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...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Engineering optimization Ročník 47; číslo 8; s. 1043 - 1062
Hlavní autori:	Sessarego, M., Dixon, K.R., Rival, D.E., Wood, D.H.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Abingdon Taylor & Francis 03.08.2015 Taylor & Francis Ltd
Predmet:	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
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!