A Cloud Displacement Estimation Approach for Sky Images Based on Phase Correlation Theory
Date
2016
Authors
Zhen, Zhao
Sun, Yujing
Wang, Fei
Mi, Zengqiang
Ren, Hui
Su, Shi
Yan, Yuting
Lu, Hai
Engerer, Nicholas
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IEEE
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.
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2016 IEEE International Conference on Power System Technology, POWERCON 2016
Type
Conference paper
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2099-12-31
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