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Field validation and benchmarking of a cloud shadow speed sensor

Kuhn, Pascal Moritz and Wirtz, Marco and Wilbert, Stefan and Bosch, J.L. and Wang, G and Ramirez-Santigosa, Lourdes and Heinemann, Detlev and Pitz-Paal, Robert (2018) Field validation and benchmarking of a cloud shadow speed sensor. Solar Energy (173), pp. 229-245. Elsevier. DOI: 10.1016/j.solener.2018.07.053 ISSN 0038-092X

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Official URL: https://www.sciencedirect.com/science/article/pii/S0038092X18307175#!

Abstract

With ramp rate regulations for photovoltaic plants being discussed in many countries, the speed of clouds has gained significant importance lately. Besides, measuring cloud velocities and directions is of interest for validations of numerical weather predictions and solar nowcasting systems. Recently, the Cloud Shadow Speed Sensor (CSS) was developed and validated in San Diego for low cumulus clouds. In this publication, the CSS is studied under different weather and cloud conditions in the desert of Tabernas in southern Spain. Furthermore, a novel shadow camera based low-cost, low-maintenance approach to determine cloud shadow motion vectors is presented and used as a reference to benchmark the CSS. In comparison, the absolute velocities derived from the CSS and the shadow camera on 59 days for ±5 min temporal medians show deviations of RMSD 2.1 m/s (28.0%), MAD 1.2 m/s (15.7%) and a bias of −0.2 m/s (2.8%). Deviations of the cloud shadow direction are RMSD 47.9° (26.6%), MAD 25.3° (14.0%) and bias 3.7° (2.0%). An adaption of the CSS software yields 91% more measurements on 59 days in comparison to the previously used algorithms at the expense of reduced accuracies, both for the measured velocities and for the measured directions. The CSS and the novel shadow camera based reference system enable long-time, low-maintenance ground measurements of cloud shadow speeds, which were previously not available. The distinct advantages and limitations of the two systems are discussed. In addition to the comparisons between the shadow camera system and the CSS on 59 days, the detection rates of the CSS are classified and measured on 223 days by analyzing CSS radiometer signals. Depending on the shading strength and shading durations, detection rates vary between 3.7% and 21.6%. Furthermore, the basic assumption as well as possible correction approaches of the linear cloud edge – curve fitting method are studied. The CSS was found to be a robust tool with great potential. However, optically thin clouds with diffuse edges pose a challenge and the detection rate leaves room for improvements. The newly developed shadow camera system provides more measurements which scatter less but needs certain geographical requirements. The shadow camera is found to be a feasible validation tool for cloud (shadow) motion vectors.

Item URL in elib:https://elib.dlr.de/121312/
Document Type:Article
Title:Field validation and benchmarking of a cloud shadow speed sensor
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Kuhn, Pascal MoritzPascal.Kuhn (at) dlr.dehttps://orcid.org/0000-0001-9978-5706
Wirtz, MarcoSF-QLFUNSPECIFIED
Wilbert, StefanStefan.Wilbert (at) dlr.dehttps://orcid.org/0000-0003-3573-3004
Bosch, J.L.Universidad de HuelvaUNSPECIFIED
Wang, GUniversity of CaliforniaUNSPECIFIED
Ramirez-Santigosa, LourdesCIEMATUNSPECIFIED
Heinemann, DetlevUniversität OldenburgUNSPECIFIED
Pitz-Paal, RobertRobert.Pitz-Paal (at) dlr.dehttps://orcid.org/0000-0002-3542-3391
Date:October 2018
Journal or Publication Title:Solar Energy
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
DOI :10.1016/j.solener.2018.07.053
Page Range:pp. 229-245
Publisher:Elsevier
ISSN:0038-092X
Status:Published
Keywords:cloud shadow speed sensor, cloud speed, shadow camera system
HGF - Research field:Energy
HGF - Program:Renewable Energies
HGF - Program Themes:Concentrating Solar Thermal Technology
DLR - Research area:Energy
DLR - Program:E SW - Solar and Wind Energy
DLR - Research theme (Project):E - Impact of Desert Environment
Location: Köln-Porz
Institutes and Institutions:Institute of Solar Research > Qualification
Deposited By: Kruschinski, Anja
Deposited On:18 Sep 2018 08:31
Last Modified:01 Dec 2019 03:00

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