Data-Based Statistical Property Analyzing and Storage Sizing for Hybrid Renewable Energy Systems

This paper presents a novel scheme of analyzing the statistical properties and sizing the storage for wind-photovoltaic-storage hybrid systems, based on the data organization and treatment for system optimization. First, the partial Fourier transform is derived for spectrum analysis by utilizing the periodic sparse properties of the solar data. Second, the storage for stabilizing the power variance caused by fluctuating renewable energies and varying grid loads is sized with spectrum analysis of the power data output from the system advisor model. Third, the weighting factor for storage sizing is achieved by constructing a hybrid probability distribution of renewable energies considering the coastal climates in South Eastern Australia, together with simplified parameter calculation methods. The real data sets, including the hourly wind speed, solar irradiation, and grid load, are used to design and validate the proposed scheme.