Nonparametric Conditional Heteroscedastic Hourly Probabilistic Forecasting of Solar Radiation

We develop a new probabilistic forecasting method for global horizontal irradiation (GHI) by extending our previous bootstrap method to a case of an exponentially decaying heteroscedastic model for tracking dynamics in solar radiance. Our previous method catered for the global systematic variation in variance of solar radiation, whereas our new method also caters for the local variation in variance. We test the performance of our new probabilistic forecasting method against our old probabilistic forecasting method at three locations: Adelaide, Darwin, and Mildura. These locations are chosen to represent three distinct climates. The prediction interval coverage probability, prediction interval normalized averaged width and Winkler score results from our new probabilistic forecasting method are encouraging. Our new method performs better than our previous method at Adelaide and Mildura; regions with a higher proportion of clear-sky days, whereas our previous method performs better than our new method at Darwin; a region with a lower proportion of clear-sky days. These results suggest that the ideal probabilistic forecasting method might be climate specific.