A hybrid multi-objective evolutionary algorithm for wind-turbine blade optimization

A concurrent-hybrid non-dominated sorting genetic algorithm (hybrid NSGA-II) has been developed and applied to the simultaneous optimization of the annual energy production, flapwise root-bending moment and mass of the NREL 5 MW wind-turbine blade. By hybridizing a multi-objective evolutionary algor...

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Bibliographic Details
Published in:	Engineering optimization Vol. 47; no. 8; pp. 1043 - 1062
Main Authors:	Sessarego, M., Dixon, K.R., Rival, D.E., Wood, D.H.
Format:	Journal Article
Language:	English
Published:	Abingdon Taylor & Francis 03.08.2015 Taylor & Francis Ltd
Subjects:	beam theory Bending blade element momentum theory Blades Computational efficiency Convergence Evolutionary algorithms Genetic algorithms hybrid multi-objective evolutionary algorithm Hybridization multi-objective optimization Optimization Searching Three dimensional Tradeoffs Turbines
ISSN:	0305-215X, 1029-0273
Online Access:	Get full text
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