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Τίτλος: Evaluating the suitability of Sentinel-1 SAR data for offshore wind resource assessment around Cyprus
Συγγραφείς: Hadjipetrou, Stylianos 
Liodakis, Stelios 
Sykioti, Anastasia 
Katikas, Loukas 
Park, No-Wook 
Kalogirou, Soteris A. 
Akylas, Evangelos 
Kyriakidis, Phaedon 
Major Field of Science: Engineering and Technology
Field Category: Environmental Engineering
Λέξεις-κλειδιά: Coastal meteorological stations;Sentinel-1;UERRA;Validation;Weibull
Ημερομηνία Έκδοσης: Ιαν-2022
Πηγή: Renewable Energy, 2022, vol. 182, pp. 1228-1239
Volume: 182
Start page: 1228
End page: 1239
Περιοδικό: Renewable Energy 
Περίληψη: Offshore wind offers an excellent opportunity for domestic renewable energy production with a vast potential for future energy systems. Offshore wind resource assessment, however, can be challenging. Remote sensing data e.g., Synthetic Aperture Radar (SAR), provide high spatial resolution detailed information on the spatial variability of offshore wind and have been used for wind resource assessment, as well as for the long-term validation of wind speed estimates from other sources (e.g. Numerical Weather Prediction models). This paper focuses on the evaluation of a 26-month time-series of Sentinel-1 SAR Level 2 OCN products for wind resource assessment in the offshore areas around Cyprus. Sentinel data were evaluated against a 10-year regional reanalysis dataset (UERRA) time-series and wind measurements from 5 coastal meteorological stations in Cyprus. Comparison revealed an overall agreement between the fitted stations and Sentinel Weibull distributions while discrepancies exist between the two data sources and UERRA. Bias observed between Sentinel and UERRA Weibull-derived statistics appears to be spatially dependent. Preliminary wind power assessment results indicate a significant wind power potential for the southwestern offshore areas of Cyprus, surpassing 400 W/m2 on average, offering thus economically viable solutions in terms of a future offshore wind power project development.
URI: https://hdl.handle.net/20.500.14279/23901
ISSN: 09601481
DOI: 10.1016/j.renene.2021.10.100
Rights: © Elsevier
Type: Article
Affiliation: Cyprus University of Technology 
ERATOSTHENES Centre of Excellence 
National Technical University Of Athens 
Inha University 
Geospatial Analytics Lab 
Publication Type: Peer Reviewed
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