Evaluation of Deep Learning-Based Neural Network Methods for Cloud Detection and Segmentation

Stefan Hensel, Marin B. Marinov, Michael Koch and Dimitar Arnaudov
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Stefan Hensel: Department for Electrical Engineering, University of Applied Sciences Offenburg, Badstraße 24, D-77652 Offenburg, Germany
Marin B. Marinov: Department of Electronics, Technical University of Sofia, 8, Kliment Ohridski Blvd., BG-1756 Sofia, Bulgaria
Michael Koch: Department for Electrical Engineering, University of Applied Sciences Offenburg, Badstraße 24, D-77652 Offenburg, Germany
Dimitar Arnaudov: Department of Power Electronics, Technical University of Sofia, 8, Kliment Ohridski Blvd., BG-1756 Sofia, Bulgaria

Energies, 2021, vol. 14, issue 19, 1-14

Abstract: This paper presents a systematic approach for accurate short-time cloud coverage prediction based on a machine learning (ML) approach. Based on a newly built omnidirectional ground-based sky camera system, local training and evaluation data sets were created. These were used to train several state-of-the-art deep neural networks for object detection and segmentation. For this purpose, the camera-generated a full hemispherical image every 30 min over two months in daylight conditions with a fish-eye lens. From this data set, a subset of images was selected for training and evaluation according to various criteria. Deep neural networks, based on the two-stage R-CNN architecture, were trained and compared with a U-net segmentation approach implemented by CloudSegNet. All chosen deep networks were then evaluated and compared according to the local situation.

Keywords: machine learning; generation; ground-based sky image; irradiation; load scheduling; photovoltaic power; short-term forecasting; solar irradiance; solar photovoltaics; total cloud cover (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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