A Cloud Displacement Estimation Approach for Sky Images Based on Phase Correlation Theory

Abstract

For intro-hour solar power forecasting approaches with sky images, the computing for cloud motion is very necessary. In this paper, a cloud displacement estimation method for sky images based on phase correlation theory is proposed. By Fourier transforming, the image matrix in frequency domain is obtained and then the cross-power spectrum of two adjacent sky images can be calculated. According to the inverse Fourier transform of the cross-power spectrum, the displacement of cloud in the two adjacent sky images is achieved. To improve the practical application ability of the approach, the noise signal in cross-power spectrum is analyzed and a filtering method to exclude erroneous results is also provided. Simulation results showed the effectiveness of the proposed method.