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Assessment of Wind Fin Performance Run by Mixed Flows: Experimental and Numerical Investigation

  • Research Article-Mechanical Engineering
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Abstract

Wind energy considers an important source for a clean power generation. Several problems in the wind-power generation are due to its uncertainty the sudden change in both wind speed rates and direction. Especially, for small wind power generation system, when wind turbines are connected to a small system or isolated grid, the output power fluctuates from time to time. More so, the need for a new wind blade design that works at low air velocities and different direction wind currents requires further investigation. In this work, the numerical and experimental analysis of mixed flows turbine, the possibility of air currents with horizontal and vertical directions on rotating the proposed models was studied. Firstly, two models of a mixed flows turbine were designed and fabricated for experiments. The experiments were conducted to test two important parameters; inlet velocity at 0.8, 1.4, 2.8, and 4.3 m/s, and yaw angles at 45° and 70°, respectively. Secondly, the modeling has been conducted in the environment of CFD, and the turbine system simulation utilized a SST k-ω model to solve and post process the problem. The results can be drawn from the analysis: the characteristics of the mixed flows turbine have the best self-starting and the lower-starting torque as standard for developing the turbine; the starting torque is dependent on the yaw angle for the blade, in which the wind turbine with a large yaw angles for blades is needed to the smaller starting torques; also the output power increased by increasing the wind velocity.

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Abbreviations

Po :

Output power, [watt]

To :

Torque, [N.m]

F :

Thrust force, N

T :

Reaction force, N

ω :

Angular speed [rad/s]

CP :

Power coefficient [−]

CT :

Torque coefficient [−]

N :

Speed [r.p.m]

C l :

Lift coefficient

C g :

Drag coefficient

Uw :

Wind velocity, [m/s]

Ub :

Diesel axial velocity, m/s

α :

Yaw angle (fixing blade angle) [deg]

τij :

Average shear stress

Sui :

Centrifugal and Coriolis force

ρ :

Density, kg/m3

μ :

Dynamic viscosity, kg/m s

λ :

Entry angle [deg]

δ :

Tip speed ratio

r :

Rotor radius [m]

References

  1. Chong, W.T.; Fazlizan, A.; Poh, S.C.; Pan, K.C.; Hew, W.P.; Hsiao, F.B.: The design simulation and testing of an urban vertical axis wind turbine with the omni-direction-guide-vane. Appl. Energy 112, 601–609 (2013)

    Article  Google Scholar 

  2. Toshimitsu, K.; Kikugawa, H.; Sato, K.; Sato, T.: Experimental investigation of performance of the wind turbine with the flanged-diffuser shroud in sinusoid ally oscillating and fluctuating velocity flows. Open J. Fluid Dyn. 2(4), 215–221 (2012)

    Article  Google Scholar 

  3. Dragomirescu, A.: Performance assessment of a small wind turbine with cross flow runner by numerical simulations. Renew. Energy 36, 957–965 (2011)

    Article  Google Scholar 

  4. Diniar, M.K.; Dominicus, D.P.T.; Budi, S.: Experimental investigation on performance of cross flow wind turbine as effect of blades number. AIP Conf. Proc. 1931, 030045 (2018)

    Google Scholar 

  5. Petru, T.; Thiringer, T.: Modeling of wind turbines for power system studies. IEEE Trans. Power Syst. 17(4), 1132–1139 (2002)

    Article  Google Scholar 

  6. Rasekh, S.; HosseiniDoust, M.; KarimianAliabadi, S.: Accuracy of dynamic stall response for wind turbine airfoils based on semi-empirical and numerical methods. J. Appl. Fluid Mech. 11(5), 1287–1296 (2018)

    Article  Google Scholar 

  7. Bianchi, F.D.; Mantz, R.J.; Christiansen, C.F.: Gain scheduling control of variable-speed wind energy conversion systems using quasi-LPV models. Control. Eng. Pract. 13, 247–255 (2005)

    Article  Google Scholar 

  8. Eisenhut, C.; Krug, F.; Schram, C.; Klockl, B.: Wind-turbine model for system simulations near cut-in wind speed. IEEE Trans. Energy Convers. 22(2), 414–420 (2007)

    Article  Google Scholar 

  9. Ekanayake, J.B.; Holdsworth, L.; Wu, X.; Jenkins, N.: Dynamic modeling of doubly fed induction generator wind turbines. IEEE Trans. Power Syst. 18(2), 803–809 (2003)

    Article  Google Scholar 

  10. Bolin, K.; Bluhm, G.; Eriksson, G.; Nilsson, M.E.: Infrasound and low frequency noise from wind turbines: exposure and health effects. Environ. Res. Lett. 6, 035103 (2011)

    Article  Google Scholar 

  11. Dahne, M.; Gilles, A.; Lucke, K.; Peschko, V.; Adler, S.; Krügel, K.; Sundermeyer, J.; Siebert, U.: Effects of pile-driving on harbour porpoises (Phocoenaphocoena) at the first offshore wind farm in Germany. Environ. Res. Lett. 8, 025002 (2013)

