Aerodynamic performance enhancement and computational methods for H-Darrieus vertical axis wind turbines: Review

Figures & data

Figure 1. Characteristic of wind turbines (Ahmed and Gawad 2016).

Figure 2. Darrieus types VAWT design concepts (Dabachi, Rahmouni, and Bouksour 2020).

Figure 3. Lift-type VAWTs trends (Möllerström et al. 2019).

Figure 4. Fixed and variable pitch VAWTs configuration (Sagharichi, Zamani, and Ghasemi 2018).

Table 1. Comparison of four different pitching strategies for H-Darrieus VAWT (Zhao et al. 2017).

TurbineItems	θ (^o)	FP-VAWT	VP-VAWT Cyclic	VP-VAWT cycloidal	VP-VAWT Modified
AoA	0 (180)	0	0	0	0
	90 (270)	Maximum	Maximum	Approached to maximum	May be max
Pitch angle	0 (180)	0	0	0	0
	90 (270)	0	Maximum	Approached to max	0
Pitch angle curve			Sinusoidal	Near to sinusoidal	Combination of two trigonometric functions
Design effect			The largest growth is limited in azimuths of 90 and 270	The largest growth is limited in azimuths near 90 or 270	The largest value will distribute at four zones for two sides of 90 and 270

Figure 5. Aerodynamic simulations for the test H-Darrieus rotor operating at λ of 4.5 (Soraghan et al. 2013), a) AoA b) Induction Factor c) Tangential Force Coefficient d) Normal Force Coefficient.

Figure 6. Variation AoA vs azimuthal angle for a λ of 1.5. a) high solidity on the variable pitch (Sagharichi, Zamani, and Ghasemi 2018) b) the variation of pitch angle at different azimuth positions vs AoA (Elkhoury, Kiwata, and Aoun 2015).

Figure 7. Instantaneous pressure coefficient through mid-plane of an FP and VP angles VAWT at λ = 1 (Elkhoury, Kiwata, and Aoun 2015).

Figure 8. Instantaneous torque coefficients of H-Darrieus VAWT as a function of azimuth position.

Figure 9. Vortex structure for lower and higher tip speed ratios at different azimuthal positions (θ) (Mukherjee, Jain, and Saha 2016).

Figure 10. Instantaneous moment coefficient for the last turbine revolution for different tip speed ratios using various azimuthal increments (σ = 0.12) (Rezaeiha, Montazeri, and Blocken 2018b).

Figure 11. Airfoil performance evaluations, a) instantaneous rotor torque coefficient as a function of the blade at the midsection azimuth coordinate of NACA0012airfoil blade(Castelli et al. 2013) b) instantaneous best airfoils torque coefficients different family of an airfoil at 4 tip speed ratio (Mohamed, Ali, and Hafiz 2015; Mohamed, Dessoky, and Alqurashi 2019).

Figure 12. Comparative performance of NACA0015 to four S-series airfoils at different azimuth angles (Cao et al. 2018).

Figure 13. The effect of solidity on Darrieus peak efficiency (Kirke and Lazauskas 2011).

Figure 14. Four bar linkage mechanism in H-Darrieus wind turbine a) 2D view (Kiwata et al. 2010), and the 3D view (right) (Sagharichi, Maghrebi, and ArabGolarcheh 2016; Sagharichi, Zamani, and Ghasemi 2018).

Figure 15. Schematics of the over-speed prevention device using double tail vanes for variable pitch VAWT (Yamada et al. 2012).

Figure 16. Sensor and actuating systems layout for individual pitch control system (Hwang et al. 2006).

Figure 17. MLP-ANN variable pitch control system (Abdalrahman, Melek, and Lien 2017).

Figure 18. Staggered arrangement of H-Darrieus turbine in a wind farm a) flow domain b) all turbines rotating in the same direction c) One turbine counters rotating.

Figure 19. Key elements to be considered during wind turbine blade materials selection (Zangenberg, Brøndsted, and Koefoed 2014).

