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Shadow-camera based solar nowcasting system for shortest-term forecasts

Kuhn, Pascal Moritz and Garsche, Dominik and Wilbert, Stefan and Nouri, Bijan and Hanrieder, Natalie and Prahl, Christoph and Zarzarlejo, Luis and Fernández, Jesús and Kazantzidis, Andreas and Schmidt, Thomas and Heinemann, Detlev and Blanc, Philippe and Pitz-Paal, Robert (2019) Shadow-camera based solar nowcasting system for shortest-term forecasts. Meteorologische Zeitschrift. Borntraeger Science Publishers. doi: 10.1127/metz/2019/0954. ISSN 0941-2948.

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Official URL: http://dx.doi.org/10.1127/metz/2019/0954


The rapid growth of solar power generation and the variable nature of the solar resource pose challenges for our electricity grids. Forecasting future changes in the irradiance might help to cost-efficiently manage this variability both for photovoltaic and concentration solar plants as well as grids with high solar penetrations. So far, for shortest-term forecasts with lead times of a few minutes, all-sky imager based nowcasting systems are used. However, due to the complexity of dynamically changing 3d cloud shapes as well as certain geometrical effects such as self-occlusion or near-horizon saturation, all-sky imager based nowcasting systems exhibit inherent weaknesses. Here, we present a novel system to generate shortest-term solar forecasts, which is located at Plataforma Solar de Almería in southern Spain. This approach is based on downward-facing cameras (shadow cameras), taking images of the ground. From these images, spatially resolved irradiance maps are derived. By tracking cloud shadows, future irradiances are predicted. A demonstration system is achieved, which provides shortest-term forecasts for the next 2min. To the best of our knowledge, this is the first time such a system is developed. We benchmark several possible algorithmic approaches on 16 days and compare the deviations to a state-of-the-art all-sky imager based nowcasting system on 22 days. The root-mean-squared deviation (RMSD) of this shadow camera based nowcasting system for direct normal irradiance (DNI) and 1-min temporal averages is 15.6% for lead times of 2min (MAD, DNI: 9.6 %). In comparison to an all-sky imager system, this is an improvement as the all-sky imager system only reaches 22.0% RMSD and 14.8% MAD (both DNI). This demonstrates the feasibility and attractiveness in terms of accuracy of the proposed concept.

Item URL in elib:https://elib.dlr.de/128807/
Document Type:Article
Title:Shadow-camera based solar nowcasting system for shortest-term forecasts
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Kuhn, Pascal MoritzPascal.Kuhn (at) dlr.dehttps://orcid.org/0000-0001-9978-5706
Wilbert, StefanStefan.Wilbert (at) dlr.dehttps://orcid.org/0000-0003-3573-3004
Nouri, BijanBijan.Nouri (at) dlr.deUNSPECIFIED
Hanrieder, NatalieNatalie.Hanrieder (at) dlr.deUNSPECIFIED
Prahl, ChristophChristoph.Prahl (at) dlr.deUNSPECIFIED
Zarzarlejo, LuisCIEMAT, AlmeriaUNSPECIFIED
Fernández, JesúsCIEMAT - Plataforma Solar de AlmeríaUNSPECIFIED
Kazantzidis, AndreasLAP, GRUNSPECIFIED
Schmidt, Thomasth.Schmidt (at) dlr.deUNSPECIFIED
Heinemann, Detlevdetlev.heinemann (at) dlr.deUNSPECIFIED
Blanc, Philippephilippe.blanc (at) mines-paristech.frUNSPECIFIED
Pitz-Paal, RobertRobert.Pitz-Paal (at) dlr.dehttps://orcid.org/0000-0002-3542-3391
Date:24 May 2019
Journal or Publication Title:Meteorologische Zeitschrift
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
DOI :10.1127/metz/2019/0954
EditorsEmailEditor's ORCID iD
Publisher:Borntraeger Science Publishers
Series Name:Energy Meteorology
Keywords:Solar nowcasting, energy meteorology, meteorological cameras, forecasting
HGF - Research field:Energy
HGF - Program:Technology, Innovation and Society
HGF - Program Themes:Renewable Energy and Material Resources for Sustainable Futures - Integrating at Different Scales
DLR - Research area:Energy
DLR - Program:E SY - Energy Systems Analysis
DLR - Research theme (Project):E - Systems Analysis and Technology Assessment (old), E - Impact of Desert Environment (old)
Location: Köln-Porz
Institutes and Institutions:Institute of Networked Energy Systems
Institute of Solar Research > Qualification
Deposited By: Kruschinski, Anja
Deposited On:26 Sep 2019 12:08
Last Modified:20 Jun 2021 15:52

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