한국항공우주학회지 (Journal of the Korean Society for Aeronautical & Space Sciences)

  • 제47권3호
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  • Pages.177-186
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  • 2019
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  • 1225-1348(pISSN)
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  • 2287-6871(eISSN)
한국항공우주학회 (The Korean Society for Aeronautical and Space Sciences)
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수직축 풍력터빈 성능향상을 위한 풍력타워 최적설계에 관한 연구

Optimum Design of a Wind Power Tower to Augment Performance of Vertical Axis Wind Turbine

  • 투고 : 2019.01.01
  • 심사 : 2019.03.01
  • 발행 : 2019.03.01
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초록

풍력 타워는 수직형 풍력터빈의 성능을 향상시키기 위해 사용되어왔다. 하지만 올바르게 설계되지 않은 풍력 타워는 오히려 풍력터빈의 성능을 저하시킬 수 있다. 따라서 본 연구에서는 풍력 타워의 최적화 연구를 수행하였다. 이를 위하여 다음과 같이 6가지의 설계변수가 선택되었다. 즉, 가이드 벽의 외부 및 내부 반경, 스플리터의 적용 여부, 스플리터의 내부 반경, 가이드 벽의 개수 및 원주각도가 선정되었다. 최적화를 위한 목적함수는 풍력타워 내에 설치된 수직형 풍력터빈에서의 주기적인 평균 토크가 사용되었으며, 최적화 과정에서 지엽적인 최적화 결과를 피하기 위하여 실험계획법, 유전자알고리즘 및 인공신경망기법이 사용되었다. 인공신경망은 세대의 증가에 따라 지속적으로 향상하였으며, 수직 풍력터빈의 성능은 독립운전에 비하여 최적화된 풍력 타워 내에서 두 배 이상 향상되었다.

Wind power tower has been used to augment the performance of VAWT (Vertical Axis Wind Turbine). However, inappropriately designed wind power tower could reduce the performance of VAWT. Hence, an optimization study was conducted on a wind power tower. Six design variables were selected, such as the outer radius and the inner radius of the guide wall, the adoption of the splitter, the inner radius of the splitter, the number of the guide wall and the circumferential angle. For the objective function, the periodic averaged torque obtained at the VAWT was selected. In the optimization, Design of Experiment (DOE), Genetic Algorithm (GA), and Artificial Neural Network (ANN) have been applied in order to avoid a localized optimized result. The ANN has been continuously improved after finishing the optimization process at each generation. The performance of the VAWT was improved more than twice when it operated within the optimized wind power tower compared to that obtained at a standalone.

