| Autor: |
Carlo Caligiuri, Laura Stendardi, Massimiliano Renzi |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Engineering Science and Technology, an International Journal, Vol 35, Iss , Pp 101117- (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2215-0986 |
| DOI: |
10.1016/j.jestch.2022.101117 |
| Popis: |
The exploitation of wind energy potential has been strongly limited in the Mediterranean area due to its critical bathymetry. However, the spread of new deep offshore technologies such as floating turbines could drastically change the actual scenario, allowing wind energy to be exploited even in areas with critical bathymetric conditions. In such framework, remote sensing technologies could significantly help the development of offshore wind farms and may represent a valid resource for better planning wind energy solutions. In this article, a satellite based methodology for assessing the wind energy potential of offshore areas is presented and applied on a study case in the Ionian sea to identify the most effective areas for energy harvesting. The study is based on the use of the Sentinel-1 OCeaN (OCN) products, which are Level-2 sea-based data products provided by Copernicus (the principle European Union’s earth observation programme), containing wind retrieval information. Despite their proven accuracy and their ease of use, OCN products have been rarely used in recent scientific production for energetic purposes. An initial investigation on wind speed characteristics has been carried out using as reference data-set the one provided by the Global Wind Atlas (GWA). A sub-area with maximum coastal wind speed gradient has been identified in the Region of Interest (ROI). Afterwards, 54 Sentinel-1 images have been processed. Data have been aggregated on a monthly domain (February 2020 - January 2021) to produce 12 wind speed maps of the ROI sub-area. A productivity analysis has been carried out in three specific sites. Results show: (i) the effectiveness of an OCN products based methodology for wind energy solutions planning, (ii) the reliability of the monthly based data aggregation (proven by a spatial dispersion analysis) and (iii) the specific wind energy production potentialities of the chosen ROI, where a single wind turbine installation could ensure an annual power production up to 19.06 GWh. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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