Estimation of mean monthly global solar radiation using sunshine hours for Nairobi City, Kenya

2015 ◽  
Vol 7 (5) ◽  
pp. 053105 ◽  
Author(s):  
A. Omondi Onyango ◽  
Victor Ongoma
Keyword(s):  
Solar Radiation ◽  
Global Solar Radiation ◽  
Sunshine Hours

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 (

scholarly journals Estimation of monthly global solar radiation in Buenos Aires: preliminary analysis

2014 ◽  
Vol 5 (1) ◽  
pp. 669-680
Author(s):  
Susan G. Lakkis ◽  
Mario Lavorato ◽  
Pablo O. Canziani
Keyword(s):  
Solar Radiation ◽  
Buenos Aires ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Estimation Accuracy ◽  
Mean Bias Error ◽  
Percentage Error ◽  
Bias Error ◽  
Third Order ◽  
Sunshine Hours

Six existing models and one proposed approach for estimating global solar radiation were tested in Buenos Aires using commonly measured meteorological data as temperature and sunshine hours covering the years 2010-2013. Statistical predictors as mean bias error, root mean square, mean percentage error, slope and regression coefficients were used as validation criteria. The variability explained (R2), slope and MPE indicated that the higher precision could be excepted when sunshine hours are used as predictor. The new proposed approach explained almost 99% of the RG variability with deviation of less than ± 0.1 MJm-2day-1 and with the MPE smallest value below 1 %. The well known Ångström-Prescott methods, first and third order, was also found to perform for the measured data with high accuracy (R2=0.97-0.99) but with slightly higher MBE values (0.17-0.18 MJm-2day-1). The results pointed out that the third order Ångström type correlation did not improve the estimation accuracy of solar radiation given the highest range of deviation and mean percentage error obtained.  Where the sunshine hours were not available, the formulae including temperature data might be considered as an alternative although the methods displayed larger deviation and tended to overestimate the solar radiation behavior.

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.

Estimation of Daily Global Solar Radiation with Measured Meteorological Data in Xining, China

2013 ◽  
Vol 860-863 ◽  
pp. 54-57
Author(s):  
Hui Xie ◽  
Wei Liang ◽  
Jing Wen Luo
Keyword(s):  
Solar Radiation ◽  
Meteorological Data ◽  
Simulation Models ◽  
Global Solar Radiation ◽  
Optimal Method ◽  
Crop Simulation ◽  
Crop Simulation Models ◽  
Sunshine Hours ◽  
Major Variable

Solar radiation is a very important and major variable in crop simulation models. However, it is measured at a very limited number of meteorological stations worldwide. In this study, with Xining station, China, as a case study, 9 models were calibrated and evaluated using the meteorological data from 1959 to 2000 for estimating daily global solar radiation. The best results were derived from models 1-4, which used sunshine hours as the predictor. Temperature-based models (models 7-9) provided less accurate results. Therefore, we proposed a strategy to select an optimal method for calculating daily global solar radiation: (1) when sunshine hour data are available, use models 1-4; (2) when only temperature data are available, use models 7-9; and (3) when any meteorological data are not available, use models 5 and 6. Although these models were based on the metrological data of Xining station, they could be applied to other regions with similar meteorological conditions in China after calibration.

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