A cloud displacement estimation approach for sky images based on phase correlation theory

Zhao Zhen, Yujing Sun, Fei Wang, Zengqiang Mi, Hui Ren, Shi Su, Yuting Yan, Hai Lu, Nicholas A. Engerer

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    2 Citations (Scopus)

    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.

    Original languageEnglish
    Title of host publication2016 IEEE International Conference on Power System Technology, POWERCON 2016
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9781467388481
    DOIs
    Publication statusPublished - 22 Nov 2016
    Event2016 IEEE International Conference on Power System Technology, POWERCON 2016 - Wollongong, Australia
    Duration: 28 Sept 20161 Oct 2016

    Publication series

    Name2016 IEEE International Conference on Power System Technology, POWERCON 2016

    Conference

    Conference2016 IEEE International Conference on Power System Technology, POWERCON 2016
    Country/TerritoryAustralia
    CityWollongong
    Period28/09/161/10/16

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