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https://hdl.handle.net/20.500.14279/23901
Title: | Evaluating the suitability of Sentinel-1 SAR data for offshore wind resource assessment around Cyprus | Authors: | 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 | Keywords: | Coastal meteorological stations;Sentinel-1;UERRA;Validation;Weibull | Issue Date: | Jan-2022 | Source: | Renewable Energy, 2022, vol. 182, pp. 1228-1239 | Volume: | 182 | Start page: | 1228 | End page: | 1239 | Journal: | Renewable Energy | Abstract: | 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 |
Appears in Collections: | Άρθρα/Articles |
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