    Article  Google Scholar 

  12. Abanteriba, S.; Kosasih, B.; Tondelli, A.: Experimental study of shrouded micro-wind turbine. Procedia Eng. 49, 92–98 (2012)

    Article  Google Scholar 

  13. Aranake, A.C.; Lakshminarayan, V.K.; Duraisamy, K.: Computational analysis of shrouded wind turbine configurations using a 3-dimensional RANS solver. Renew. Energy 75, 818–832 (2015)

    Article  Google Scholar 

  14. Noura, B.; Dobrev, I.; Kerfah, R.; Massouh, F.; Khelladi, S.: Investigation of the rotor wake of horizontal axis wind turbine under yawed condition. J. Appl. Fluid Mech. 9(6), 2695–2705 (2016)

    Article  Google Scholar 

  15. Baoqing, X.; Tian, D.: Simulation and test of the blade models output characteristics of wind turbine. Energy Procedia 17, 1201–1208 (2012)

    Article  Google Scholar 

  16. Djavareshkian, M.H.; LatifiBidarouni, A.; Saber, M.R.: New approach to high fidelity aerodynamic design optimization of a wind turbine blade. Int. J. Renew. Energy Res. 3(3), 725–735 (2013)

    Google Scholar 

  17. Peter, J.; Schubel, R.; Crossley, J.: Wind turbine blade design. Energies 5, 3425–3449 (2012)

    Article  Google Scholar 

  18. Jureczko, M.; Pawlak, M.; Mezyk, A.: Optimization of wind turbine blades. J. Mater. Process. Technol. 167, 463–471 (2005)

    Article  Google Scholar 

  19. Yurdusev, M.A.; Ata, R.; Cetin, N.S.: Assessment of optimum tip speed ratio in wind turbines using artificial neural networks. Energy 31, 2153–2161 (2006)

    Article  Google Scholar 

  20. Peter, J.S.; Richard, J.C.: Wind turbine blade design. Energies 5, 3425–3449 (2012)

    Article  Google Scholar 

  21. Atmaca, M.; Girgin, I.; Ezgi, C.: CFD modeling of a diesel evaporator used in fuel cell systems. Int. J. Hydrogen Energy 41(14), 6004–6012 (2016)

    Article  Google Scholar 

  22. Atmaca, M.; Çetin, B.; Yılmaz, E.: CFD analysis of unmanned aerial vehicles (UAV) moving in flocks. Acta Phys. Pol. A 135, 694–696 (2019)

    Article  Google Scholar 

  23. Atmaca, M.: Wind tunnel experiments and CFD simulations for gable-roof buildings with different roof slopes. Acta Phys. Pol. A 135, 690–693 (2019)

    Article  Google Scholar 

  24. Atmaca, M.; Ezgi, C.: Three-dimensional CFD modeling of a steam ejector. Energy Sources Part A: Recov. Util. Environ. Eff. (2019). https://doi.org/10.1080/15567036.2019.1649326

    Article  Google Scholar 

  25. Shojaeefard, M.H.; Tahani, M.; Ehghaghi, M.B.; Fallahian, M.A.; Beglari, M.: Numerical study of the effects of some geometric characteristics of a centrifugal pump impeller that pumps a viscous fluid. Comput. Fluids 60, 61–70 (2012)

    Article  Google Scholar 

  26. Mojtaba, T.; Ali, R.; Alibakhsh, K.; Mehdi, M.; Mojtaba, M.: Design and numerical investigation of savories wind turbine with discharge flow directing capability. Energy 130, 327–338 (2017)

    Article  Google Scholar 

  27. Sarah, A.; Sattar, A.; Abdul Hassan, A.K.: Optimization and experimental investigation of savonius wind turbine performance at low wind speed condition. Int. J. Mech. Mechatron. Eng. 20(5), 1–15 (2020)

    Google Scholar 

  28. Nawfal, M.A.; Abdul Hassan, A.K.; Sattar, A.: Effect of conventional multistage savonius wind turbines on the performance of the turbine at low wind velocity. J. Adv. Res. Dyn. Control Syst. 11(11), 229–239 (2019)

    Article  Google Scholar 

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Acknowledgements

Authors are grateful to University of Technology/Baghdad-Iraq for the support by Center of Renewable and Generation Energy.

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Authors and Affiliations

  1. Mechanical Engineering Department, University of Technology, Baghdad, Iraq

    Hasanain A. Abdul Wahhab, Sattar Aljabair & Sadoon K. Ayed

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  1. Hasanain A. Abdul Wahhab
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  2. Sattar Aljabair
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  3. Sadoon K. Ayed
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Correspondence to Hasanain A. Abdul Wahhab.

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Abdul Wahhab, H.A., Aljabair, S. & Ayed, S.K. Assessment of Wind Fin Performance Run by Mixed Flows: Experimental and Numerical Investigation. Arab J Sci Eng 46, 12077–12088 (2021). https://doi.org/10.1007/s13369-021-05843-w

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  • DOI: https://doi.org/10.1007/s13369-021-05843-w

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