An autocorrelation-based copula model for producing realistic clear-sky index and photovoltaic power generation time-series

This study presents a method for using copulas to model the temporal variability of the clear-sky index. The method utilizes the autocorrelation function and correlated outputs for $N$ time-steps are obtained. Results from the copula model are, in terms of distribution, autocorrelation, step changes and mean daily distribution, compared with the original data set and with an uncorrelated model based on random clear-sky index data. The copula model is shown to be superior to the uncorrelated model in all these aspects.