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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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División Académica de Ingeniería y Arquitectura, Doctorado en Ciencias de la Ingeniería (DCI), DAIA-UJAT, Universidad Juárez Autónoma de Tabasco, Carret. Cunduacán-Jalpa de Méndez Km. 1, Unidad Chontalpa, Cunduacán 86690, Mexico
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División Académica de Ingeniería y Arquitectura, DAIA-UJAT, Universidad Juárez Autónoma de Tabasco, Carret. Cunduacán-Jalpa de Méndez Km. 1, Unidad Chontalpa, Cunduacán CP 86690, Mexico
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Facultad de Ingeniería, Universidad Autónoma de Yucatán, Av. Industrias No Contaminantes, Apdo. Postal 150, Mérida 97310, Mexico
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Author to whom correspondence should be addressed.
Energies 2018, 11(11), 3197; https://doi.org/10.3390/en11113197
Received: 14 October 2018 / Revised: 4 November 2018 / Accepted: 16 November 2018 / Published: 18 November 2018
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 behavior 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. View Full-Text
Keywords: wind energy; wind characteristics; artificial intelligence; multi-gene genetic programming; sensitivity analysis wind energy; wind characteristics; artificial intelligence; multi-gene genetic programming; sensitivity analysis
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MDPI and ACS Style

López-Manrique, L.M.; Macias-Melo, E.V.; May Tzuc, O.; Bassam, A.; Aguilar-Castro, K.M.; Hernández-Pérez, I. Assessment of Resource and Forecast Modeling of Wind Speed through An Evolutionary Programming Approach for the North of Tehuantepec Isthmus (Cuauhtemotzin, Mexico). Energies 2018, 11, 3197.

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