0

Full Content is available to subscribers

Subscribe/Learn More  >

Multi-Discipline Design of a Wind Turbine

[+] Author Affiliations
Nickolas Vlahopoulos, Hong Yoon Kim, Kevin Maki

University of Michigan, Ann Arbor, MI

Ricardo Sbragio

Michigan Engineering Services, Ann Arbor, MI

Paper No. DETC2011-47756, pp. 291-301; 11 pages
doi:10.1115/DETC2011-47756
From:
  • ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 5: 37th Design Automation Conference, Parts A and B
  • Washington, DC, USA, August 28–31, 2011
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5482-2
  • Copyright © 2011 by ASME

abstract

In this paper a Multi-Level System design (MLS) algorithm is presented and utilized for a wind turbine system analysis. The MLS guides the decision making process for designing a complex system where many alternatives and many mutually competing objectives and disciplines need to be considered and evaluated. Mathematical relationships between the design variables and the multiple discipline performance objectives are developed adaptively as the various design considerations are evaluated and as the design is being evolved. These relationships are employed for rewarding performance improvement during the decision making process by allocating more resources and influence to the disciplines which exhibit the improvement. Simulation tools developed by the National Renewable Energy Laboratory (NREL) are employed in the wind turbine design analysis. The Cost Of Energy (COE) comprises the overall system level objective, while performance improvements at two technical design disciplines are pursued at the same time. The optimal design of the blade geometry for maximum Annual Energy Production (AEP), and the structural design of the blade for minimum bending moment at the root of the blade comprise the two technical design disciplines. Scalar metamodels are developed for linking the design variables with the performance metrics associated with the design of the blade geometry. Main characteristics of the wind turbine, namely, the rotor diameter, the rotational speed, the maximum rated power, the hub height, the structural characteristics of the blade, and the geometric characteristics of the blade (distribution of thickness, twist angle, and chord) are employed as design variables for the overall design analysis. The optimization results and the physical insight which can be gained through a sensitivity analysis for the optimal configuration are presented and discussed.

Copyright © 2011 by ASME

Figures

Tables

Interactive Graphics

Video

Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In