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Research Papers: Alternative Energy Sources

Numerical Shape Optimization of a Wind Turbine Blades Using Artificial Bee Colony Algorithm

[+] Author and Article Information
Shahram Derakhshan

School of Mechanical Engineering,
Iran University of Science and Technology,
Narmak, Tehran 16844, Iran
e-mail: shderakhshan@iust.ac.ir

Ali Tavaziani, Nemat Kasaeian

School of Mechanical Engineering,
Iran University of Science and Technology,
Narmak, Tehran 16844, Iran

1Corresponding author.

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received February 26, 2015; final manuscript received July 6, 2015; published online July 30, 2015. Assoc. Editor: Ryo Amano.

J. Energy Resour. Technol 137(5), 051210 (Jul 30, 2015) (12 pages) Paper No: JERT-15-1091; doi: 10.1115/1.4031043 History: Received February 26, 2015

Use of wind turbines is rapidly growing because of environmental impacts and daily increase in energy cost. Therefore, improving the wind turbines' characteristics is an important issue in this regard. This study has two objectives: one is investigating the aerodynamic performance of wind turbine blades and the other is developing an efficient approach for shape optimization of blades. The numerical solver of flow field was validated by phase VI rotor as a case study. First, flow field around the wind turbine blades was simulated using computational flow dynamics (CFD) and blade element momentum (BEM) methods, then obtained results were validated by available experimental data to show an appropriate conformity. Then for yielding the optimal answer, a shape optimization algorithm was used based on artificial bee colony (ABC) coupled by artificial neural networks (ANNs) as an approximate model. Effect of most important parameters in wind turbine, such as twist angle, chord line, and pitch angle, was changed till achieving the best performance. The flow characteristics of optimized and initial geometries were compared. The results of global optimization showed a value of 8.58% increase for output power. By using pitch power regulate, the maximum power was shifted to higher wind speed and results in a steady power for all work points.

Copyright © 2015 by ASME
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References

Figures

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Fig. 1

Written optimization package

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Fig. 2

Designed twist at different sections of blade (a) and 3D blade (b)

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Fig. 3

(a) Modeled rotor and (b) tested rotor

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Fig. 4

Mesh on flow domain

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Fig. 5

Blade to blade view at root, tip, and trailing edge

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Fig. 6

Investigation of power versus mesh number

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Fig. 7

Comparison of experimental power and computed power

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Fig. 8

Comparison pressure coefficients between experimental and numerical in 7 m/s wind speed

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Fig. 9

Comparison pressure coefficients between experimental and numerical in 10 m/s wind speed

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Fig. 10

Comparison pressure coefficients between experimental and numerical in 15 m/s wind speed

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Fig. 11

Comparison of normal force coefficient from CFD calculation and experimental one at different sections

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Fig. 12

Comparison of tangential force coefficient from CFD calculation and experimental one at different sections

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Fig. 13

History of objective function convergence during twist optimization

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Fig. 14

Comparison between numerical results of wind turbine with initial and optimized blade for twist optimization

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Fig. 15

History of objective function convergence during chord size optimization

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Fig. 16

Comparison between numerical results of wind turbine with initial and optimized blade for chord size optimization

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Fig. 17

Comparison between numerical results of wind turbine with initial and optimized blade (a) and optimum pitch angle (b) for chord size optimization

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Fig. 18

Comparison between numerical results of wind turbine with initial and optimized blade blade for twist optimization

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Fig. 19

Comparison of initial numerical normal force coefficient with the numerical results of optimum blade

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Fig. 20

Comparison of initial numerical normal force coefficient with the numerical results of optimum blade

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Fig. 21

Comparison between initial and optimum blade

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Fig. 22

Comparison between relative speed of original and optimal blade at 10 m/s in 30%, 46.7%, 63.3%, 80% and 95% spans, respectively, (a) original blade and (b) optimized blade

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