scholarly journals Prediction of daily global solar radiation using different empirical models on the basis of meteorological parameters at Trans Himalaya Region, Nepal

BIBECHANA ◽  
2021 ◽  
Vol 18 (1) ◽  
pp. 159-169
Author(s):  
Usha Joshi ◽  
I B Karki ◽  
N P Chapagain ◽  
K N Poudyal
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Meteorological Parameters ◽  
Energy Resource ◽  
Global Solar Radiation ◽  
Empirical Models ◽  
Mean Bias Error ◽  
Percentage Error ◽  
Sunshine Hour ◽  
Empirical Constants

Global Solar Radiation (GSR) is the cleanest and freely available energy resource on the earth.  GSR  was measured for six years (2010 -2015) at the horizontal surface using calibrated first-class CMP6 pyranometer at Kathmandu (Lat. 27.70o N, Long. 85.5oE and Alt. 1350m). This paper explains the daily, monthly, and seasonal variations of GSR and also compares with sunshine hour, ambient temperature, relative humidity, and precipitation to GSR. The annual average global solar radiation is about 4.16 kWh/m2/day which is a significant amount to promote solar active and passive energy technologies at the Trans-Himalaya region. In this study, the meteorological parameters are utilized in the regression technique for four different empirical models and finally, the empirical constants are found. Thus obtained coefficients are utilized to predict the GSR using meteorological parameters for the years to come. In addition, the predicted GSR is found to be closer to the measured value of GSR. The values are justified by using statistical tools such as coefficient of determination (R2), root mean square error (RMSE), mean percentage error (MPE), and mean bias error (MBE). Finally, the values of R2, RMSE, MPE, and MBE are found to be 0.792, 1.405, -1.014, and 0.011, respectively for the model (D), which are based on sunshine hour, temperature and relative humidity. In this model, the empirical constants, a = 0.155, b = 0.134, c = 0.014 and d = 0.0007 are determined which can be utilized at the similar geographical locations of Nepal. BIBECHANA 18 (2021) 159-169

scholarly journals Estimation of Solar Energy Using Different Empirical Models at Mid Hill, Nepal

2021 ◽  
Vol 7 (2) ◽  
pp. 42-48
Author(s):  
U. Joshi ◽  
P. M. Shrestha ◽  
S. Maharjan ◽  
B. Maharjan ◽  
N. P. Chapagain ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Solar Energy ◽  
Global Solar Radiation ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Percentage Error ◽  
Bias Error ◽  
Sunshine Hour ◽  
Empirical Constants

Accurate knowledge of global solar radiation distribution is essential for designing, sizing, and performing an evaluation of solar energy system in any part of the world. However, it is not available in many sites of Nepal due to the high expense of the technical process. This study is focused on the performance of different models based on daily global solar radiation, sunshine hour, temperature, and relative humidity at mid-hill region Lumle, (lat. 28.29650N, long. 83.8179oE, and Alt. 1740.0 m.a.s.l.). This study is carried for the year 2018 to 2020. The performance of different models based on sunshine hour, temperature, and relative humidity were analyzed using the regression technique and statistical tools such as Root Mean Square Error (RMSE), Mean Bias Error (MBE), Mean Percentage Error (MPE), and Coefficient of determination (R2). After the analysis, the modified Angstrom model (M-9) based on temperature difference and relative humidity was found to be the best in terms of accuracy of least RMSE value and highest coefficient of determination. Finally, the empirical constants for model m-9 are a = 0.003, b = 0.523, c = 0.118 and, d = 0.002 obtained. The calculated empirical constants can be utilized for the prediction of GSR at similar geographical locations of Nepal.

scholarly journals Influence of Sunshine Hour and Relative Humidity on Total Solar Radiation at Nepalganj, Nepal

Patan Pragya ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 97-104
Author(s):  
Usha Joshi ◽  
P. M. Shrestha ◽  
I. B. Karki ◽  
N. P. Chapagain ◽  
K. N. Poudyal
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Meteorological Parameters ◽  
Clean Energy ◽  
Empirical Models ◽  
Energy Resources ◽  
Total Solar Radiation ◽  
Sunshine Hour ◽  
Empirical Constants ◽  
Better Than

The solar energy is the abundantly available free and clean energy resources in Nepal. There are more than 300 sunny days because of Nepal lies in solar zone in a global map. The total solar radiation was measured by using CMP6 pyranometer at Nepalgunj (lat.:28.10oN, long.: 81.67oEand Alt. 165.0masl). The main objective of this study is to select the better empirical model and its empirical constants for the prediction of TSR for the year come. In this research, six different empirical models and meteorological parameters are utilized in the presence of regression technique for the years 2011 and 2012. Finally the different empirical constants are found. After the error analysis, the Swarthman-Oguniade model is found to perform better than others models. So the empirical constants of this model is utilized to predict the TSR of similar geographical sites of Nepal.