Figure 20. Comparison of the position of natural fibers against synthetic fibers concerning specific tensile strength and stiffness (Ashby 2008).

Figure 21. H-Darrieus-Savonieus Hybrid WT performance (Mohamed 2013). a) Static torque coefficient and hybrid system. b) Torque coefficients for an individual and hybrid turbine.

Figure 22. Cascade model of Darrieus VAWT (Kumar et al. 2017a).

Figure 23. Schematics of vortices model. a) Vortex model filaments in straight-blade (Griffith et al. 2018). b) Strength of different vortices of FP and VP H-Darrieus VAWT (Zhao et al. 2019).

Figure 24. Single-stream tube model (Kumar et al. 2017a).

Figure 25. Multiple stream tube model (Kumar et al. 2017a).

Figure 26. Double multiple stream tube models (Kumar et al. 2017a).

Figure 27. H-Darrieus blade vortex. a) flow streamlines in the tip region, skin friction lines, and z velocity component on the blade suction surface (Balduzzi et al. 2017). b) instantaneous torque at different blade sections (Jiang et al. 2020).

Table 2. Strength and weakness of different analytical models (Batista et al.; Hirsch and Mandal 1987; Islam, Ting, and Fartaj 2008).

Models	Strengths	Limitations
Cascade	No-solution convergence problem Can predict any range of turbine parameters	High computational time Poor in accounting Dynamic stall effect
Vortex	Effectively account flow dynamic stall Have a good agreement with correlation to experimental data.	Expensive computational cost
SST	Very fast prediction	Insufficient predictions for highly loaded VAWT Disagreement with experimental data
MST	Fast computational time Reasonable computations for lightly loaded VAWT	Convergence problem Increasing computational time Disagreement with the field test result
DMST	Offer good agreement with experimental data	Increasing computational time Convergence problems Poor tip loss Consideration Over predictions for high solidity and at high TSR VAWT

Table 3. Accuracy comparison of aerodynamic models (Ferreira et al. 2014).

Models	CT	CP
MST	0.92	0.55
DMST	0.87	0.6
Actuator Cylinder	0.89	0.59
U2DiVA	0.89	0.56
CACTUS	0.86	0.57
ARDEMA2D	0.92	0.63

Figure 28. The flow domain ratio effects on the turbine torque coefficient (Ferreira et al. 2014).

Figure 29. CFD model comparison of power coefficient C_P as a function of TSR and experimental studies results used for H-Darrieus VAWT.

Figure 30. Structural analysis platform of vertical axis wind turbines (VAWTs) (Lin, Xu, and Xia 2019).

Figure 31. Modal analysis of straight-bladed H-Darrieus WT. a) blade deflection b) natural frequency.

Figure 32. Multi-body dynamics of typical VAWT (Verkinderen and Imam 2015). a) FE model of 15 m mast and first three mode shapes. b) Mast, turbine and coupled system natural frequencies for different mast lengths.

Figure 33. The architecture of ANN (Teksin, Azginoglu, and Akansu 2022).

Figure 34. Typical Aeroelastic (FSI) based tool.

Figure 35. Typical System coupling. a) one-way coupling (Wang et al. 2015) (the left side one) b) Two-way coupling (Rafiee, Tahani, and Moradi 2016), (the right side one).

Figure 36. Boundary conditions and computational domain. a) top view b) isometric view.

Table 4. Simulation Parameter.

Parameter	Value	Parameter	Value
Number of blades	3	Air velocity (m/s)	11.2
Blade length (m)	6.1	Turbulence model	SST k-ω and Realizable k-ε
Blade cross-section	S1046	Flow /structural solver	ANSYS fluent/Mechanical 2020R2
Chord (m)	0.07	Fluid-structure domain Coupling	Two-ways/bidirectional
Rotor radius (m)	0.51m	Type of simulation	Unsteady
Blade Material	Aluminum Alloy and E-glass fiber reinforced epoxy composites

Figure 37. Model mesh.

