Empirical Models for Calculating Monthly Average Daily of Global Solar Radiation from Meteorological Data for Thailand
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Abstract
In this work, empirical models for estimating monthly average daily of global radiation from meteorological data were performed. The performance of the models was started with the collection of daily global solar radiation data, air temperature data (daily maximum, daily minimum, and daily mean), daily mean relative humidity data, and daily mean cloud cover data from 32 meteorological stations in Thailand for the seven-year period (2009 - 2015). The values of monthly average daily of global radiation, daily maximum air temperature, daily minimum air temperature, mean air temperature, mean relative humidity, and mean cloud cover and the values of monthly average of the difference between the daily maximum and daily minimum air temperatures were calculated. The values of monthly average daily extraterrestrial radiation were also computed. The adjusted coefficient of the ten models expressed the ratio of monthly average daily of global solar radiation and monthly average daily extraterrestrial radiation as functions of the monthly average daily of air temperature, relative humidity and cloud cover, and the difference between the daily maximum and daily minimum air temperatures. Then the models were tested against independent data set (2016 - 2018). The monthly average daily of global solar radiation calculated from these models was compared with that obtained from the measurement, with a root mean square error (RMSE) and mean bias error (MBE) between 4.3 - 19.2% and -6.3 - 7.0, respectively. However, the model 5 is the best.
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