu Mustapha ◽  
Olatunji Obalowu Mohammed
Keyword(s):  
Solar Radiation ◽  
Fuzzy Inference ◽  
Meteorological Data ◽  
Coefficient Of Determination ◽  
Maximum Temperature ◽  
Inference System ◽  
Hybrid Approaches ◽  
Neuro Fuzzy ◽  
Sunshine Hours ◽  
Statistical Indicators

<p>For an effective and reliable solar energy production, there is need for precise solar radiation knowledge. In this study, two hybrid approaches are investigated for horizontal solar radiation prediction in Nigeria. These approaches combine an Adaptive Neuro-fuzzy Inference System (ANFIS) with Particle Swarm Optimization (PSO) and Wavelet Transform (WT) algorithms. Meteorological data comprising of monthly mean sunshine hours (SH), relative humidity (RH), minimum temperature (Tmin) and maximum temperature (Tmax) ranging from 2002-2012 were utilized for the forecasting. Based on the statistical evaluators used for performance evaluation which are the root mean square error and the coefficient of determination (RMSE and R²), the two models were found to be very worthy models for solar radiation forecasting. The statistical indicators show that the hybrid WT-ANFIS model’s accuracy outperforms the PSO-ANFIS model by 65% RMSE and 9% R². The results show that hybridizing the ANFIS by PSO and WT algorithms is efficient for solar radiation forecasting even though the hybrid WT-ANFIS gives more accurate results.</p>

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 Empirical models for estimation of global solar radiation using the monthly average daily sunshine hours data for Makurdi, Benue State

2020 ◽  
Vol 12 (1) ◽  
pp. 32-39
Author(s):  
R.S. Sa’id ◽  
S.I. Akor ◽  
U.M. Gana
Keyword(s):  
Solar Radiation ◽  
Diffuse Radiation ◽  
Global Solar Radiation ◽  
Climatic Conditions ◽  
Empirical Models ◽  
Coefficient Of Determination ◽  
Linear Quadratic ◽  
Diffuse Fraction ◽  
Correlation Models ◽  
Sunshine Hours

This paper proposes empirical correlation models for estimating global solar radiation using data of sunshine hours for the location of Makurdi in Benue State of Nigeria. The paper suggests extrapolation of the empirical models for other locations with similar climatic conditions. The proposed models are: Linear, Quadratic, Cubic, Exponential, Power and Logarithmic models. Each of the models is based on Angstrom-Prescott equations for estimating global solar radiation. Any of the models can ease the use of sophisticated equipments, which are expensive, delicate and sometimes develop faults during measurement. The results of the models show that the cubic model is the best with slightly higher coefficient of  determination. The coefficient of  determination of each of the models was found to be 0.952, 0.965, 0.967, 0.965, 0.948& 0.924 respectively, while the absolute correlation was found to be unity. Errors evaluated include MBE, RMSE and MPE with minimal values. The percentage diffuse and direct solar radiations, clearness index and the diffuse fraction were also estimated using the models. The results of the estimations done using the proposed models indicate that there is an estimated average annual global solar radiation of 6056MJm-2, monthly value of 505MJm-2 and daily insolation of 16.82MJm-2 sufficient enough for maximum solar radiation exploitation. Keywords: Solar Radiation, Empirical Models, Diffuse Radiation, Direct Radiation

scholarly journals Empirical Models for Estimating Global Solar Radiation over the Ashanti Region of Ghana

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Emmanuel Quansah ◽  
Leonard K. Amekudzi ◽  
Kwasi Preko ◽  
Jeffrey Aryee ◽  
Osei R. Boakye ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Air Temperature ◽  
Empirical Model ◽  
Global Solar Radiation ◽  
Temperature Measurements ◽  
Coefficient Of Determination ◽  
Temperature Dependent ◽  
Tropical Regions ◽  
Ashanti Region ◽  
Sunshine Hours

The performances of both sunshine and air temperature dependent models for the estimation of global solar radiation (GSR) over Ghana and other tropical regions were evaluated and a comparison assessment of the models was carried out using measured GSR at Owabi (6°45′0′′N, 1°43′0′′W) in the Ashanti region of Ghana. Furthermore, an empirical model which also uses sunshine hours and air temperature measurements from the study site and its environs was proposed. The results showed that all the models could predict very well the pattern of the measured monthly daily mean GSR for the entire period of the study. However, most of the selected models overestimated the measured GSR, except in April and November, where the empirical model using air temperature measurements underestimated the measured GSR. Nevertheless, a very good agreement was found between the measured radiations and the proposed models with a coefficient of determination within the range 0.88–0.96. The results revealed that the proposed models using sunshine hours and air temperature had the smallest values of MBE, MPE, and RMSE of −0.0102, 0.0585, and 0.0338 and −0.2973, 1.7075, and 0.9859, respectively.

