Multi-objective Optimization of a Megawatt Wind Turbine Blade Geometry Using an Evolutionary Algorithm, M.Sc. Thesis Sharif University of Technology ; Darbandi, Masoud (Supervisor)
Abstract
Without optimization, it is impossible to reduce the cost of power generation from an efficient megawatt wind turbine. In this work, we present a multi-objective algorithm to optimize the megawatt blade geometry. In this algorithm, the mass of blade and the wind turbine annual energy production (AEP) are considered as the objective functions. The design variables are blade chord, blade twist, airfoil thickness, spar geometry and blade curvature distribution.The constraints are maximum allowable strain for the chosen materials, maximum tip deflection and maximum tip speed. For the internal geometry, we consider two spars and four panels. The blade element momentum method (BEM) is used for...
Cataloging briefMulti-objective Optimization of a Megawatt Wind Turbine Blade Geometry Using an Evolutionary Algorithm, M.Sc. Thesis Sharif University of Technology ; Darbandi, Masoud (Supervisor)
Abstract
Without optimization, it is impossible to reduce the cost of power generation from an efficient megawatt wind turbine. In this work, we present a multi-objective algorithm to optimize the megawatt blade geometry. In this algorithm, the mass of blade and the wind turbine annual energy production (AEP) are considered as the objective functions. The design variables are blade chord, blade twist, airfoil thickness, spar geometry and blade curvature distribution.The constraints are maximum allowable strain for the chosen materials, maximum tip deflection and maximum tip speed. For the internal geometry, we consider two spars and four panels. The blade element momentum method (BEM) is used for...
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