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• W2564754722 endingPage "304" @default.
• W2564754722 startingPage "280" @default.
• W2564754722 abstract "The joint modelling of wind speed and direction in an area is important for wind energy projects and a variety of ocean engineering applications. In the context of wind resource assessment, the analytical description of wind climate is usually confined to the description of wind speed; however, the accurate joint description of the directional and linear wind characteristics is also essential at the candidate sites for wind farm development. In this work, three families of models for the joint probabilistic description of wind speed and wind direction are examined and thoroughly evaluated, namely Johnson-Wehrly and two families of copulas, Farlie-Gumbel-Morgenstern and Plackett families. These models are applied on long-term wind data obtained by different measuring devices (five oceanographic buoys and one meteorological mast) for six different locations of the Greek and Spanish waters in the Mediterranean Sea. The proposed bivariate models are theoretically sound and tractable, since they are defined by closed relations and are constructed by considering the marginal (univariate) distributions of wind speed and wind direction along with an appropriate dependence structure of the involved variables. In the univariate case, wind speed modelling is based on a wide range of conventional and mixture distributions, while wind direction is modelled through finite mixtures of von Mises distributions. The evaluation of the bivariate models is based on seven bin-specific goodness-of-fit criteria, namely root mean square error, relative root mean square error, mean absolute error, index of agreement, chi-square statistic, adjusted coefficient of determination and normalized deviation. The obtained results suggest that the performance of the Johnson-Wehrly model is rather superior, since it provides better fits compared to the other two families of bivariate distributions for the overwhelming majority of the examined cases and criteria. The most efficient bivariate models are then implemented to estimate the detailed structure of wind power density at three selected locations." @default.
• W2564754722 created "2017-01-06" @default.
• W2564754722 creator A5030074450 @default.
• W2564754722 creator A5069083937 @default.
• W2564754722 date "2017-02-01" @default.
• W2564754722 modified "2023-10-05" @default.
• W2564754722 title "On the selection of bivariate parametric models for wind data" @default.
• W2564754722 cites W1000318598 @default.
• W2564754722 cites W1504395394 @default.
• W2564754722 cites W1835720201 @default.
• W2564754722 cites W1922082495 @default.
• W2564754722 cites W1968404225 @default.
• W2564754722 cites W1971518160 @default.
• W2564754722 cites W1974683416 @default.
• W2564754722 cites W1982487450 @default.
• W2564754722 cites W1985283750 @default.
• W2564754722 cites W1986377643 @default.
• W2564754722 cites W1989425731 @default.
• W2564754722 cites W1992821923 @default.
• W2564754722 cites W1995088783 @default.
• W2564754722 cites W1997497261 @default.
• W2564754722 cites W1998992373 @default.
• W2564754722 cites W2000097368 @default.
• W2564754722 cites W2000910899 @default.
• W2564754722 cites W2002010431 @default.
• W2564754722 cites W2002212083 @default.
• W2564754722 cites W2002924263 @default.
• W2564754722 cites W2004276209 @default.
• W2564754722 cites W2006393530 @default.
• W2564754722 cites W2006672150 @default.
• W2564754722 cites W2008759638 @default.
• W2564754722 cites W2010623381 @default.
• W2564754722 cites W2011251859 @default.
• W2564754722 cites W2013169545 @default.
• W2564754722 cites W2013267875 @default.
• W2564754722 cites W2014844929 @default.
• W2564754722 cites W2016255514 @default.
• W2564754722 cites W2017468850 @default.
• W2564754722 cites W2019495931 @default.
• W2564754722 cites W2026826548 @default.
• W2564754722 cites W2032170581 @default.
• W2564754722 cites W2032177435 @default.
• W2564754722 cites W2035971761 @default.
• W2564754722 cites W2047884674 @default.
• W2564754722 cites W2048061429 @default.
• W2564754722 cites W2053558371 @default.
• W2564754722 cites W2054091362 @default.
• W2564754722 cites W2055514786 @default.
• W2564754722 cites W2062337601 @default.
• W2564754722 cites W2063423863 @default.
• W2564754722 cites W2067718405 @default.
• W2564754722 cites W2068307375 @default.
• W2564754722 cites W2082128561 @default.
• W2564754722 cites W2082939027 @default.
• W2564754722 cites W2084028390 @default.
• W2564754722 cites W2084888130 @default.
• W2564754722 cites W2087056193 @default.
• W2564754722 cites W2090296073 @default.
• W2564754722 cites W2092545623 @default.
• W2564754722 cites W2095314268 @default.
• W2564754722 cites W2105137415 @default.
• W2564754722 cites W2108681805 @default.
• W2564754722 cites W2109966924 @default.
• W2564754722 cites W2113316891 @default.
• W2564754722 cites W2122780104 @default.
• W2564754722 cites W2132512281 @default.
• W2564754722 cites W2136686018 @default.
• W2564754722 cites W2137876336 @default.
• W2564754722 cites W2165436720 @default.
• W2564754722 cites W2168175751 @default.
• W2564754722 cites W2176166680 @default.
• W2564754722 cites W2181043883 @default.
• W2564754722 cites W2182235577 @default.
• W2564754722 cites W2283673116 @default.
• W2564754722 cites W2287448331 @default.
• W2564754722 cites W2291904439 @default.
• W2564754722 cites W2322769727 @default.
• W2564754722 cites W2336076800 @default.
• W2564754722 cites W2337297617 @default.
• W2564754722 cites W2345560945 @default.
• W2564754722 cites W2404758937 @default.
• W2564754722 cites W2433711949 @default.
• W2564754722 cites W2471082963 @default.
• W2564754722 cites W2473490200 @default.
• W2564754722 cites W2501819379 @default.
• W2564754722 cites W4229685370 @default.
• W2564754722 doi "https://doi.org/10.1016/j.apenergy.2016.11.097" @default.
• W2564754722 hasPublicationYear "2017" @default.
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