Performance analysis of Savonius wind turbines in different models

Abstract

This study presents experimental results of power performance characterizations for of 12 different Savonius turbine blades. There are three different models and the numbers of each blade types have been selected as 2, 3, 4, and 5. Three different blade types are drawn in a CAD program and all blade models are produced from 3D printer. The experiments are carried out in the subsonic wind tunnel laboratory of the Faculty of Aeronautics and Astronautics at Erciyes University. The wind tunnel has 15 kW motor power to produce wind flow. Test zone inlet and outlet section is 0.57 m × 0.57 m and 0.59 m × 0.59 m respectively. Shaft to shaft type torque meter is mounted between turbine and electric motor. Measurements have been made at wind speeds between 1 and 30 m/s. The performance values of each turbine have been measured. While the 3-bladed turbine showed the highest power coefficient values in the whole study, the maximum value was obtained from the modified helical turbine type.

Keywords

Vertical axis wind turbine Savonius performance wind tunnel

Introduction

Wind energy has been used in various applications since 5000 BC (U.S. Energy Information Administration, 2022). In the 11th century, wind pumps and windmills were used for food production in the Middle East (U.S. Energy Information Administration, 2022). The use of small wind turbines for electricity generation became widespread in the late 1800s and early 1900s (U.S. Energy Information Administration, 2022). The consumption of energy resources has increased due to population increase in the World. Studies on renewable energy have increased significantly because of environmental pollution and increase in energy demand in worldwide. In recent years, wind energy is one of the most important as a source of renewable electricity energy around world (Azman et al., 2015).

Recent studies show that a lot of research groups within the wind energy community started to develop and use fluid-structure coupled high fidelity analysis frameworks (Hsu and Bazilevs, 2012). The wind turbines which can convert the wind energy into electricity have achieved strong development (Mckenna et al., 2016). In general, wind turbines can be classified under two main groups. They have been named into horizontal axis wind turbines (HAWTs) and vertical axis wind turbines (VAWTs), in accordance with the orientation of their rotational axis (Pagnini et al., 2015; Saeidi et al., 2013).

Vertical axis wind turbines (VAWTs) have some advantages than horizontal axis wind turbines (HAWT). The pressure and suction surfaces of VAWT blade are in alternative variation during a rotation cycle. The natural structural features resulting in the variation of angle of attack for VAWT blade are very different from HAWT blade. A significant changing of angle of attack leads to unstable aerodynamic performance. It is the primary reason that VAWT is considered to have a lower power coefficient than HAWT.

The importance of VAWT has long been ignored and underestimated. In the next 20 or 30 years, the power coefficient of VAWT is expected to be equal or higher than that of HAWT (Yang et al., 2017). The VAWT has two main designs which are lift type (Darrieus) and drag type (Savonius), based on which component of aerodynamic force is used as a means of propulsion (Jin et al., 2015).

Savonius VAWT consist of bucket shaped blades which catch the wind and rotate the shaft, VAWTs can easily be mounted on building roofs and have more advantage than HAWTs in areas with turbulent flow. The Darrieus VAWT airfoil blades rotate to shaft with the force of the wind and drive the generator (Chowdhury et al., 2015; Islam et al., 2008; Tekşin and Kurt, 2021).

In the literature, researchers have made many experimental or numerical studies in order to use wind energy and to make this sustainable resource more efficient and they continue these studies rapidly. The power coefficient used to characterize wind turbines is the mechanical power produced by the wind turbine against total wind power available (Kishore and Priya, 2013). Especially savonius wind turbine type has important drawbacks such as low efficiency and high negative torque region. On the other hand, it is one of the main advantages of being easy to start. VAWT analyses have been generally conducted with non-dimensional parameters such as power coefficient, torque coefficient and tip speed ratios (TSR).

Using a validated CFD model, steady wind simulations at U_∞ = 7 m/s were conducted and results have shown a typical performance curve prediction for this particular VAWT scale was examined by Danao et al. (2014). Islam et al. (2008) analyzed several aerodynamic models which are applied for better performance prediction a design analysis of straight-bladed Darrieus-type VAWT. Putri et al. experimental studied to assess the capability of an obstacle located upstream of a Savonius wind turbine to improve the power generated by the rotor. They stated that the obstacle and the Reynolds number have a small influence on the rotational speed of the loaded turbine (Putri et al., 2019).

Akansu et al. (2017) numerically investigated on a blade fixed pitch VAWT using NACA0021, NACA0015, NACA5520, and Clark-Y airfoils as a blade profile to assess its performance. They concluded that NACA5520 had better initial movement and higher average power factor than others.

Here are many studies on increasing efficiency in Savonius turbines (Bai et al., 2019; Chen et al., 2015; Deda Altan et al., 2016; Hassanzadeh and Mohammadnejad, 2019; Jeon et al., 2015; Kothe et al., 2020; Lee et al., 2016; Morshed et al., 2013; Mrigua et al., 2020; Pallotta et al., 2020; Putri et al., 2019; Tian et al., 2018). Hassanzadeh and Mohammadnejad studied on inward and outward overlap ratios overlap ratios of two-blade Savonius turbine. They observed that the maximum power coefficient is in the inwards overlap ratio of 0.2 (Hassanzadeh and Mohammadnejad, 2019). Thiyagaraj et al. (2021) investigated the number of blades with number of blades. They changed the overlap ratios to get more power coefficient. Two blade savonius turbine has presented better performance characteristics than the 3, 4, 5, and 6 blade.