scholarly journals Empirical Models for Estimating Tropospheric Radio Refractivity Over Osogbo, Nigeria

2019 ◽  
Vol 13 (1) ◽  
pp. 43-55
Author(s):  
D. O. Akpootu ◽  
A. M. Rabiu
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Global Solar Radiation ◽  
Absolute Temperature ◽  
Empirical Models ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Percentage Error ◽  
Bias Error ◽  
Monthly Average

Background:Estimation of tropospheric radio refractivity is significant in the planning and design of terrestrial communication links.Methods:In this study, the monthly average daily atmospheric pressure, relative humidity and temperature data obtained from the National Aeronautics and Space Administration (NASA) during the period of twenty two years (July 1983 - June 2005) for Osogbo (Latitude 7.470N, Longitude 4.290E, and 302.0 m above sea level) were used to estimate the monthly tropospheric radio refractivity. The monthly average daily global solar radiation with other meteorological parameters was used to developed one, two, three and four variable correlation(s) tropospheric radio refractivity models for the location. The accuracy of the proposed models are validated using statistical indicator of coefficient of determination (R2), Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), Nash - Sutcliffe Equation (NSE) and Index of Agreement (IA).Results:In each case one empirical model was recommended based on their exceptional performances after ranking, except for the two variation correlations with two empirical models. The recommended models were further subjected to ranking from which the three variable correlations model that relates the radio refractivity with the absolute temperature, relative humidity and global solar radiation was found more suitable for estimating tropospheric radio refractivity for Osogbo with R2= 100.0%, MBE = -0.2913 N-units, RMSE = 0.3869 N-units, MPE = 0.0811%, NSE = 99.9999% and IA = 100.00%.Conclusion:The newly developed recommended models (Equations 16c, 17d, 17f, 18d and 19) can be used for estimating daily and monthly values of tropospheric radio refractivity with higher accuracy and has good compliance to highly varying climatic conditions for Osogbo and regions of similar climatic information.

scholarly journals Empirical Models for Estimating Tropospheric Radio Refractivity Over Osogbo, Nigeria

2019 ◽  
Vol 13 (1) ◽  
pp. 43-55
Author(s):  
D. O. Akpootu ◽  
A. M. Rabiu
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Global Solar Radiation ◽  
Absolute Temperature ◽  
Empirical Models ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Percentage Error ◽  
Bias Error ◽  
Monthly Average

Background:Estimation of tropospheric radio refractivity is significant in the planning and design of terrestrial communication links.Methods:In this study, the monthly average daily atmospheric pressure, relative humidity and temperature data obtained from the National Aeronautics and Space Administration (NASA) during the period of twenty two years (July 1983 - June 2005) for Osogbo (Latitude 7.470N, Longitude 4.290E, and 302.0 m above sea level) were used to estimate the monthly tropospheric radio refractivity. The monthly average daily global solar radiation with other meteorological parameters was used to developed one, two, three and four variable correlation(s) tropospheric radio refractivity models for the location. The accuracy of the proposed models are validated using statistical indicator of coefficient of determination (R2), Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), Nash - Sutcliffe Equation (NSE) and Index of Agreement (IA).Results:In each case one empirical model was recommended based on their exceptional performances after ranking, except for the two variation correlations with two empirical models. The recommended models were further subjected to ranking from which the three variable correlations model that relates the radio refractivity with the absolute temperature, relative humidity and global solar radiation was found more suitable for estimating tropospheric radio refractivity for Osogbo with R2= 100.0%, MBE = -0.2913 N-units, RMSE = 0.3869 N-units, MPE = 0.0811%, NSE = 99.9999% and IA = 100.00%.Conclusion:The newly developed recommended models (Equations 16c, 17d, 17f, 18d and 19) can be used for estimating daily and monthly values of tropospheric radio refractivity with higher accuracy and has good compliance to highly varying climatic conditions for Osogbo and regions of similar climatic information.

scholarly journals A Comparative Study of Some Regression Models to Estimate the Global Solar Radiation on a Horizontal Surface from Sunshine Duration and Meteorological Parameters for Ghardaïa Site, Algeria

