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Persistent Identifier
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hdl:21.15109/ARP/XVUWKB |
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Publication Date
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2024-11-11 |
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Title
| Ground-based all-sky imagery and weather data |
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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. |
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Other Identifier
| doi: 10.5158/ARP/XVUWKB |
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Author
| Barancsuk, Lilla (Centre for Energy Research) - ORCID: 0000-0002-3036-0133 |
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Point of Contact
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Use email button above to contact.
Barancsuk, Lilla (Centre for Energy Research) |
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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) |
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Subject
| Computer and Information Science; Earth and Environmental Sciences; Engineering; Physics |
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Keyword
| all-sky-imagery
meteorological data
ground based remote sensing
deep neural network
image processing
cloud |
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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) |
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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 |
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Notes
| This dataset contains the images zipped by day. |
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Language
| English |
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Producer
| Barancsuk, Lilla (HUN-REN Centre for Energy Research) (HUN-REN CER) https://www.ek.hun-ren.hu/en/home/ |
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Production Date
| 2024-11-09 |
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Production Location
| Budapest |
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Contributor
| Project Leader : Groma, Veronika
Data Collector : Günter, Dalma |
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Depositor
| Barancsuk, Lilla |
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Deposit Date
| 2024-11-09 |
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Time Period
| Start Date: 2024-11-09 ; End Date: 2024-11-30 |
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Date of Collection
| Start Date: 2021-11-11 ; End Date: 2024-08-04 |
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Data Type
| Kép |
