The availability of short-term forecast weather model for a particular country or region is essential for operation planning of\r\nenergy systems. This paper presents the first step by a group of researchers at UAE University to establish a weather model for\r\nthe UAE using the weather data for at least 10 years and employing various models such as classical empirical models, artificial\r\nneural network (ANN) models, and time-series regression models with autoregressive integrated moving-average (ARIMA). This\r\nwork uses time-series regression with ARIMA modeling to establish a model for the mean daily and monthly global solar radiation\r\n(GSR) for the city of Al-Ain, United Arab Emirates. Time-series analysis of solar radiation has shown to yield accurate average\r\nlong-term prediction performance of solar radiation in Al-Ain. The model was built using data for 10 years (1995ââ?¬â??2004) and\r\nwas validated using data of three years (2005ââ?¬â??2007), yielding deterministic coefficients (R2) of 92.6% and 99.98% for mean daily\r\nand monthly GSR data, respectively. The low corresponding values of mean bias error (MBE), mean absolute bias error (MABE),\r\nmean absolute percentage error (MAPE), and root-mean-square error (RMSE) confirm the adequacy of the obtained model for\r\nlong-term prediction of GSR data in Al-Ain, UAE.
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