Formation-aware Cloud Segmentation of Ground-based Images with Applications to PV Systems

Juan Andrade; Sameeksha Katoch; Pavan Turaga; Andreas Spanias; Cihan Tepedelenlioglu; Kristen Jaskie

doi:10.1109/IISA.2019.8900762

Formation-aware Cloud Segmentation of Ground-based Images with Applications to PV Systems

Juan Andrade
, Sameeksha Katoch
, Pavan Turaga
, Andreas Spanias
, Cihan Tepedelenlioglu
, Kristen Jaskie

Arizona State University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

Ground-based sky imaging has won popularity due to its higher temporal and spatial resolution when compared with satellite or air-borne sky imaging systems. Cloud identification and segmentation is the first step in several areas, such as climate research and lately photovoltaic power generation forecast. Cloud-sky segmentation involves several variables including sun position and type and altitude of clouds. We proposed a training-free cloud/sky segmentation based on a threshold that adapts to the cloud formation conditions. Experimental results show that the proposed method reaches higher detection accuracy against state-of-the-art algorithms; additionally, qualitative results over hemispherical high dynamic range (HDR) sky images are provided. The proposed cloud segmentation method can be applied to shading prediction for photovoltaic (PV) systems.

Original language	English
Title of host publication	10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728149592
DOIs	https://doi.org/10.1109/IISA.2019.8900762
State	Published - Jul 2019
Externally published	Yes
Event	10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019 - Patras, Greece Duration: 15 Jul 2019 → 17 Jul 2019

Publication series

Name	10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019

Conference

Conference	10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019
Country/Territory	Greece
City	Patras
Period	15/07/19 → 17/07/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Cloud segmentation
Curve fitting
Ground-based sky imaging
PV systems
Solar arrays
Training-free
Whole sky imager

Access to Document

10.1109/IISA.2019.8900762

Cite this

Andrade, J., Katoch, S., Turaga, P., Spanias, A., Tepedelenlioglu, C., & Jaskie, K. (2019). Formation-aware Cloud Segmentation of Ground-based Images with Applications to PV Systems. In 10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019 Article 8900762 (10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IISA.2019.8900762

Andrade, Juan ; Katoch, Sameeksha ; Turaga, Pavan et al. / Formation-aware Cloud Segmentation of Ground-based Images with Applications to PV Systems. 10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019).

@inproceedings{9cbd570e283c48eb84543e29ffd7244f,

title = "Formation-aware Cloud Segmentation of Ground-based Images with Applications to PV Systems",

abstract = "Ground-based sky imaging has won popularity due to its higher temporal and spatial resolution when compared with satellite or air-borne sky imaging systems. Cloud identification and segmentation is the first step in several areas, such as climate research and lately photovoltaic power generation forecast. Cloud-sky segmentation involves several variables including sun position and type and altitude of clouds. We proposed a training-free cloud/sky segmentation based on a threshold that adapts to the cloud formation conditions. Experimental results show that the proposed method reaches higher detection accuracy against state-of-the-art algorithms; additionally, qualitative results over hemispherical high dynamic range (HDR) sky images are provided. The proposed cloud segmentation method can be applied to shading prediction for photovoltaic (PV) systems.",

keywords = "Cloud segmentation, Curve fitting, Ground-based sky imaging, PV systems, Solar arrays, Training-free, Whole sky imager",

author = "Juan Andrade and Sameeksha Katoch and Pavan Turaga and Andreas Spanias and Cihan Tepedelenlioglu and Kristen Jaskie",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019 ; Conference date: 15-07-2019 Through 17-07-2019",

year = "2019",

month = jul,

doi = "10.1109/IISA.2019.8900762",

language = "Ingl{\'e}s",

series = "10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019",

}

Andrade, J, Katoch, S, Turaga, P, Spanias, A, Tepedelenlioglu, C & Jaskie, K 2019, Formation-aware Cloud Segmentation of Ground-based Images with Applications to PV Systems. in 10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019., 8900762, 10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019, Institute of Electrical and Electronics Engineers Inc., 10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019, Patras, Greece, 15/07/19. https://doi.org/10.1109/IISA.2019.8900762

Formation-aware Cloud Segmentation of Ground-based Images with Applications to PV Systems. / Andrade, Juan; Katoch, Sameeksha; Turaga, Pavan et al.
10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8900762 (10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Formation-aware Cloud Segmentation of Ground-based Images with Applications to PV Systems

AU - Andrade, Juan

AU - Katoch, Sameeksha

AU - Turaga, Pavan

AU - Spanias, Andreas

AU - Tepedelenlioglu, Cihan

AU - Jaskie, Kristen

PY - 2019/7

Y1 - 2019/7

N2 - Ground-based sky imaging has won popularity due to its higher temporal and spatial resolution when compared with satellite or air-borne sky imaging systems. Cloud identification and segmentation is the first step in several areas, such as climate research and lately photovoltaic power generation forecast. Cloud-sky segmentation involves several variables including sun position and type and altitude of clouds. We proposed a training-free cloud/sky segmentation based on a threshold that adapts to the cloud formation conditions. Experimental results show that the proposed method reaches higher detection accuracy against state-of-the-art algorithms; additionally, qualitative results over hemispherical high dynamic range (HDR) sky images are provided. The proposed cloud segmentation method can be applied to shading prediction for photovoltaic (PV) systems.

AB - Ground-based sky imaging has won popularity due to its higher temporal and spatial resolution when compared with satellite or air-borne sky imaging systems. Cloud identification and segmentation is the first step in several areas, such as climate research and lately photovoltaic power generation forecast. Cloud-sky segmentation involves several variables including sun position and type and altitude of clouds. We proposed a training-free cloud/sky segmentation based on a threshold that adapts to the cloud formation conditions. Experimental results show that the proposed method reaches higher detection accuracy against state-of-the-art algorithms; additionally, qualitative results over hemispherical high dynamic range (HDR) sky images are provided. The proposed cloud segmentation method can be applied to shading prediction for photovoltaic (PV) systems.

KW - Cloud segmentation

KW - Curve fitting

KW - Ground-based sky imaging

KW - PV systems

KW - Solar arrays

KW - Training-free

KW - Whole sky imager

UR - https://www.revistaespacios.com/a20v41n48/a20v41n48p07.pdf

U2 - 10.1109/IISA.2019.8900762

DO - 10.1109/IISA.2019.8900762

M3 - Contribución a la conferencia

AN - SCOPUS:85075853100

T3 - 10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019

BT - 10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019

Y2 - 15 July 2019 through 17 July 2019

ER -

Andrade J, Katoch S, Turaga P, Spanias A, Tepedelenlioglu C, Jaskie K. Formation-aware Cloud Segmentation of Ground-based Images with Applications to PV Systems. In 10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8900762. (10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019). doi: 10.1109/IISA.2019.8900762

Formation-aware Cloud Segmentation of Ground-based Images with Applications to PV Systems

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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