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dc.contributor.authorMeneguzzo Pasquali, Felipe
dc.date.accessioned2017-08-23T20:24:32Z
dc.date.available2017-08-23T20:24:32Z
dc.date.issued2016
dc.identifier.isbn9781339858425
dc.identifier.other1810143868
dc.identifier.urihttp://hdl.handle.net/10477/76324
dc.description.abstractWind energy has experienced significant growth over the past ten years. The reliance on wind energy is expected to grow even more as research and development efforts expand the technology for offshore use. Still, wind energy must become lower in cost, and the reliability must also improve to compete with traditional fossil fuels. In the majority of projects, the capital cost of the wind turbine is amortized in yearly payments through the service life. Thus, there is a relationship between the cost of energy and service life. Currently, the research lacks an investigation into the optimal service life of a wind turbine. This work aims to lay the groundwork towards such a model. To determine the optimal service life of a wind turbine, one must first have design tools that can accurately predict the fatigue life of the various components of the wind turbine. Accordingly, the objective of this work is to investigate, propose, and test such a framework. The framework defines a method for designing wind turbine components that are optimized with respect to cost and service life. Moreover, it creates a new design tool that compliments the existing computational resources that have been developed by the United Stated Department of Energy, National Renewable Energy Laboratory. The design tool has been developed in the MATLAB environment, and its use is demonstrated through a case study. Four wind turbine tower designs with a fatigue life of 20, 30, 40, and 80 years are compared in terms of cost. The results show that the tower with the longest design life is the optimal selection. Moreover, it demonstrates the use of the design methodology and framework.
dc.languageEnglish
dc.sourceDissertations & Theses @ SUNY Buffalo,ProQuest Dissertations & Theses Global
dc.subjectSocial sciences
dc.subjectApplied sciences
dc.subjectAeroelastic
dc.subjectGenetic algorithm
dc.subjectOptimization
dc.subjectTower
dc.subjectWind turbine
dc.titleAn Integrative Framework for Optimal Tower Life and Cost
dc.typeDissertation/Thesis


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