Figure 38. Model grid Independence.

Figure 39. Torque generated in FSI simulation.

Figure 40. Aerodynamic model comparisons.

Figure 41. Total deformation contour. a) Epoxy_Eglass _UD blades b) Aluminum Alloy blades.

Table 5. Parametric studies of H-Darrieus wind turbine Summary

Selected Airfoil	N	C	D	H	λ	U	TM	Findings	Reference
NACA0018	3	0.1	0.4	0.3	< 3	3-12	BEM	DMST model predicts negative Cp at a low aspect ratio (<1.2) and Re below 2 × 105 which cannot obtain in an experiment.	[146]
NACA0015	3	0.152	5			6	BEM	Turbulence wind allows the wind turbine to self-start at low Re and TSR than constant wind.	[168]
NACA0018	3	0.2	4		0.25-5	4	BEM	Blade shape modification (flexible tip), DMST result shows that the turbine generates negative torque for the lower tip speed ratios.	[169]
S1046	3	0.035	1.3	1	2-8	9	Realizable k-ε	S1046 airfoil with the presence cyclonical of wind lens the CP was augmented by +0.00135 than open NACA0015 airfoil H-Darrieus turbine.	[252]
NACA0018	3	0.2	0.8	0.8	0.4-1.5	7	SST k-ω	The power coefficient was improved with the maximum and minimum growth rate of 26.82% at 0.9TSR and 9.02% at 1.5TSR respectively	[195]
NACA0025	3	0.86	1.03	1	2.58	9	SST k-ω	The three-bladed H-rotors were 5% and 15% higher Cp than four and five-bladed rotors respectively.	[62]
S1046	3	0.07	2	1		5	SST k-ω	S1046 was the highest performance Cp 38.5% at 4.3 TSR over other airfoils and can use for wide range of applications.	[52]
NACA0015	2	0.25	1.7	1	2.29	7	SST k-ω	At 140 AoA and 11.90 pitch angle, 20% higher performance at variable pitch than fixed pitch.	[38]
S1046	3	2	1	0.1	2-9	5	SST-k-ω	NACA63415 & NACA64415, shows higher performance (high lift to drag ratio) and large operating ranges over S1046 and others 23s	[12]
NACA0018	2	0.06	1	1	4.5	9.3	U-T-SST	Flow separation was minimum for low solidity high aspect ratio VAWT,	[253]
NACA0015	3	0.42	2.7	3	1-2.5		T-SST	NACA0030 attained higher CP at low TSR, 2blade has higher CP than 3blade VAWT b/c higher solidity leads to large vortex interaction	[65]
NACA0015	3	0.06	1	1	4	7	U-T SST	The Cp was increased by 6.6% at -20 and The change in pitch angle literature the instantaneous loads of the blade.	[37]
NACA0012	3	0.086	1.03	1.03	-	9	SST k-ω	GRF–blade deformations, The inertial contributions of different values of shell thickness were higher than the aerodynamic deformation and maximum at the trailing edge than the leading edge.	[60]
NACA0015	2	0.2225	1.7	1.02	2.29	7	k-ε, SST	The Spanwise pressure effect was higher at the blade tip, and the maximum blade performance was obtained at z/(H/2)=0 which is 50% higher CT than other locations.	[254]
NACA0018	3	0.0246	1.7	1	2-2.5	10	SST-k-ω	Individual variable pitch control system boosted the power coefficient by 25% than the conventional fixed pitch H-d turbine	[71]
NACA0021	2	0.3	3	1.2	2.5	˂10	k-ε-expt.	Aspect ratio and CP were maximum as H/D was higher and the induced drag and spanwise backflow became reduced, hence power performance is improved.	[64]
-	4	0.25	1.70	2	1.2	6	k-ε,SST k-ω	The flow separation was higher at the trailing edge in the upstream regions of 90° < θ < 180, b/c an AoA becomes smaller and its variation range also narrower with the increase of TSR.	[190]
NACA0018	2	0.06	1	-	4.5	9.3	k-ε, SST k-ω	At optimal TSR, the upwind flow has 50% contributions which inherently increase the unsteady nature of H-D, hence introducing flow control methods can improve significant power enhancements. eg, introducing a variable speed controller, a turbine rotating at 65.1rad/s by 4m/s improved up to 168%.	[44]
NACA0012	1	1	-	-	-	Re=	FSI	Under 0-200 AoA, The performance of flexible airfoil blade without the use of pitch control became 4.2% higher than the rigid blade.	[241]
NACA0015	3	0.4	2.5	3	1.25	6	FSI	Flexible (Morphing) blade VAWT provide 9.6% higher power coefficient than fixed blade at the maximum Young’s modules (0.5MPA) for case study sample	[245]
DU06W200	3	0.127	1.168	6		11.4	FRI	The rotor in the 4rad/s case was promising to self-start, and the range of the tower tip displacement during the cycle was about 0.10–0.12m.	[247]

