Ground-based all-sky imagery and weather data

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Barancsuk, Lilla, 2024, "Ground-based all-sky imagery and weather data", https://hdl.handle.net/21.15109/ARP/XVUWKB, ARP, V1

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Description	Ground-based remote sensing all-sky imagery recorded using a wide lens all-sky camera, meteorological measurements, and sky-parameter dataset calculated from the images using image processing and neural network architectures pre-trained with the datasets. The data collected during the project is recorded at the HUN-REN Center for Energy Research (HUN-REN CER) as part of the internal research project "Ultra-short-term irradiation forecasting using a combination of deep learning and image processing". The research aims to support the proper quality of power grid services, by forecasting solar radiation in the ultra-short-term, leading to improved operation of photovoltaic plants. The forecast is based on sky camera images and weather data, using a combination of deep learning and traditional image processing methodologies. (2024-11-09)
Subject	Computer and Information Science; Earth and Environmental Sciences; Engineering; Physics
Keyword	all-sky-imagery, meteorological data, ground based remote sensing, deep neural network, image processing, cloud
Related Publication	Barancsuk L, Groma V, Günter D, Osán J, Hartmann B. Estimation of Solar Irradiance Using a Neural Network Based on the Combination of Sky Camera Images and Meteorological Data. Energies. 2024; 17(2):438. doi: https://doi.org/10.3390/en17020438 doi: 10.3390/en17020438
Notes	This dataset contains the images zipped by day.
License/Data Use Agreement	CC BY-NC-SA 4.0

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	20211119.zip all-sky-imagery/2021/202111/ZIP Archive - 146.8 MB Published Nov 11, 2024 2 Downloads MD5: a345605b248ea205b34abf57f0ec34df	Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX
	20211120.zip all-sky-imagery/2021/202111/ZIP Archive - 125.4 MB Published Nov 11, 2024 0 Downloads MD5: b9db180275deba2d3dce98ed5ae9cd44	Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX
	20211121.zip all-sky-imagery/2021/202111/ZIP Archive - 86.1 MB Published Nov 11, 2024 0 Downloads MD5: 5f204fe2168bce91272d5e99371573bd	Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX
	20211122.zip all-sky-imagery/2021/202111/ZIP Archive - 150.2 MB Published Nov 11, 2024 0 Downloads MD5: ac2c4f79f17eee94228324ebbf857fb7	Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX
	20211123.zip all-sky-imagery/2021/202111/ZIP Archive - 132.5 MB Published Nov 11, 2024 0 Downloads MD5: 3edbacc3449ac06c2690b61ad1c24803	Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX
	20211124.zip all-sky-imagery/2021/202111/ZIP Archive - 119.3 MB Published Nov 11, 2024 0 Downloads MD5: 2992310b58e11a328c39e7893ba80a30	Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX
	20211125.zip all-sky-imagery/2021/202111/ZIP Archive - 140.6 MB Published Nov 11, 2024 0 Downloads MD5: 7044e96fab7072df4a68fa34845527ab	Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX
	20211126.zip all-sky-imagery/2021/202111/ZIP Archive - 132.0 MB Published Nov 11, 2024 0 Downloads MD5: f07924de61a4035ed625d63252c42797	Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX
	20211127.zip all-sky-imagery/2021/202111/ZIP Archive - 151.5 MB Published Nov 11, 2024 0 Downloads MD5: 7a03455f952bc021510a8eac966f4b65	Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX
	20211128.zip all-sky-imagery/2021/202111/ZIP Archive - 146.0 MB Published Nov 11, 2024 0 Downloads MD5: 25af302aeb0d50f7cc93a7d0f5ebe8b1	Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX

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Persistent Identifier	hdl:21.15109/ARP/XVUWKB
Publication Date	2024-11-11
Title	Ground-based all-sky imagery and weather data
Hungarian title	ground-based remote sensing all-sky imagery recorded using a wide lens all-sky camera, meteorological measurements, and sky-parameter dataset calculated from the images using image processing and neural network architectures pre-trained with the datasets. The data collected during the project is recorded at the HUN-REN Center for Energy Research (HUN-REN CER) as part of the internal research project "Ultra-short-term irradiation forecasting using a combination of deep learning and image processing". The research aims to support the proper quality of power grid services, by forecasting solar radiation in the ultra-short-term, leading to improved operation of photovoltaic plants. The forecast is based on sky camera images and weather data, using a combination of deep learning and traditional image processing methodologies. The total expected data volume for the project is approximately 250 GB. This includes raw images, processed data, and derived datasets.
Other Identifier	doi: 10.5158/ARP/XVUWKB
Author	Barancsuk, Lilla (Centre for Energy Research) - ORCID: 0000-0002-3036-0133
Point of Contact	Use email button above to contact. Barancsuk, Lilla (Centre for Energy Research)
Description	Ground-based remote sensing all-sky imagery recorded using a wide lens all-sky camera, meteorological measurements, and sky-parameter dataset calculated from the images using image processing and neural network architectures pre-trained with the datasets. The data collected during the project is recorded at the HUN-REN Center for Energy Research (HUN-REN CER) as part of the internal research project "Ultra-short-term irradiation forecasting using a combination of deep learning and image processing". The research aims to support the proper quality of power grid services, by forecasting solar radiation in the ultra-short-term, leading to improved operation of photovoltaic plants. The forecast is based on sky camera images and weather data, using a combination of deep learning and traditional image processing methodologies. (2024-11-09)
Subject	Computer and Information Science; Earth and Environmental Sciences; Engineering; Physics
Hungarian description	Földi távérzékelésű, széles objektíves égbolt-kamerával rögzített égboltfelvételek, meteorológiai mérések és a képekből hagyományos képfeldolgozással és mélytanulással kiszámított égbolt-paraméter-adatkészlet. A HUN-REN Energiakutatási Központban a "Ultra-rövid távú besugárzás-előrejelzés mélytanulás és képfeldolgozás kombinációjával" című kutatási projekthez rögzített adatok az ultra-rövid távú napsugárzás előrejelzésével támogatják az áramhálózati szolgáltatásokat és a fotovoltaikus erőművek biztonságos működését. Az adatok a 2021 novembere és 2024 júniusa közötti időszakra vonatkoznak, a felvételek 1 perces felbontásúak. (2024-11-09)
Keyword	all-sky-imagery meteorological data ground based remote sensing deep neural network image processing cloud
Related Publication	Barancsuk L, Groma V, Günter D, Osán J, Hartmann B. Estimation of Solar Irradiance Using a Neural Network Based on the Combination of Sky Camera Images and Meteorological Data. Energies. 2024; 17(2):438. doi: https://doi.org/10.3390/en17020438 doi: 10.3390/en17020438 https://www.mdpi.com/1996-1073/17/2/438
Notes	This dataset contains the images zipped by day.
Language	English
Producer	Barancsuk, Lilla (HUN-REN Centre for Energy Research) (HUN-REN CER) https://www.ek.hun-ren.hu/en/home/
Production Date	2024-11-09
Production Location	Budapest
Contributor	Project Leader : Groma, Veronika Data Collector : Günter, Dalma
Depositor	Barancsuk, Lilla
Deposit Date	2024-11-09
Time Period	Start Date: 2024-11-09 ; End Date: 2024-11-30
Date of Collection	Start Date: 2021-11-11 ; End Date: 2024-08-04
Data Type	Kép

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