From Event: SPIE Optical Engineering + Applications, 2016
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.
Yanjun Chen, Wei Li, Chongyang Zhang, and Chuanping Hu, "Global velocity constrained cloud motion prediction for short-term solar forecasting," Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 99711U (Presented at SPIE Optical Engineering + Applications: September 01, 2016; Published: 28 September 2016); https://doi.org/10.1117/12.2239468.
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