Where: N, C, D, H, σ, λ, U, and TM, U-T, and expt. represents, number of blade, camber(m), rotor diameter(m), highlight(m), solidity, tip speed ratio, upwind velocity(m/s), turbulence model unsteady-transitions and experiment, respectively.

Ahmed, M. F., and A. F. A. Gawad. 2016. “Utilization of wind energy in green buildings,” In 12th International Conference of Fluid Dynamics, Le Méridien Pyramids Hotel pp. 19–20. Cairo, Egypt.

 Google Scholar

Dabachi, M. A., A. Rahmouni, and O. Bouksour. 2020. Design and aerodynamic performance of new floating H-darrieus vertical Axis wind turbines. Materials Today: Proceedings 30:899–904.

 Google Scholar

Möllerström, E., P. Gipe, J. Beurskens, and F. Ottermo. 2019. A historical review of vertical axis wind turbines rated 100 kW and above. Renewable and Sustainable Energy Reviews 105:1–13. doi:10.1016/j.rser.2018.12.022.

 Web of Science ®Google Scholar

Sagharichi, A., M. Zamani, and A. Ghasemi. 2018. Effect of solidity on the performance of variable-pitch vertical axis wind turbine. Energy 161:753–75. doi:10.1016/j.energy.2018.07.160.

 Web of Science ®Google Scholar

Zhao, Z., S. Qian, W. Shen, T. Wang, B. Xu, Y. Zheng, R Wang. 2017. Study on variable pitch strategy in H-type wind turbine considering effect of small angle of attack. Journal of Renewable and Sustainable Energy. 9(5):053302. https://doi.org/10.3390/app8060957

 Web of Science ®Google Scholar

Soraghan, C. E., W. E. Leithead, J. Feuchtwang, and H. Yue. June. 2013. Double multiple streamtube model for variable pitch vertical axis wind turbines,” In 31st AIAA Applied Aerodynamics Conference. https://doi.org/10.2514/6.2013-2802

 Google Scholar

Elkhoury, M., T. Kiwata, and E. Aoun. 2015. Experimental and numerical investigation of a three-dimensional vertical-axis wind turbine with variable-pitch. Journal of Wind Engineering and Industrial Aerodynamics 139:111–23. doi:10.1016/j.jweia.2015.01.004.

 Web of Science ®Google Scholar

Mukherjee, P., S. Jain, and U. Saha, “Influence of Tip Speed Ratio on the Flow Behaviour of a Darrieus Wind Turbine,” in 6th International and 43rd National Conference on Fluid Mechanics and Fluid Power, MNNITA, Allahabad, India, Dec, 2016, pp. 15–17.

 Google Scholar

Rezaeiha, A., H. Montazeri, and B. Blocken. 2018b. Towards accurate CFD simulations of vertical axis wind turbines at different tip speed ratios and solidities: Guidelines for azimuthal increment, domain size and convergence. Energy Conversion and Management 156:301–16. doi:10.1016/j.enconman.2017.11.026.