키워드

참고문헌

  1. Timmer, W. A., and Rooij, R. P. J. O. M. V., "Summary of the Delft University Wind Turbine Dedicated Airfoils," 2003, AIAA-2003-0352.
  2. Grasso, F., "Hybrid Optimization for Wind Turbine Thick Airfoils," 2012, AIAA 2012-1354.
  3. Schubel, P. J., and Crossley, R. J., "Wind Turbine Blade Design," Energies, No. 5, 2012, pp. 3425-3449.
  4. Park, J., Lee, S., Sabourin, T., and Park, K., "A Novel Vertical Axis Wind Turbine for Distributed & Utility Deployment," 2007, Ontario Sustainable Energy Association
  5. Takao, M., Maeda, T., Kamada, Y., Oki, M., and Kuma, H., "A Straight-Bladed Vertical Axis Wind Turbine with a Directed Guide Vane Row," Journal of Fluid Science and Technology, Vol. 3, No. 3, 2008, pp.379-386. https://doi.org/10.1299/jfst.3.379
  6. Isensee, G. M., and Abdul-Razzak, H., "Modeling and Analysis of Diffuser Augmented Wind Turbine," International Journal of Energy Science, Vol. 2, No. 3, 2012, pp.84-88
  7. Phillips, D. G., Richards P. J., and Flay, R. G. J., "CFD Modelling and the Development of the Diffuser Augmented Wind Turbine," Wind and Structures, Vol. 5, 2002, pp.267-276. https://doi.org/10.12989/was.2002.5.2_3_4.267
  8. Chong, W. T., Poh, S. C., Fazlizan, A., and Pan, K. C., "Vertical axis Wind Turbine with Omni-Directional-Guide-Vane for Urban High Rise Application," Journal of Central South University of Technology, Vol. 19, 2012, pp.721-732. https://doi.org/10.1007/s11771-012-1063-9
  9. Chen, L., Ponta, F. L., and Lago, L. I., "Perspectives on Innovative Concepts in Wind-Power Generation," Energy for Sustainable Development, Vol. 15, 2011, pp.398-410. https://doi.org/10.1016/j.esd.2011.06.006
  10. Allaei, D., and Andreopoulos, Y., "Invelox: Description of a New Concept in Wind Power and its Performance Evaluation," Energy, Vol. 69, 2014, pp.336-344. https://doi.org/10.1016/j.energy.2014.03.021
  11. Baek, Y. M., "Design of Guided Vane for Improving the Efficiency of a Vertically Layered Wind Turbine Generator," TR-2017, Odin Energy, 2017.
  12. Cho, S. Y., Choi, S. K., Kim, J. K., and Cho, C. H., "An Experimental Study for Efficient Design Parameters of a Wind Power Tower," Journal of The Korean Society for Aeronautical and Space Sciences, Vol. 46, No. 2, 2018, pp.114-123. https://doi.org/10.5139/JKSAS.2018.46.2.114
  13. Cho, S. Y., Rin, C., Choi, S. K., Kim, J. K., and Park, S. K., "Numerical Analysis on the Performance of Vertical Axis Wind Turbine Affected by the Configuration of the Wind Power Tower," New Renew. Energy, Vol. 11, No. 2, 2015, pp.17-28. https://doi.org/10.7849/ksnre.2015.06.11.2.17
  14. Wang, Z., Xi, G., and Wang, X., "Aerodynamics Design Optimization of Vaned Diffuser for Centrifugal Compressors Using Kriging Model," Proceeding of Asian Joint Conference on Propulsion and Power, China, Beijing, 2006, AJCPP2006-22023.
  15. Shu, X., Gu, C., Xiao, J., and Gao, C., "Centrifugal Compressor Blade Optimization Based on Uniform Design and Genetic Algorithms," Frontiers of Energy and Power Engineering in China, Vol. 2, No. 4, 2008, pp.454-456.
  16. Fan, H. Y., "An Inverse Design Method of Diffuser Blades by Genetic Algorithms," Proceedings Institutes Mech. Engineering(A), Vol. 212, 1998, pp. 261-268. https://doi.org/10.1243/0957650981536781
  17. Pierret, S., and Braembussche, R. A., "Turbomachinery Blade Design Using a Navier-Stokes Solver and Artificial Neural Network," Journal of Turbomachinery, Vol. 121, 1999, pp.326-332. https://doi.org/10.1115/1.2841318
  18. Bonaiuti, D., Arnone, A., Ermini, M., and Baldassarre, L., "Analysis and Optimization of Transonic Centrifugal Compressor Impellers Using the Design of Experimental Technique," GT-2002-30619, 2002.
  19. Bonaiuti, D., and Zangeneh, M., "On the Coupling of Inverse Design and Optimization Techniques for the Multi-objective, Multi-point Design of Turbomachinery Blades," Journal of Turbomachinery, Vol. 131, 2009, 021014-1.
  20. Verstraete, T., Alsalihi, Z., and Braembussche, R. A. V., "Multidisciplinary Optimization of a Radial Compressor for Microgas Turbine Applications," Journal of Turbo- machinery, Vol. 132, 2010, 031004-1.
  21. Bonaiuti, D., Arone, A., Ermini, M., and Baldassarre, L., "Analysis and Optimization of Transonic Centrifugal Compressor Impellers Using the Design of Experiments Technique," Journal of Turbomachinery, Vol. 128, 2006, pp.786-797. https://doi.org/10.1115/1.1579507
  22. Hagan, M. T., and Menhaj. M., "Training Feed-Forward Networks with the Marquardt Algorithm," IEEE Transactions on Neural Networks, Vol. 5, No. 6, 1999, pp.989-993. https://doi.org/10.1109/72.329697
  23. Hagan, M. T., Demuth, H. B., and Beale, M. H., "Neural Network Design," Boston, MA: PWS Publishing, 1996.
  24. Matlab R2013a, MathWorks, Inc.
  25. CFX, v.17, 2017, ANSYS Inc.
  26. Li, C., Zhu, S., Xu, Y. L., and Xiao, Y., "2.5-D Large Eddy Simulation of Vertical Axis Wind Turbine in Consideration of High Angle of Attack Flow," Renewable Energy, Vol. 51, 2013, pp. 317-330. https://doi.org/10.1016/j.renene.2012.09.011
  27. Cho, S. Y., Choi, S. K., Kim, J. K., and Cho, C. H., "Numerical Study to Investigate the Design Parameters of a Wind Tower to Improve the Performance of a Vertical-Axis Wind Turbine," Advances in Mechanical Engineering, Vol. 9, No. 12, 2017, pp.1-12.