Improvements in solar radiation models based on cloud data

Simple radiation estimation models using meteorologically observed input parameters are often used in the applications requiring rough estimations of solar horizontal radiation. One of the parameters employed, cloud cover, is widely available from multiple regional and national weather stations. Kasten and Czeplak, Muneer and Gul, and Lam and Li, have proposed cloud-based models for the estimation of global and diffuse horizontal irradiance. In the current study, three new cloud-based models have been proposed. To compare the validity of the above models, statistical indicators have been developed for assessing the accuracy of estimation of global, diffuse and beam horizontal irradiance. The slope of the best fit line and the coefficient of determination between measured and calculated values, mean bias error, and root mean square error were calculated. In addition, the kurtosis and skewness of error histograms were also obtained. These parameters were used to obtain accuracy indicators for the models under validation. It was concluded that the proposed models outperformed the Kasten / Czeplak, and Lam / Li models, in both their original and modified forms. Practical application: Solar radiation data is an essential part of designing passive and active solar systems in building services. However, the solar radiation data is not always measured at the desired location, but other meteorological data are more available, therefore, tools have been developed to estimate the solar radiation from other measured parameters such as cloud cover. The models that are proposed are more accurate than their predecessors are, and provide global, beam and diffuse horizontal irradiance estimations. List of symbols