Comparison and Prediction of Monthly Average Solar Radiation Data Using Soft Computing Approach for Eastern India

2014 ◽  
pp. 317-326 ◽  
Author(s):  
Sthitapragyan Mohanty ◽  
Prashanta Kumar Patra ◽  
Sudhansu S. Sahoo
Keyword(s):  
Solar Radiation ◽  
Soft Computing ◽  
Eastern India ◽  
Monthly Average ◽  
Radiation Data ◽  
Computing Approach

Analysis of Experimental Solar Radiation Data for Osogbo, Nigeria

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Abdulhamid Yusuf ◽  
Hakeem Bolarinwa ◽  
Lukman Animasahun ◽  
Yinusa Babatunde
Keyword(s):  
Solar Radiation ◽  
Global Solar Radiation ◽  
Total Radiation ◽  
Wet Season ◽  
Annual Average ◽  
Percentage Frequency ◽  
Monthly Average ◽  
Radiation Data ◽  
Maximum Value ◽  
Daily Total

An analysis of measured global solar radiation (GR) in Osogbo (7.77oN, 4.57oE, 288m) is presented in the form of hourly average, monthly average and percentage frequency distribution. The experimental data corresponds to a year data of 2017. The results reveal that the monthly average values of daily total radiation exhibit seasonal variation with maximum value in dry season month of March (16.59MJ/m2) and minimum value in wet season month of August (8.98 MJ/m2). The annual average GR value is 14.20 MJ/m2 while the annual cumulative GR is 5122 MJ/m2. The solar radiation climate of Osogbo has also been compared to those reported for a number of locations. The percentage frequency of days possessing irradiation rate greater than 15 MJ/m2 is 14 percent whereas that possessing less than 10 MJ/m2 is 61 percent. We conclude, based upon the above analysis that Osogbo is characterized by relatively low global solar radiation.

scholarly journals Generating Artificial Weather Data Sequences for Solar Distillation Numerical Simulations

2021 ◽  
Author(s):  
Bao The Nguyen
Keyword(s):  
Solar Radiation ◽  
Ambient Temperature ◽  
Simulation Program ◽  
Weather Data ◽  
Data Series ◽  
Monthly Average ◽  
Radiation Data ◽  
Solar Distillation ◽  
Irradiance Data ◽  
Tropical Climates

According to the natural geographical distribution, developing countries are concentrated in tropical climates, where radiation is abundant. So the use of solar energy is a sustainable solution for developing countries. However, daily or hourly measured solar irradiance data for designing or running simulations for solar systems in these countries is not always available. Therefore, this chapter presents a model to calculate the daily and hourly radiation data from the monthly average daily radiation. First, the chapter describes the application of Aguiar’s model to the calculation of daily radiation from average daily radiation data. Next, the chapter presents an improved Graham model to generate hourly radiation data series from monthly radiation. The above two models were used to generate daily and hourly radiation data series for Ho Chi Minh City and Da Nang, two cities representing two different tropical climates. The generated data series are tested by comparing the statistical parameters with the measured data series. Statistical comparison results show that the generated data series have acceptable statistical accuracy. After that, the generated radiation data series continue to be used to run the simulation program to calculate the solar water distillation system and compare the simulation results with the radiation data. Measuring radiation. The comparison results once again confirm the accuracy of the solar irradiance data generation model in this study. Especially, the model to generate the sequences of hourly solar radiation values proposed in this study is much simpler in comparison to the original model of Graham. In addition, a model to generate hourly ambient tempearure date from monthly average daily ambient temperature is also presented and tested. Then, both generated hourly solar radiation and ambient temperature sequences are used to run a solar dsitillation simulation program to give the outputs as monthly average daily distillate productivities. Finally, the outputs of the simulation program running with the generated solar radiation and ambient temperature data are compared with those running with measured data. The errors of predicted monthly average daily distillate productivities between measured and generated weather data for all cases are acceptably low. Therefore, it can be concluded that the model to generate artificial weather data sequences in this study can be used to run any solar distillation simulation programs with acceptable accuracy.

scholarly journals Soft Computing Techniques for a Solar Collector Using Solar Radiation Data

2017 ◽  
Vol 109 ◽  
pp. 439-446 ◽  
Author(s):  
Sthita Pragyan Mohanty ◽  
Auroshis Rout ◽  
Prashanta Kumar Patra ◽  
Sudhansu S. Sahoo
Keyword(s):  
Solar Radiation ◽  
Soft Computing ◽  
Solar Collector ◽  
Radiation Data ◽  
Soft Computing Techniques

