In this study, several regression models were employed to estimate global solar radiation from commonly available meteorological data such as sunshine duration, temperature, precipitation, and cloud cover for 34 meteorological stations of Bangladesh. The models studied were calibrated using five meteorological stations that are providing global solar radiation as well as other meteorological data. Estimated values were also compared with measured values in terms of statistical evaluation indicators like the coefficient of determination $$(R^{2}),$$ mean percentage error, mean bias error, root mean square error (RMSE), mean absolute relative error, and t statistic. The statistical analysis showed that the models assessed were well suited to accurately estimate the solar potential. Sunshine duration-based models performed best, and cloud cover-based models performed worst. Among 45 developed models to predict solar radiation, the models with RMSE value lower than 0.2 are recommended for use.

中文翻译：

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根据孟加拉国常用气象数据估算的全球太阳辐射

在这项研究中，采用了几种回归模型从孟加拉国34个气象站的常用气象数据（例如日照时长，温度，降水和云量）估算全球太阳辐射。使用五个提供全球太阳辐射以及其他气象数据的气象站对所研究的模型进行了校准。还根据统计评估指标（例如确定系数$$（R ^ {2}），$$平均百分比误差，平均偏差误差，均方根误差（RMSE），平均绝对相对误差）将估计值与测量值进行比较误差和t统计量。统计分析表明，所评估的模型非常适合准确估算太阳势。基于阳光持续时间的模型效果最好，基于云覆盖的模型表现最差。在45个预测太阳辐射的已开发模型中，建议使用RMSE值低于0.2的模型。