Research Papers

Bladelets—Winglets on Blades of Wind Turbines: A Multiobjective Design Optimization Study

[+] Author and Article Information
Sohail R. Reddy

Presidential Fellow
MAIDROC Laboratory, Department of Mechanical and Materials Engineering,
Florida International University,
Miami, FL 33174
e-mail: sredd001@fiu.edu

George S. Dulikravich

Fellow ASME
Director of MAIDROC Lab, MAIDROC Laboratory,
Department of Mechanical and Materials Engineering,
Florida International University,
Miami, FL 33174
e-mail: dulikrav@fiu.edu

Helmut Sobieczky

Institute of Fluid Mechanics and Heat Transfer,
Vienna University of Technology,
1010 Vienna, Austria
e-mail: helmut@sobieczky.at

Manuel Gonzalez

MAIDROC Laboratory,
Department of Mechanical and Materials Engineering,
Florida International University,
Miami, FL 33174
e-mail: mgonz697@fiu.edu

Contributed by the Solar Energy Division of ASME for publication in the Journal of Solar Energy Engineering: Including Wind Energy and Building Energy Conservation. Manuscript received May 26, 2018; final manuscript received April 24, 2019; published online May 20, 2019. Assoc. Editor: Douglas Cairns.

J. Sol. Energy Eng 141(6), 061003 (May 20, 2019) (6 pages) Paper No: SOL-18-1234; doi: 10.1115/1.4043657 History: Received May 26, 2018; Accepted April 25, 2019

The work presented in this paper used rigorous 3D flow-field analysis combined with multi-objective constrained shape design optimization for the design of complete blade + bladelet configurations for a three-blade horizontal-axis wind turbine. The fluid flow analysis in this work was performed using Openfoam software. The 3D, steady, incompressible, turbulent flow Reynolds-Averaged Navier–Stokes equations were solved in the rotating frame of reference for each combination of wind turbine blade and bladelet geometry. The free stream uniform wind speed in all cases was assumed to be 9 m s−1. The three simultaneous design optimization objectives were as follows: (a) maximize the coefficient of power, (b) minimize the coefficient of thrust force, and (c) minimize twisting moment around the blade axis. The bladelet geometry was fully defined by using a small number of parameters. The optimization was carried out by creating a multidimensional response surface for each of the simultaneous objectives. The response surfaces were based on radial basis functions, where the support points were designs analyzed using the high-fidelity computational fluid dynamics (CFD) analysis of the full blade + bladelet geometry. The response surfaces were then coupled to an optimization algorithm in modefrontier software. The predicted values of the objective functions for the optimum designs were then again validated using Openfoam high-fidelity analysis code. Results for a Pareto-optimized bladelet on a given blade indicate that more than 4% increase in the coefficient of power at minimal thrust force penalty is possible at off-design conditions compared to the same wind turbine rotor blade without a bladelet.

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Fig. 1

(a) Geometry for baseline Vestas27 wind turbine blade and (b) a sketch of a bladelet at the tip of the Vestas27 blade

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Fig. 2

Dimensions of the computational domain used to analyze each blade + bladelet geometry

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Fig. 3

Results from Openfoam aerodynamic analysis: (a) relative velocity and (b) pressure field on the surface of the Vestas27 blade without a bladelet

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Fig. 4

(a) Relative velocity and (b) pressure field on the surface of the Vestas27 blade with an unoptimized bladelet

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Fig. 5

Workflow of the optimization framework

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Fig. 6

Response surface points for (a) CT versus CP, (b) CM versus CP, and (c) CM versus CT

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Fig. 7

(a) Unoptimized and (b) optimized bladelets

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Fig. 8

(a) Relative velocity and (b) pressure field on the surface of the unoptimized blade + optimized bladelet configuration

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Fig. 9

Variation of the coefficient of power as a function of (a) the tip speed ratio and (b) velocity



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