Texas Solar Radiation Database (TSRDB)

Solar Energy ◽  
2002 ◽  
Author(s):  
Gary C. Vliet
Keyword(s):  
Solar Radiation ◽  
Normal Values ◽  
Average Difference ◽  
Monthly Average ◽  
Radiation Data ◽  
West Texas ◽  
Good Agreement

Solar radiation data have been acquired over approximately a five year period (1996 to present) at 15 sites in Texas (Texas Solar Radiation DataBase – TSRDB). These data are compared with comparable sites in the National Solar Radiation DataBase (NSRDB). Comparison of the TSRDB and NSRDB data for eleven (11) coincident or nearby locations show reasonably good agreement between the global horizontal values. Relative to the NSRDB, individual monthly average differences between the two sets range from −20 to +13%, and the annual averages varied from −9 to +8.5%, with positive values meaning the TSRDB values are higher. Overall, the TSRDB global horizontal data are about 2% lower than the NSRDB. However, there are considerable differences in the direct normal values, with the TSRDB values generally being higher. The monthly average differences ranged from −18 to +36%, and the average annual difference for the compared locations is about +5%. The greatest deviations for direct normal data are for coastal locations in the winter, with the three compared coastal locations exhibiting an average difference of about +30% for the combined months of December and January. Also, the TSRDB data for the Trans-Pecos region in west Texas exhibits significantly higher direct normal solar radiation throughout the year than does the NSRDB.

scholarly journals Angström-Prescott empirical model to estimate solar radiation in Norte de Santander, Colombia

2021 ◽  
Vol 11 (2) ◽  
pp. 413-428
Author(s):  
Wilmer Contreras-Sepúlveda ◽  
Migan Giuseppe Galban-Pineda ◽  
Luis Fernando Bustos-Márquez ◽  
Sergio Basilio Sepúlveda-Mora ◽  
Jhon Jairo Ramírez-Mateus
Keyword(s):  
Solar Radiation ◽  
Geographic Location ◽  
Historical Records ◽  
Monthly Average ◽  
Radiation Data ◽  
Design And Implementation ◽  
The Hours ◽  
Solar Brightness ◽  
A Site ◽  
Average Information

The document shows the application of the empirical Angström-Prescott model in different places in Norte de Santander, Colombia. The model estimates solar radiation from hours of sunlight, at a site where brightness and solar radiation are measured. The data were obtained from the Institute of Hydrology, Meteorology and Environmental Studies, IDEAM; algorithms were developed in RStudio to process and analyze the information. The model establishes a linear relationship between solar radiation and the hours of sunlight, in a specific geographic location. Therefore, regression analyzes were performed for three different sites, using historical records of brightness and solar radiation, obtaining the R-squared coefficients of: 0.73, 0.78, and 0.42. The models were then extrapolated to nearby regions with solar brightness records, but without solar radiation data, to obtain an estimate of radiation at these locations. Finally, a database was created with monthly average information on solar radiation for various subregions of Norte de Santander, which can be used for the design and implementation of photovoltaic systems.

scholarly journals Evaluation of different sunshine-based models for predicting global solar radiation – case study: New Borg El-Arab city, Egypt

2018 ◽  
Vol 22 (2) ◽  
pp. 979-992 ◽  
Author(s):  
Gasser Hassan ◽  
Elsayed Youssef ◽  
Mohamed Ali ◽  
Zahraa Mohamed ◽  
Ahmed Hanafy
Keyword(s):  
Solar Radiation ◽  
Global Solar Radiation ◽  
Horizontal Surface ◽  
Monthly Average ◽  
Radiation Data ◽  
Evaluation Of Performance ◽  
Model Predictions ◽  
Statistical Indicators ◽  
Radiation Measurements

The unavailability of the solar radiation measurements for different locations around the world leads to develop various empirical models to estimate the global solar radiation. In this consider, this study aims to investigate the performance of different solar radiation models to predict the monthly average daily global solar radiation on a horizontal surface. To achieve this, the measured global solar radiation data for a case study location are used. The model predictions are compared with the measured data to introduce the most accurate model for estimating the global solar radiation. The performance of each model is evaluated based on the different statistical indicators. The results show that the Robaa model has the best performance among the other models. Consequently, it can be used for estimating global solar radiation on a horizontal surface in the location under consideration. The accurate estimations of the global solar radiation using this approach can be used in the design and evaluation of performance for different solar applications.

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