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Kacem Gairaa ◽  
Yahia Bakelli
Keyword(s):  
Solar Radiation ◽  
Horizontal Plane ◽  
Regression Models ◽  
Meteorological Parameters ◽  
Sunshine Duration ◽  
Global Solar Radiation ◽  
Mean Bias Error ◽  
Percentage Error ◽  
Bias Error ◽  
Quadratic Models

A comparison between some regression correlations for predicting the global solar radiation received on a horizontal plane has been processed. Seven models for estimating the global solar radiation from sunshine duration and two meteorological parameters (air temperature and relative humidity) are presented. The root mean square error (RMSE), mean bias error (MBE), correlation coefficient (CC), and percentage error () have been also computed to test the accuracy of the proposed models. Comparisons between the measured and the calculated values have been made. The results obtained show that the linear and quadratic models are the most suitable for estimating the global solar radiation from sunshine duration, and for the models based on meteorological parameters, Abdalla and Ojosu's models give the best performance with a CC of 0.898 and 0.892, respectively.

Evaluation of Global Solar Radiation using Sunshine Hour, Temperature and Relative Humidity at Low Land Region of Nepal

2020 ◽  
Vol 6 (1) ◽  
pp. 16-24
Author(s):  
U. Joshi ◽  
K.N. Poudyal ◽  
I.B. Karki ◽  
N.P. Chapagain
Keyword(s):  
Solar Radiation ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Percentage Error ◽  
Bias Error ◽  
Energy Potential ◽  
To Come ◽  
Empirical Constants

The accurate knowledge of solar energy potential is essential for agricultural scientists, energy engineers, architects and hydrologists for relevant applications in concerned fields. It is cleanest and freely available renewable energy measured using CMP6 Pyranometer. However, it is quite challenging to acquire accurate solar radiation data in different locations of Nepal because of the high cost of instruments and maintenances. In these circumstances, it is essential to select an appropriate empirical model to predict global solar radiation for the use of future at low land, Nepalgunj (28.102°N, 81.668°E and alt. 165 masl) for the year 2011-2012. In this paper, six different empirical models have been used based on regression technique, provided the meteorological data. The empirical constants (a = 0.61, b = 0.05, c = -0.0012 and d = -0.017) are obtained to predict Global solar radiation. The values of statistical tools such as mean percentage error, mean bias error, root mean square error, and coefficient of determination obtained for Abdalla model are 1.99%, 0.003 MJ/m2/day, 2.04 MJ/m2/day and 0.74 respectively. Using the error analysis, it is concluded that the Abdalla model is better than others. So the empirical constants of this model are utilized to predict the global solar radiation to the similar geographical sites of Nepal for the years to come and it can be used to estimate the missing data of solar radiation for the respective sites.

scholarly journals Choice of ideal sunshine hour based model to predict global solar radiation in India

MAUSAM ◽  
2021 ◽  
Vol 71 (3) ◽  
pp. 451-466
Author(s):  
SAMANTA SUMAN ◽  
BANERJEE SAON ◽  
PATRA PULAK KUMAR ◽  
MAITI SUDHANSU SEKHAR ◽  
CHATTOPADHYAY NABANSU
Keyword(s):  
Energy Source ◽  
Solar Radiation ◽  
Energy Demand ◽  
Global Solar Radiation ◽  
Exponential Model ◽  
Mean Bias Error ◽  
Percentage Error ◽  
Bias Error ◽  
Energy Conversion Systems ◽  
Sunshine Hour

Solar radiation is the key energy source for most of the energy conversion systems, whether it is biological or mechanical. It is also the most fundamental energy source for future energy demand. Like most of the developing countries, India also lacks sufficient instrument facilities to measure global solar radiation (GSR) at recommended spatial interval and alternative approaches must be used to generate GSR data. In the present study, six well known empirical models were tested to estimate the GSR over twelve major cities of India using long-term global solar radiation and bright sunshine hour data. The empirical coefficients have been calculated for all the models and each location using regression analysis method. Daily GSR are then calculated using those regression constants along with statistical analysis. Results reveal that all the models shows close estimation with low mean bias error (MBE), root mean square error (RMSE) and mean percentage error (MPE) values. Among all models, linear exponential and linear logarithmic models are highly recommended for prediction of GSR throughout the country, except Shillong, where Bakircilinear exponential model is recommended. Significance tests i.e., t-test also confirms that this two model produce most significant results than others.

scholarly journals Empirical models for predicting global solar radiation using meteorological parameters for Sokoto, Nigeria

