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Universidade Federal do Rio de Janeiro

Estabilidade atmosférica em projetos eólicos: estimativa bayesiana do comprimento de Monin Obukhov e simulação do escoamento atmosférico

Abstract

dc:description.abstract

This dissertation managed to increase the reliability of the assessment of any wind energy project using only what is already standard for any wind project development. Bayesian estimates of atmospheric parameters using only average wind speed measurements of a cup anemometer and CFD simulations coupled with thermal equations are used in order to define a more consistent WRG database without acquiring more data, investment or computational demand. Moreover, postprocessing of such WRG database aiming to kinetically identify vortexes was also carried out. Some validation studies were carried out in order to prove the reliability of those new methodologies created within this research. Results of atmospheric flow simulations regarding thermal stability are presented and contrasted with similar results that do not take into consideration thermal stability. Thus, the final analysis of the results obtained herein shows beyond doubt that it is possible to increase the quality of a standard wind resource assessment without necessarily requiring further investments or increasing computational demand.

Degree

thesis:*
Grantor dc:publisher
Universidade Federal do Rio de Janeiro
Year dc:date.issued
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Ramos, Daniel Agnese
Advisor dc:contributor.advisor
  • Duda, Fernando Pereira

Subjects

dc:subject × 3

Rights

dc:rights
Statement dc:rights
  • Acesso Aberto
Language dc:language
por

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/11422/5964
OAI identifier oai:identifier
oai:pantheon.ufrj.br:11422/5964

Chain of custody

source
Harvested from
Brazil UERJ
Base URL
pantheon.ufrj.br/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Ramos, Daniel Agnese. Estabilidade atmosférica em projetos eólicos: estimativa bayesiana do comprimento de Monin Obukhov e simulação do escoamento atmosférico. Universidade Federal do Rio de Janeiro, 2017. http://hdl.handle.net/11422/5964