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Title: | Analysis of sea waves data for the Maltese Islands |
Authors: | Vassallo, Martina (2022) |
Keywords: | Oceanography -- Malta Ocean waves -- Malta Ocean waves -- Simulation methods Ocean wave power -- Malta |
Issue Date: | 2022 |
Citation: | Vassallo, M. (2022). Analysis of sea waves data for the Maltese Islands (Master's dissertation). |
Abstract: | This dissertation analyses different sources of sea waves data for the Maltese Islands. The first aim was to establish the comparability of different datasets, be it modelled or measured, hindcast or forecast, for the purpose of operational use. The second aim was to asses the power potential, using the same datasets as before, and investigating the applicability of different Wave Energy Converters (WECs). The dataset sources considered are the following: Directional Wave Spectral Drifter (buoy), HF Radar, Satellite, Copernicus model, and ROSARIOSWAN model. The ROSARIOSWAN model used in this work is one which has yet to be extensively validated and fine tuned, and so, this work serves to contribute to its further development. The inter-comparison of data from the considered datasets (excluding HF radar) generally yielded the the best correlation for the significant wave height (SWH) comparison, and the worst for the peak period comparison. ROSARIOSWAN models tend to overestimate the buoy values, while the Copernicus model compares better, despite lower resolution. Filtering out data with lower SWH yielded better correlation for all but the SWH parameter, when comparing buoy and model data. Two prominent wave directions, East and North-West, resulted from this analysis. The wave power potential analysis indicated that the Maltese Islands have a low potential for wave energy extraction (Class I) due to, mainly, low SWH; this is typical of enclosed seas. In addition, high variability in the Maltese Waters further worsen the situation. The WEC found to be most suitable in this study is the point absorber Wavestar C6 which, at the buoy position, has an annual average output power of 192.7 kW and capacity factor of 32.1%. |
Description: | M.Sc.(Melit.) Sust.Energy |
URI: | https://www.um.edu.mt/library/oar/handle/123456789/106951 |
Appears in Collections: | Dissertations - InsSE - 2022 |
Files in This Item:
File | Description | Size | Format | |
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2218ISEISE533005058753_1.PDF | 10.98 MB | Adobe PDF | View/Open |
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