assessment of offshore wind power potential in the aegean and ionian seas based on high-resolution hindcast model results

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ID: 176510
2017
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Abstract
In this study long-term wind data obtained from high-resolution hindcast simulations is used to analytically assess offshore wind power potential in the Aegean and Ionian Seas and provide wind climate and wind power potential characteristics at selected locations, where offshore wind farms are at the concept/planning phase. After ensuring the good model performance through detailed validation against buoy measurements, offshore wind speed and wind direction at 10 m above sea level are statistically analyzed on the annual and seasonal time scale. The spatial distribution of the mean wind speed and wind direction are provided in the appropriate time scales, along with the mean annual and the inter-annual variability; these statistical quantities are useful in the offshore wind energy sector as regards the preliminary identification of favorable sites for exploitation of offshore wind energy. Moreover, the offshore wind power potential and its variability are also estimated at 80 m height above sea level. The obtained results reveal that there are specific areas in the central and the eastern Aegean Sea that combine intense annual winds with low variability; the annual offshore wind power potential in these areas reach values close to 900 W/m2, suggesting that a detailed assessment of offshore wind energy would be worth noticing and could lead in attractive investments. Furthermore, as a rough estimate of the availability factor, the equiprobable contours of the event [4 m/s ≤ wind speed ≤ 25 m/s] are also estimated and presented. The selected lower and upper bounds of wind speed correspond to typical cut-in and cut-out wind speed thresholds, respectively, for commercial offshore wind turbines. Finally, for seven offshore wind farms that are at the concept/planning phase the main wind climate and wind power density characteristics are also provided.
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soukissian2017aimsassessment Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Takvor Soukissian;Anastasios Papadopoulos;Panagiotis Skrimizeas;Flora Karathanasi;Panagiotis Axaopoulos;Evripides Avgoustoglou;Hara Kyriakidou;Christos Tsalis;Antigoni Voudouri;Flora Gofa;Petros Katsafados
Journal Biology
Year 2017
DOI
10.3934/energy.2017.2.268
URL
http://www.aimspress.com/energy/article/1331/fulltext.html
Keywords
variability central stations powerplants

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