 Web of Science ®Google Scholar

Castelli, M. R., A. Dal Monte, M. Quaresimin, and E. Benini. 2013. Numerical evaluation of aerodynamic and inertial contributions to Darrieus wind turbine blade deformation. Renewable Energy 51:101–12. doi:10.1016/j.renene.2012.07.025.

 Web of Science ®Google Scholar

Mohamed, M., A. Ali, and A. Hafiz. 2015. CFD analysis for H-rotor Darrieus turbine as a low speed wind energy converter. Engineering Science and Technology, an International Journal 18 (1):1–13. doi:10.1016/j.jestch.2014.08.002.

 Google Scholar

Mohamed, M., A. Dessoky, and F. Alqurashi. 2019. Blade shape effect on the behavior of the H-rotor Darrieus wind turbine: Performance investigation and force analysis. Energy 179:1217–34. doi:10.1016/j.energy.2019.05.069.

 Web of Science ®Google Scholar

Cao, H., X. Wu, H. Ye, S. Hu, L. Lu, and J. Peng. 2018. “Optimization research on lift-type vertical axis wind turbine airfoil by CFD,” In Journal of Physics: Conference Series, 2018. 1064, vol. 1, p. 012072: IOP Publishing. https://iopscience.iop.org/article/10.1088/1742-6596/1064/1/012072

 Google Scholar

Kirke, B., and L. Lazauskas. 2011. Limitations of fixed pitch Darrieus hydrokinetic turbines and the challenge of variable pitch. Renewable Energy 36 (3):893–97. doi:10.1016/j.renene.2010.08.027.

 Web of Science ®Google Scholar

Kiwata, T., T. Yamada, T. Kita, S. Takata, N. Komatsu, and S. Kimura. 2010. Performance of a vertical axis wind turbine with variable-pitch straight blades utilizing a linkage mechanism. Journal of Environment and Engineering 5 (1):213–25. doi:10.1299/jee.5.213.

 Google Scholar

Sagharichi, A., M. J. Maghrebi, and A. ArabGolarcheh. 2016. Variable pitch blades: An approach for improving performance of Darrieus wind turbine. Journal of Renewable and Sustainable Energy 8 (5):053305. doi:10.1063/1.4964310.

 Web of Science ®Google Scholar

Yamada, T., T. Kiwata, T. Kita, M. Hirai, N. Komatsu, and T. Kono. 2012. Overspeed control of a variable-pitch vertical-axis wind turbine by means of tail vanes. Journal of Environment and Engineering 7 (1):39–52. doi:10.1299/jee.7.39.

 Google Scholar

Hwang, I. S., S. Y. Min, I. O. Jeong, Y. H. Lee, and S. J. Kim. 2006. Efficiency improvement of a new vertical axis wind turbine by individual active control of blade motion. In Smart structures and materials 2006: Smart structures and integrated systems, Vol. 6173, San Diego, California, United States: International Society for Optics and Photonics.https://doi.org/10.1117/12.658935

 Google Scholar

Abdalrahman, G., W. Melek, and F.-S. Lien. 2017. Pitch angle control for a small-scale Darrieus vertical axis wind turbine with straight blades (H-Type VAWT). Renewable Energy 114:1353–62. doi:10.1016/j.renene.2017.07.068.

 Web of Science ®Google Scholar

Zangenberg, J., P. Brøndsted, and M. Koefoed. 2014. Design of a fibrous composite preform for wind turbine rotor blades. Materials & Design (1980-2015) 56:635–41. doi:10.1016/j.matdes.2013.11.036.

 Web of Science ®Google Scholar

Ashby, M. F. 2008. The CES EduPack database of natural and man-made materials. In Granta Material Inspiration, 1st ed., Bioengineering. UK: Cambridge University and Granta Design. https://www.grantadesign.com/download/pdf/biomaterials.pdf

 Google Scholar

Mohamed, M. 2013. Impacts of solidity and hybrid system in small wind turbines performance. Energy 57:495–504. doi:10.1016/j.energy.2013.06.004.

