A classified irradiance forecast approach for solar PV prediction based on wavelet decomposition

Abstract

A classified irradiance forecast approach for solar PV prediction is proposed based on wavelet decomposition. The Daubechies wavelet is chose to decompose the irradiance series measured in the PV plant into approximate component and detailed component. The trend and variability of irradiance series are estimated respectively based on the two components. Then all the available irradiance data are labeled according to the features extracted from the approximate and detailed components. In the end, multiple forecast models are built and trained to adapt to the irradiance series of different labels. The simulation results show the effectiveness of the proposed approach.