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Short-term forecasting of solar irradiance

Paulescu, Marius, Paulescu, Eugenia
Renewable energy 2019 v.143 pp. 985-994
radiometry, renewable energy sources, solar radiation, statistical models, transmittance, Romania
Five statistical models for nowcasting solar irradiance are evaluated from different perspectives. The first four models are purely statistical ones: random walk, moving average, exponential smoothing and autoregressive integrated moving average. These models can be considered as benchmarks of different levels of complexity. The fifth model is a version of the two-state model, an applications suite for nowcasting solar irradiance developed by our team. The two-state model connects in an innovative manner an empirical estimator for clear-sky solar irradiance with a statistical predictor for the sunshine number, a binary indicator stating whether the sun shines or not. On the basis of different error metrics, the models’ performances are analyzed from four perspectives: forecast accuracy, forecast precision, data series granularity and variability in data series. The study is conducted with high-quality radiometric data measured at a high frequency of four samples per minute on the Solar Platform of the West University of Timisoara, Romania. No model is ranked as the best, but the peculiarities that cause a model to perform better than others are discussed. By processing information about the atmospheric transmittance, the two-state model proves a slight advance in the forecast accuracy and a notable performance in the forecast precision.