3D cloud detection and tracking for solar forecast using multiple sky imagers

Zhenzhou Peng, Shinjae Yoo, Dantong Yu, Dong Huang, Paul Kalb, John Heiser

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

Abstract

Cloud detection and tracking (CDT) is the most challenging problem in integrating solar energy into the smart grid. In this paper, we present a novel 3D cloud detection and tracking using images from three TSI (Total Sky Imager), and propose to incorporate history into a multi-layer cloud detection pipeline. Our pilot study shows that the new CDT significantly improves the short-term solar irra-diance forecasting and enable regional radiation prediction, which is impossible with a single TSI.

Original languageEnglish (US)
Title of host publicationProceedings of the 29th Annual ACM Symposium on Applied Computing, SAC 2014
PublisherAssociation for Computing Machinery
Pages512-517
Number of pages6
ISBN (Print)9781450324694
DOIs
StatePublished - Jan 1 2014
Externally publishedYes
Event29th Annual ACM Symposium on Applied Computing, SAC 2014 - Gyeongju, Korea, Republic of
Duration: Mar 24 2014Mar 28 2014

Publication series

NameProceedings of the ACM Symposium on Applied Computing

Other

Other29th Annual ACM Symposium on Applied Computing, SAC 2014
Country/TerritoryKorea, Republic of
CityGyeongju
Period3/24/143/28/14

All Science Journal Classification (ASJC) codes

  • Software

Keywords

  • Cloud detection
  • Cloud tracking
  • SmartGrid

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