28 September 2016 Global velocity constrained cloud motion prediction for short-term solar forecasting
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Abstract
Cloud motion is the primary reason for short-term solar power output fluctuation. In this work, a new cloud motion estimation algorithm using a global velocity constraint is proposed. Compared to the most used Particle Image Velocity (PIV) algorithm, which assumes the homogeneity of motion vectors, the proposed method can capture the accurate motion vector for each cloud block, including both the motional tendency and morphological changes. Specifically, global velocity derived from PIV is first calculated, and then fine-grained cloud motion estimation can be achieved by global velocity based cloud block researching and multi-scale cloud block matching. Experimental results show that the proposed global velocity constrained cloud motion prediction achieves comparable performance to the existing PIV and filtered PIV algorithms, especially in a short prediction horizon.
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Yanjun Chen, Yanjun Chen, Wei Li, Wei Li, Chongyang Zhang, Chongyang Zhang, Chuanping Hu, Chuanping Hu, } "Global velocity constrained cloud motion prediction for short-term solar forecasting", Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 99711U (28 September 2016); doi: 10.1117/12.2239468; https://doi.org/10.1117/12.2239468
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