 Web of Science ®Google Scholar

Kumar, P. M., S. R. Rashmitha, N. Srikanth, and T.-C. Lim. 2017a. Wind tunnel validation of double multiple streamtube model for vertical axis wind turbine. Smart Grid and Renewable Energy 8 (12):412–24.

 Google Scholar

Griffith, D. T. 2018. Design studies for deep-water floating offshore vertical axis wind turbines . Albuquerque, NM (United States): Sandia National Lab.(SNL-NM). https://doi.org/10.2172/1459118

 Google Scholar

Zhao, Z., D. Su, T. Wang, B. Xu, H. Wu, and Y. Zheng. 2019. A blade pitching approach for vertical axis wind turbines based on the free vortex method. Journal of Renewable and Sustainable Energy 11 (5):053301. doi:10.1063/1.5099411.

 Web of Science ®Google Scholar

Balduzzi, F., J. Drofelnik, A. Bianchini, G. Ferrara, L. Ferrari, and M. S. Campobasso. 2017. Darrieus wind turbine blade unsteady aerodynamics: A three-dimensional Navier-Stokes CFD assessment. Energy 128:550–63. doi:10.1016/j.energy.2017.04.017.

 Web of Science ®Google Scholar

Jiang, Y., C. He, P. Zhao, and T. Sun. 2020. Investigation of blade tip shape for improving VAWT performance. Journal of Marine Science and Engineering 8 (3):225. doi:10.3390/jmse8030225.

 Web of Science ®Google Scholar

Hirsch, I. H., and A. Mandal. 1987. A Cascade Theory for the Aerodynamic Performance of Darrieus Wind Turbines. Wind Engineering 11 (3): 164–175. http://www.jstor.org/stable/43749306

 Google Scholar

Islam, M., D. S.-K. Ting, and A. Fartaj. 2008. Aerodynamic models for Darrieus-type straight-bladed vertical axis wind turbines. Renewable and Sustainable Energy Reviews 12 (4):1087–109. doi:10.1016/j.rser.2006.10.023.

 Web of Science ®Google Scholar

Ferreira, C. S., H. A. Madsen, M. Barone, B. Roscher, P. Deglaire, and I. Arduin. 2014. Comparison of aerodynamic models for vertical axis wind turbines. In Journal of Physics: Conference Series, vol. 524, 012125, Copenhagen, Denmark: 1IOP Publishing. doi:10.1088/1742-6596/524/1/012125.

 Google Scholar

Lin, J., Y.-L. Xu, and Y. Xia. 2019. Structural Analysis of Large-Scale Vertical Axis Wind Turbines Part II: Fatigue and Ultimate Strength Analyses. Energies 12 (13):2584. doi:10.3390/en12132584.

 Web of Science ®Google Scholar

Verkinderen, E., and B. Imam. 2015. A simplified dynamic model for mast design of H-Darrieus vertical axis wind turbines (VAWTs). Engineering Structures 100:564–76. doi:10.1016/j.engstruct.2015.06.041.

 Web of Science ®Google Scholar

Teksin, S., N. Azginoglu, and S. Akansu. 2022. Structure estimation of vertical axis wind turbine using artificial neural network. Alexandria Engineering Journal 61 (1):305–14. doi:10.1016/j.aej.2021.05.002.

 Web of Science ®Google Scholar

Wang, L., A. Kolios, P.-L. Delafin, T. Nishino, and T. Bird. 2015. Fluid structure interaction modelling of a novel 10MW vertical-axis wind turbine rotor based on computational fluid dynamics and finite element analysis, 2015. France, Paris: Annual Event. EWEA.

 Google Scholar

Rafiee, R., M. Tahani, and M. Moradi. 2016. Simulation of aeroelastic behavior in a composite wind turbine blade. Journal of Wind Engineering and Industrial Aerodynamics 151:60–69. doi:10.1016/j.jweia.2016.01.010.

 Web of Science ®Google Scholar