scholarly journals Comparative Study of Ground Measured, Satellite-Derived, and Estimated Global Solar Radiation Data in Nigeria

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Boluwaji M. Olomiyesan ◽  
Onyedi D. Oyedum
Keyword(s):  
Solar Radiation ◽  
Comparative Study ◽  
Global Radiation ◽  
Statistical Error ◽  
Global Solar Radiation ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Percentage Error ◽  
Radiation Data ◽  
Proposed Model

In this study, the performance of three global solar radiation models and the accuracy of global solar radiation data derived from three sources were compared. Twenty-two years (1984–2005) of surface meteorological data consisting of monthly mean daily sunshine duration, minimum and maximum temperatures, and global solar radiation collected from the Nigerian Meteorological (NIMET) Agency, Oshodi, Lagos, and the National Aeronautics Space Agency (NASA) for three locations in North-Western region of Nigeria were used. A new model incorporating Garcia model into Angstrom-Prescott model was proposed for estimating global radiation in Nigeria. The performances of the models used were determined by using mean bias error (MBE), mean percentage error (MPE), root mean square error (RMSE), and coefficient of determination (R2). Based on the statistical error indices, the proposed model was found to have the best accuracy with the least RMSE values (0.376 for Sokoto, 0.463 for Kaduna, and 0.449 for Kano) and highest coefficient of determination, R2 values of 0.922, 0.938, and 0.961 for Sokoto, Kano, and Kaduna, respectively. Also, the comparative study result indicates that the estimated global radiation from the proposed model has a better error range and fits the ground measured data better than the satellite-derived data.

scholarly journals Empirical model based on meteorological parameters to estimate the global solar radiation in Nepal

BIBECHANA ◽  
2014 ◽  
Vol 11 ◽  
pp. 25-33
Author(s):  
Krishna R Adhikari ◽  
Shekhar Gurung ◽  
Binod K Bhattarai
Keyword(s):  
Solar Radiation ◽  
Empirical Model ◽  
Meteorological Data ◽  
Cost Effective ◽  
Developed Countries ◽  
Global Solar Radiation ◽  
Develop Model ◽  
Sunshine Hours ◽  
Linear Regression Technique ◽  
Meteorological Characteristic

Solar radiation is the best option and cost effective energy resources of this globe. Only a few stations are there in developing and under developed countries including Nepal to monitor solar radiation and sunshine hours to generate a rational and accurate solar energy database. In this study, daily global solar radiation, and ubiquitous meteorological data (temperature and relative humidity) rather than rarely available sunshine hours have been used for Biratnagar, Kathmandu, Pokhara and Jumla to derive regression constants and hence to develop an empirical model. The model estimated global solar radiation is found to be in close agreement with measured values of respective sites. The estimated values were compared with Angstrom-Prescott model and examined using the statistical tools. Thus, the linear regression technique can be used to develop model at any location in the world. The resultant model may then be used to estimate the missing data of solar radiation for the respective sites and also can be used to estimate global solar radiation for the locations of similar geographic and meteorological characteristic. DOI: http://dx.doi.org/10.3126/bibechana.v11i0.10376   BIBECHANA 11(1) (2014) 25-33

scholarly journals Developing mathematical models for global solar radiation intensity estimation at Shakardara, Kabul

2021 ◽  
Vol 4 (2) ◽  
pp. 133-138
Author(s):  
Abdul Basit Da’ie
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Mathematical Models ◽  
Radiation Intensity ◽  
Global Solar Radiation ◽  
Suitable Model ◽  
Intensity Estimation ◽  
Solar Radiation Intensity ◽  
Sunshine Hours ◽  
Atmospheric Data

Solar energy properties such as Global Solar Radiation (GSR) intensity could be determined in either methods, experimentally or theoretically. Unfortunately, in most countries including Afghanistan, the first method which is more acceptable, but due to the high cost, maintenance and calibration requirements is not available. Therefore, an alternative widely used way is the second one which is model developments based on the meteorological (atmospheric) data; specially the sunny hours. The aim of this study at Shakardara area is to estimate atmospheric transparency percentage on 2017, determining the angstrom model coefficients and to introduce a suitable model for global solar radiation prediction. The hourly observed solar radiation intensity H (WHm-2 ) and sunshine hours S (

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