Assessment of Resource and Forecast Modeling of Wind Speed through An Evolutionary Programming Approach for the North of Tehuantepec Isthmus (Cuauhtemotzin, Mexico)

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@Article{Lopez-Manrique:2018:Energies,

• author = "Luis M. Lopez-Manrique and E. V. Macias-Melo and O. {May Tzuc} and A. Bassam and K. M. Aguilar-Castro and I. Hernandez-Perez",
• title = "Assessment of Resource and Forecast Modeling of Wind Speed through An Evolutionary Programming Approach for the North of Tehuantepec Isthmus (Cuauhtemotzin, Mexico)",
• journal = "Energies",
• year = "2018",
• volume = "11",
• number = "11",
• month = nov,
• keywords = "genetic algorithms, genetic programming, wind energy, wind characteristics, artificial intelligence, multi-gene genetic programming, sensitivity analysis, Matlab, GPTIPS",
• ISSN = "1996-1073",
• article-number = "3197",
• URL = "http://www.mdpi.com/1996-1073/11/11/3197",
• URL = "https://www.mdpi.com/1996-1073/11/11/3197/pdf",
• DOI = "doi:10.3390/en11113197",
• size = "22 pages",
• abstract = "This work studies the characteristics of the wind resource for a location in the north zone of Tehuantepec isthmus. The study was conducted using climatic data from Cuauhtemotzin, Mexico, measured at different altitudes above the ground level. The measured data allowed establishing the profile of wind speeds as well as the analysis of its availability. Analysis results conclude that the behaviour of the wind speed presents a bimodal distribution with dominant northeast wind direction (wind flow of sea-land). In addition, the area was identified as feasible for the use of low speed power wind turbines. On the other hand, the application of a new approach for very short-term wind speed forecast (10 min) applying multi-gene genetic programming and global sensitivity analysis is also presented. Using a computational methodology, an exogenous time series with fast computation time and good accuracy was developed for the forecast of the wind speed. The results presented in this work complement the panorama for the evaluation of the resource in an area recognized worldwide for its vast potential for wind power.",
• notes = "also known as \cite{en11113197}",

}

Genetic Programming entries for Luis Manuel Lopez-Manrique Edgar Vicente Macias Melo Oscar de Jesus May Tzuc Ali Bassam Karla Maria Aguilar Castro Ivan Hernandez-Perez

Citations