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 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.

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.

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 The seasonal variability of the amount of global solar radiation reaching the ground in urban and rural areas on the example of Warsaw and Belsk

2016 ◽  
Vol 20 (4) ◽  
pp. 29-37
Author(s):  
Kinga Nelken ◽  
Kamil Leziak
Keyword(s):  
Solar Radiation ◽  
Urban Area ◽  
Rural Area ◽  
Rural Areas ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Urban Station ◽  
Reverse Relationship ◽  
Urban And Rural Areas ◽  
The Relationship

AbstractThe aim of this paper is to determine the contemporary differences in the inflow of global solar radiation in Warsaw (urban station) and Belsk (rural station). The meteorological data used comprised daily sums of global solar radiation (in MJ•m−2) and the duration of sunshine (in hours) for the period 2008 2014. On clear days in spring and summer, the rural area receives more solar radiation in comparison to the urban area, whereas in autumn a reverse relationship occurs. On cloudy days in all seasons, the rural area receives more solar radiation than the urban area, and the relationship is the strongest in winter. Differences between urban and rural areas on cloudy days are smaller than those observed on clear days.

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 Empirical Model of Human Thermal Comfort in Subtropical Climates: A First Approach to the Brazilian Subtropical Index (BSI)

Atmosphere ◽  
2018 ◽  
Vol 9 (10) ◽  
pp. 391 ◽  
Author(s):  
João Gobo ◽  
Marlon Faria ◽  
Emerson Galvani ◽  
Fabio Goncalves ◽  
Leonardo Monteiro
Keyword(s):  
Thermal Comfort ◽  
Empirical Model ◽  
Thermal Sensation ◽  
Meteorological Data ◽  
Well Being ◽  
Global Solar Radiation ◽  
Coefficient Of Determination ◽  
Subtropical Climate ◽  
Human Thermal Comfort ◽  
The City

The bioclimatic well-being of individuals is associated with the environmental characteristics of where they live. Knowing the relationships between local and regional climatic variables as well as the physical characteristics of a given region and their implications on thermal comfort is important for identifying aspects of thermal sensation in the population. The aim of this study is to develop an empirical model of human thermal comfort based on subjective and individual environmental patterns observed in the city of Santa Maria, located in the state of Rio Grande do Sul, Brazil (Subtropical climate). Meteorological data were collected by means of an automatic meteorological station installed in the city center, which contained sensors measuring global solar radiation, air temperature, globe temperature (via a grey globe thermometer), relative humidity and wind speed and direction. A total of 1720 people were also interviewed using a questionnaire adapted from the model recommended by ISO 10551. Linear regressions were performed to obtain the predictive model. The observed results proposed a new empirical model for subtropical climate, the Brazilian Subtropical Index (BSI), which was verified to be more than 79% accurate, with a coefficient of determination of 0.926 and an adjusted R2 value of 0.924.

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