2019 ◽  
Vol 7 (2) ◽  
pp. 48
Author(s):  
Davidson O. Akpootu ◽  
Bello I. Tijjani ◽  
Usman M. Gana
Keyword(s):  
Solar Radiation ◽  
Meteorological Parameters ◽  
Meteorological Data ◽  
Climatic Variability ◽  
Global Solar Radiation ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Percentage Error ◽  
Bias Error ◽  
Radiation Maximum

The performances of sunshine, temperature and multivariate models for the estimation of global solar radiation for Sokoto (Latitude 13.020N, Longitude 05.250E and 350.8 m asl) located in the Sahelian region in Nigeria were evaluated 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). The comparison assessment of the models was carried out using statistical indices of coefficient of determination (R2), Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), t – test, Nash – Sutcliffe Equation (NSE) and Index of Agreement (IA). For the sunshine based models, a total of ten (10) models were developed, nine (9) existing and one author’s sunshine based model. For the temperature based models, a total of four (4) models were developed, three (3) existing and one author’s temperature based model. The results of the existing and newly developed author’s sunshine and temperature based models were compared and the best empirical model was identified and recommended. The results indicated that the author’s quadratic sunshine based model involving the latitude and the exponent temperature based models are found more suitable for global solar radiation estimation in Sokoto. The evaluated existing Ångström type sunshine based model for the location was compared with those available in literature from other studies and was found more suitable for estimating global solar radiation. Comparing the most suitable sunshine and temperature based models revealed that the temperature based models is more appropriate in the location. The developed multivariate regression models are found suitable as evaluation depends on the available combination of the meteorological parameters based on two to six variable correlations. The recommended models are found suitable for estimating global solar radiation in Sokoto and regions with similar climatic information with higher accuracy and climatic variability.   

scholarly journals Estimation of Global Solar Radiation using Modifed Angstrom Empirical formula on the basis of Meterological parameters in Himalaya Region Pokhara, Nepal

2016 ◽  
Vol 11 (1) ◽  
pp. 158-164
Author(s):  
Khem N. Poudyal
Keyword(s):  
Solar Radiation ◽  
Meteorological Parameters ◽  
Research Work ◽  
Global Solar Radiation ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Bias Error ◽  
Mean Square ◽  
Performance Parameters ◽  
Sunshine Hour

This research work proposes the coefficient equation of modified Angstrom   model using sunshine hour and meteorological parameters for the estimation of global solar radiation in Himalaya Region Pokhara (28.22° N, 83.32° E),  Nepal . This site is about 800.0 m above from the sea level lying just 20.0 km south of the Machhaputre Himalayas.  The model coefficients a and b obtained in this research are 0.43 and 0.23 respectively. The performance parameters of the model are: Root Mean Square Error RMSE = 0.13 MJ/m2 /day, Mean Bias Error MBE= 0.02 MJ/m /day Mean Percentage MPE= 5 percent and coefficient of determination R2 = 0.70. Journal of the Institute of Engineering, 2015, 11(1): 158-164

scholarly journals Estimation of Global Solar Radiation Using Empirical Model on Meteorological Parameters at Simara Airport, Bara, Nepal

2018 ◽  
Vol 14 (1) ◽  
pp. 143-150
Author(s):  
Janaki Awasthi ◽  
Khem Narayan Poudyal
Keyword(s):  
Solar Radiation ◽  
Empirical Model ◽  
Meteorological Parameters ◽  
Research Work ◽  
Winter Season ◽  
Global Solar Radiation ◽  
Measured Data ◽  
Mean Bias Error ◽  
Regression Equations ◽  
Empirical Constants

 This research work purpose to estimate the daily global solar radiation (GSR) using CMP6 pyranometer at low altitude of Simara Airport (lat. 27°9’33” N and long. 84°58’48” E, Alt.137m respectively). The measured data is used to study the diurnal, monthly, and seasonal variation of GSR. The maximum and minimum value of GSR is found at the spring and winter season respectively. A number of multi linear regression equations were developed to predict the relationship between GSR with one or more combinations of meteorological parameters using the regression technique and calculate the empirical constants from Tiwari & Sangeeta model which is the best empirical model among other tested models. The empirical constants and sunshine hour are utilized to estimate the GSR for the years 2009 and 2010 in the Simara Airport. The annual average solar insolation 4.62 and 4.56 k/m2/day is found at Simara Airport for years 2009 and 2010. The performance of each model was analyzed by calculating Root Mean Square Error (RMSE), Coefficient of Determination (R2) Mean Bias Error (MBE), and Mean Percent Error (MPE). The finding empirical constants 0.30 and 0.52 can be utilized to estimate the GSR where there is no measured data of GSR at similar meteorological sites of Nepal.Journal of the Institute of Engineering, 2018, 14(1): 143-150

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