TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Hensel, Stefan
A1  - Marinov, Marin B.
A1  - Schwarz, Raphael
A1  - Topalov, Ivan
ED  - Poulkov, Vladimir
T1  - Ground Sky Imager Based Short Term Cloud Coverage Prediction
T2  - FABULOUS 2019: Future Access Enablers for Ubiquitous and Intelligent Infrastructures
N2  - 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 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%.
Y1  - 2019
SN  - 1867-8211 (Print)
SS  - 1867-8211 (Print)
SN  - 1867-822X (Online)
SS  - 1867-822X (Online)
SN  - 978-3-030-23975-6 (Print)
SB  - 978-3-030-23975-6 (Print)
SN  - 978-3-030-23976-3 (Online)
SB  - 978-3-030-23976-3 (Online)
U6  - https://doi.org/10.1007/978-3-030-23976-3_33
DO  - https://doi.org/10.1007/978-3-030-23976-3_33
N1  - Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 283)
SP  - 372
EP  - 385
S1  - 12
PB  - Springer
CY  - Cham
ER  -