Ground Sky Imager Based Short Term Cloud Coverage Prediction
- The paper describes a systematic approach for a precise short-time cloud coverage prediction based on an optical system. We present a distinct pre-processing stage that uses a model based clear sky simulation to enhance the cloud segmentation in the images. The images are based on a sky imager system with fish-eye lens optic to cover a maximum area. After a calibration step, the image is rectifiedThe paper describes a systematic approach for a precise short-time cloud coverage prediction based on an optical system. We present a distinct pre-processing stage that uses a model based clear sky simulation to enhance the cloud segmentation in the images. The images are based on a sky imager system with fish-eye lens optic to cover a maximum area. After a calibration step, the image is rectified to enable linear prediction of cloud movement. In a subsequent step, the clear sky model is estimated on actual high dynamic range images and combined with a threshold based approach to segment clouds from sky. In the final stage, a multi hypothesis linear tracking framework estimates cloud movement, velocity and possible coverage of a given photovoltaic power station. We employ a Kalman filter framework that efficiently operates on the rectified images. The evaluation on real world data suggests high coverage prediction accuracy above 75%.…
Document Type: | Conference Proceeding |
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Conference Type: | Konferenzartikel |
Zitierlink: | https://opus.hs-offenburg.de/3793 | Bibliografische Angaben |
Title (English): | Ground Sky Imager Based Short Term Cloud Coverage Prediction |
Conference: | 4th EAI International Conference (FABULOUS 2019), Sofia, Bulgaria, March 28-29, 2019 |
Author: | Stefan HenselStaff MemberORCiDGND, Marin B. Marinov, Raphael Schwarz, Ivan Topalov |
Year of Publication: | 2019 |
Place of publication: | Cham |
Publisher: | Springer |
Page Number: | 12 |
First Page: | 372 |
Last Page: | 385 |
Parent Title (English): | FABULOUS 2019: Future Access Enablers for Ubiquitous and Intelligent Infrastructures |
Editor: | Vladimir Poulkov |
ISBN: | 978-3-030-23975-6 (Print) |
ISBN: | 978-3-030-23976-3 (Online) |
ISSN: | 1867-8211 (Print) |
ISSN: | 1867-822X (Online) |
DOI: | https://doi.org/10.1007/978-3-030-23976-3_33 |
Language: | English | Inhaltliche Informationen |
Institutes: | Fakultät Elektrotechnik, Medizintechnik und Informatik (EMI) (ab 04/2019) |
Collections of the Offenburg University: | Bibliografie | Formale Angaben |
Open Access: | Closed Access |
Licence (German): | ![]() |
Comment: | Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 283) |