Seasonal Wind Energy Characterization in the Gulf of Mexico

Alberto-Jesus Perea-Moreno, Gerardo Alcalá and Quetzalcoatl Hernandez-Escobedo
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Alberto-Jesus Perea-Moreno: Departamento de Física Aplicada, Universidad de Córdoba, ceiA3, Campus de Rabanales, 14071 Córdoba, Spain
Gerardo Alcalá: Centro de Investigación en Recursos Energéticos y Sustentables, Universidad Veracruzana, Veracruz 96535, Mexico
Quetzalcoatl Hernandez-Escobedo: Escuela Nacional de Estudios Superiores Juriquilla, UNAM, Queretaro 76230, Mexico

Energies, 2019, vol. 13, issue 1, 1-21

Abstract: In line with Mexico’s interest in determining its wind resources, in this paper, 141 locations along the states of the Gulf of Mexico have been analyzed by calculating the main wind characteristics, such as the Weibull shape ( c ) and scale ( k ) parameters, and wind power density (WPD), by using re-analysis MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications version 2) data with hourly records from 1980–2017 at a 50-m height. The analysis has been carried out using the R free software, whose its principal function is for statistical computing and graphics, to characterize the wind speed and determine its annual and seasonal (spring, summer, autumn, and winter) behavior for each state. As a result, the analysis determined two different wind seasons along the Gulf of Mexico;, it was found that in the states of Tamaulipas, Veracruz, and Tabasco wind season took place during autumn, winter, and spring, while for the states of Campeche and Yucatan, the only two states that shared its coast with the Caribbean Sea and the Gulf of Mexico, the wind season occurred only in winter and spring. In addition, it was found that by considering a seasonal analysis, more accurate information on wind characteristics could be generated; thus, by applying the Weibull distribution function, optimal zones for determining wind as a resource of energy can be established. Furthermore, a k -means algorithm was applied to the wind data, obtaining three clusters that can be seen by month; these results and using the Weibull parameter c allow for selecting the optimum wind turbine based on its power coefficient or efficiency.

Keywords: Weibull function; scale parameter; shape parameter; wind power density; seasons; Gulf of Mexico (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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