Interrelations of Hourly and Daily Global Illuminance

Solar Energy ◽  
2006 ◽  
Author(s):  
P. Ravikumar
Keyword(s):  
Solar Radiation ◽  
Data Base ◽  
Global Solar Radiation ◽  
Measured Data ◽  
Light Measurement

It has been found that the values of ratio of hourly global illuminance to daily global illuminance, rvt, are very close to the corresponding values for global solar radiation, rt, examined from the measured data of six IDMP [1] (International Day light Measurement Programme) locations. This has been further confirmed by examining the values for rvt and rt as calculated from TMY2 [2] (Typical Metrological Year) data base for primary locations. Based on this, it has been proposed that the correlations available in literature to predict rt can be employed to predict rvt. Adequacy of the correlation due to Collares-Pereira and Rabl [3] available for rt has been examined to predict rvt as obtained from TMY2 data base for the 56 primary locations. It has been found that the values of rvt obtained from measured illuminance data of six locations have been predicted within a rms difference of 2.71% and within a rms difference of 4.3% for the 56 primary locations of TMY2 data when the correlation due to Collares-Pereira and Rabl for rt has been employed.

Hourly Distribution of Diffuse Illuminance

2003 ◽  
Author(s):  
V. V. Satyamurty ◽  
P. Ravikumar
Keyword(s):  
Solar Radiation ◽  
Data Base ◽  
Measured Data ◽  
Diffuse Solar Radiation ◽  
Hourly Distribution ◽  
Suitable Modification

It has been found that the values of ratio of hourly diffuse illuminance to daily diffuse illuminance, rvd, are very close to the corresponding values for diffuse solar radiation, rd, examined from the measured data of two locations. This has been further confirmed by examining the values for rvd and rd as calculated from TMY2 [1] data base for primary locations. Based on this, it has been proposed that the correlations available in literature to predict rd can be employed to predict rvd Adequacy of the correlation due to Satyamurty and Lahiri [2] available for rd has been examined to predict rvd as obtained from TMY2 data base for the 56 primary locations. It has been found that the values of rvd obtained from measured illuminance data of two locations have been predicted within a rms difference of 7.1% and within a rms difference of 4.3% for the 56 primary locations of TMY2 data when the correlation due to Satyamurty and Lahiri for rd has been employed after suitable modification.

scholarly journals A Temperature-Based Model for Estimating Monthly Average Daily Global Solar Radiation in China

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Huashan Li ◽  
Fei Cao ◽  
Xianlong Wang ◽  
Weibin Ma
Keyword(s):  
Solar Radiation ◽  
Air Temperature ◽  
Statistical Error ◽  
Global Solar Radiation ◽  
Measured Data ◽  
Temperature Data ◽  
New Model ◽  
Climatic Regions ◽  
Monthly Average ◽  
Temperature Records

Since air temperature records are readily available around the world, the models based on air temperature for estimating solar radiation have been widely accepted. In this paper, a new model based on Hargreaves and Samani (HS) method for estimating monthly average daily global solar radiation is proposed. With statistical error tests, the performance of the new model is validated by comparing with the HS model and its two modifications (Samani model and Chen model) against the measured data at 65 meteorological stations in China. Results show that the new model is more accurate and robust than the HS, Samani, and Chen models in all climatic regions, especially in the humid regions. Hence, the new model can be recommended for estimating solar radiation in areas where only air temperature data are available in China.

scholarly journals Measurement of Global Solar Radiation data using Raspberry Pi and its estimation using Genetic Algorithm

2018 ◽  
Vol 153 ◽  
pp. 07004
Author(s):  
S.Shanmuga Priya ◽  
Arunabh Borkataky ◽  
Sneha Reddy ◽  
I. Thirunavukkarasu
Keyword(s):  
Solar Radiation ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Measured Data ◽  
Environmentally Benign ◽  
Raspberry Pi ◽  
Radiation Data ◽  
Data Loggers ◽  
Intelligence Models ◽  
Artificial Intelligence Models

The demand for more efficient and environmentally benign, non-conventional sources of energy came into picture due to increasing demands for human comforts. Solar energy is now the ultimate option. In this paper, the instruments used to measure the solar radiation at Innovation Centre, MIT Manipal were connected to a Raspberry Pi to access the data remotely. Genetic Algorithms were formulated, so that the monthly mean global solar radiation in Manipal can be effectively estimated. Meteorological data such as humidity, temperature, wind speed, etc. were used as inputs to train the networks. A successful network was made between the data loggers and the Raspberry Pi. The data collected by the data loggers from the devices are transmitted to the Raspberry Pi which in turn sends the data to an internal server. The Raspberry Pi can be accessed using any SSH client such as PuTTY. The meteorological data was collected for the years 2010-2014 in order to formulate the Artificial Intelligence models. The validity of the formulated models were checked by comparing the measured data with the estimated data using tools such as RMSE, correlation coefficient, etc. The modelling of solar radiation using GA was carried out in GeneXpro tools version 5.0.

Simulation on Solar Hydrogen Generation With PEM Cells and Solar Modules

Solar Energy ◽  
2006 ◽  
Author(s):  
Yousuke Kawashima ◽  
Osamu Kawanami ◽  
Itsurou Honda
Keyword(s):  
Solar Radiation ◽  
Hydrogen Generation ◽  
Global Solar Radiation ◽  
Measured Data ◽  
Optimal Combination ◽  
Weather Data ◽  
Solar Module ◽  
Solar Hydrogen ◽  
Current Voltage ◽  
One Year

A simulation of solar hydrogen generation with solar modules and PEM cells in consideration of the solar module temperature for one year was carried out using our measured weather data. The optimal combination of the number of PEM sheets and solar modules was determined and hydrogen conversion efficiency was estimated. Solar module temperature was predicted from the measured data of global solar radiation, ambient temperature, and wind velocity. The current-voltage (I-V) curves of a solar module in arbitrary states were calculated from the (I-V) curves in the reference states using conversion equations (JIS C8913).

scholarly journals Prediction of Hourly Solar Radiation on Horizontal and Inclined Surfaces for Muscat/Oman

2011 ◽  
Vol 8 (2) ◽  
pp. 19 ◽  
Author(s):  
N.Z. Al-Rawahi ◽  
Y.H. Zurigat ◽  
N.A. Al-Azri
Keyword(s):  
Solar Radiation ◽  
Systems Design ◽  
Computer Code ◽  
Global Solar Radiation ◽  
Measured Data ◽  
Thermal Design ◽  
Radiation Fluxes ◽  
Inclined Surfaces ◽  
Systems Software ◽  
Design Calculations

 In this paper, hourly terrestrial radiation: direct beam, diffuse and global solar radiation are modelled and calculated based on daily measured data for a horizontal surface. In addition, the same parameters were modelled for inclined surfaces. Most of the parameters modelled in this work represent a part of the input data required by building thermal simulation and solar energy systems software. Important trends of the solar radiation on tilted surfaces as a function of time and direction are being presented and discussed. The comparison of some of the results with measured data from other sources shows good agreement. The effect of tilt angle and orientation on the incident solar radiation fluxes arepresented along with optimum surface tilt angles and directions for maximum solar radiation collection in Muscat area. The results presented in this paper are quite useful for quick estimation of solar radiation for calculations of cooling load and solar collector performance. Also, the models and the computer code developed in this work form the backbone of any computer-aided building thermal design and solar systems design calculations. 

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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