Intrahour cloud tracking based on optical flow

Songiie Zhang, Zhekang Dong, Xinyi Yang, Songiian Chai, Zhao Xu, Donglian Qi

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)


Drifting of the clouds may shade the sun which causes significant power output fluctuations in solar power systems. Forecasting the location of clouds could provide sufficient time to smoothen the power output. A method for identification and tracking cloud pixels from a commercial All-Sky camera is presented. Sky images taken every 5s were processed to determine the optimal threshold of different criterion to identify the six classes of clouds as well as clear-sky pixels. Cloud boundaries are tracked using Lucas-Kanade optical flow estimation method. The time when clouds will shade the sun can be forecasted 30s ahead with an acceptable accuracy. The research results demonstrate that the method presented has the potential for tracking different type of clouds with high variability.

Original languageEnglish
Title of host publicationProceedings of the 38th Chinese Control Conference, CCC 2019
EditorsMinyue Fu, Jian Sun
PublisherIEEE Computer Society
Number of pages6
ISBN (Electronic)9789881563972
Publication statusPublished - Jul 2019
Event38th Chinese Control Conference, CCC 2019 - Guangzhou, China
Duration: 27 Jul 201930 Jul 2019

Publication series

NameChinese Control Conference, CCC
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927


Conference38th Chinese Control Conference, CCC 2019


  • Cloud identification
  • Cloud tracking
  • Forecasting
  • Optical flow
  • Solar energy

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Applied Mathematics
  • Modelling and Simulation


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