Donatelli and Campbell model algorithm is similar in structure to the
Bristow and Campbell model so when using the Donatelli and Campbell model empirical coefficients a,b & c can we equate them to the location dependent empirical coefficients of the Bristow - Campbell model? I wasn`t able to find any relation for finding the Donatelli and Campbell model coefficients, a little guidance will be highly appreciated. Thank you
Dear Muhammad Munir;
The empirical coefficients a, b and c of the regression models of both Donatelli & Campbell (1998) or Bristow & Campbell can be estimated by the curve estimation techniques using Excel, Matlab,....based on the measured data of global solar radiation and air temperature.
Furthermore, there are developed softwares named Gsrad,RadEst that include these two models to estimate solar radiation (check: https://www.researchgate.net/publication/222670312_A_software_component_for_estimating_solar_radiation), and you can download them from this link: http://agsys.cra-cin.it/tools/
Mostly, these coefficients that presented in each research are dependent to the site of interest, for example: if a researcher in Algeria obtain his own coefficients for sites in Algeria, if you apply them in UAE, they will not give you good performances as in Algeria.
Therefore, I recommend you to collect your measured data of the studied locations and apply different models including the above mentioned correlation and perform a new research as presented in some of these references:
1. Adaramola MS. Estimating global solar radiation using common meteorological data in Akure, Nigeria. Renew Energy 2012;47:38–44.
2. Hargreaves GH, Samani ZA. Estimating potential evapotranspiration. J Irrig
Drain Eng 1982;108:223–30.
3. Bristow KL, Campbell GS. On the relationship between incoming solar radiation and daily maximum and minimum temperature. Agric Forest Meteorol 1984;31:59–166.
4. Almorox J, Hontoria C, Benito M. Models for obtaining daily global solar radiation with measured air temperature data in Madrid (Spain). Appl Energy 2011;88:1703–9.
5. M.S. Mecibah et al. Introducing the best model for estimation the monthly mean daily global solar radiation on a horizontal surface (Case study: Algeria). Renew Sustain Energy Rev 36 (2014) 194–202.
I hope this can help
Article A software component for estimating solar radiation
Hi Muhammad,
In general these classic parametric models need to be calibrated and validated in each location since most of them lack of spatial generalization. For a review of 24 of these parametric models I recommend this paper: https://www.researchgate.net/publication/258705095_Evaluation_and_improvement_of_empirical_models_of_global_solar_irradiation_Case_study_northern_Spain
Furthermore, I recommend that if you have a sufficiently long dataset you should calibrate the model doing bootstrapping (i.e. sampling 80% original of the original dataset and using it for training and repeating this 100 times) so you can evaluate how the parameters of the model and the errors of testing with unseen data would variate in case of calibrating the model with different data (this is also explained in the paper). You should choose the models with lower errors of testing but at the same with lower variation of validation errors and parameters (more robust models). For this training I used R free software (https://www.r-project.org).
Find attach an example with R (code.R and meteo.RData). For your case of study you should create a data.frame with your meteo data.
Article Evaluation and improvement of empirical models of global sol...
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