EconPapers    
Economics at your fingertips  
 

Multi-objective optimization of wind turbine blades using lifting surface method

Xin Shen, Jin-Ge Chen, Xiao-Cheng Zhu, Peng-Yin Liu and Zhao-Hui Du

Energy, 2015, vol. 90, issue P1, 1111-1121

Abstract: This paper describes a multi-objective optimization method for the design of horizontal axis wind turbines using the lifting surface method as the performance prediction model. The aerodynamic code for the design method is based on the lifting surface method with a prescribed wake model for the description of the wake. A multi-objective optimization algorithm approach is employed for the optimization of wind turbine blades with 3D stacking line (swept leaned blades). The (NSGA II) Non-dominated sorting genetic algorithm II is used to facilitate the multi-objective optimization and to find the global optima of high-dimensional problems. The scope of the optimization method is to achieve the best trade off of the following objectives: maximum of annual energy production and minimum of blade loads including thrust and blade rood flap-wise moment. To illustrate how the optimization of the blade is carried out the procedure is applied to NREL Phase VI rotor. The result shows the optimization models can provide more efficient designs.

Keywords: Wind turbine; Lifting surface method; Free wake model; Multi-objective optimization (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S036054421500818X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:90:y:2015:i:p1:p:1111-1121

DOI: 10.1016/j.energy.2015.06.062

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:energy:v:90:y:2015:i:p1:p:1111-1121