Abdelaziz et al. (2022) both experimentally and numerically investigated the performance increasing using auxiliary blade. They reported an increase in the power coefficient varying between 8% and 13% with the addition of this body. Aboujaoude et al. (2022) used an axisymmetric truncated cone to improve efficiency of the turbine by redirecting the wind. While this structure facilitates the self-start of the turbine, it has reached a value of 0.31 in the maximum power coefficient. Mosbahi et al. (2021) evaluated the efficiency of a twisted Savonius turbine. They used different blade shapes in order to examine effect of twisted, U, V, and W type geometry. According to experimental results, maximum power coefficient obtained with V shape.

Jeon et al. studied experimentally studied the effects of end plates with various shapes and sizes on the aerodynamic performance of helical Savonius wind turbines with twist angles of 180° and two semi-circular buckets. They stated that Savonius wind turbines is applicable to helical Savonius wind turbines for small blockage ratios ranging from 3% to 8.3% (Jeon et al., 2015).

Putri et al. (2019) tested the performance of a small Savonius vertical axis wind turbine equipped with an upstream obstacle to guide the wind direction at 30000 and 90000 Reynolds number. They observed that that the mechanical torque and power generated by the rotor have been strongly affected by the obstacle and the Reynolds number has no significant impact on the rotor performance.

Kothe et al. (2020) numerically and experimentally investigated the aerodynamic performance of a helical Savonius rotor model with 180° twisted blades. They emphasized that the helical turbine, despite having a more complex manufacturing process than the two-stage turbine, presents stable torque and higher power coefficient.

Pallotta et al. (2020) reported wind tunnel measurements on a model of a vertical axis wind turbine (VAWT). They stated that using a careful design of the shape, size and relative positions of the Savonius and Darrieus blades, their performance can be optimized in mid-low wind regimes.

Morshed et al. (2013) experimentally and computationally investigated the feasibility of improving the performance of the vertical-axis Savonius wind turbine. They stated that if the Reynolds number is high, the turbine model without overlap ratio gives better aerodynamic coefficients, and if the Reynolds number is low, the model with moderate overlap ratio gives better results.

Bai et al. (2019) have numerically analyzed the effect of channel width on turbine performance in a wind tunnel. They stated that 2D is the highest performance when the channel width is considered as 2D, 3D, and 4D and the optimal TSR = 1.55 for a wind turbine placed in a 2D-wide channel. Tian et al. (2018) have numerically studied the performance of the Savonius rotor when it was convex and concave. They obtained dimensionless height of the convex side a1 = 0.3936 and dimensionless height of the concave side a2 = 0.2743. Chen et al. (2015) studied the effect of the wind deflector on savonius rotor. They emphasized that power coefficient values increase with using deflector. Marinic-Kragic et al. (2022) used global optimization of Savonius-type VAWT with multiple circular-arc blades using validated 3D computational fluid dynamic model. For novel 2 blade design of savonius turbine was reached 12% improvement compared with classical rotor.

Mrigua et al. (2020) have computationally investigated performance analyze in elliptical multistage Savonius rotor. They concluded that the two-stage rotor is more efficient than others in similar rotor aspect ratio (0.7).

The blade positions, distance and angle affect the Savonius rotor performance. Deda Altan et al. (2016) have numerically and experimentally studied on blade positions and angles in Savonius rotor. Savonius rotor and blades have been produced by 3D printer. They concluded that optimum parameters (1/r) ratio, (s/r), and additional straight blade angle values were 1°, 0.3°, and 135°, respectively.

In this study, the performance of Savonius turbines consisting of three different models and four different blade numbers have been investigated experimentally in wind tunnel set-up produced by 3D printer. All experiments were compared with each other and the design with the highest performance was determined. The modified blade design showed the best coefficient of performance Cp. Although there are different blade structures, performance enhancing or different applications in the literature, this type of study has not been encountered, so this study contributed to the literature.

Experimental description

This section aims at giving a detailed description of the experimental setup and measurement procedures used for the experiments. It consists of theory of turbine, equations used for determining data, subsonic wind tunnel system and uncertainty values about the investigation.

Wind turbine theory

In vertical axis turbines, while the wind force tries to rotate the turbine, the surface area against the wind tries to brake the turbine. While the surface area trying to rotate the turbine should be utilized very much, the surface area tried to be braked should be aerodynamically designed to apply the least reverse torque to the turbine. Figure 1 shows Savonius wind turbine works due to the difference of forces exert on each blade. The blades curvature has less drag force when moving against the wind or F_convex than the blades moving with the wind (Ali, 2013).

Equations

The calculated quantities were combined in order to obtain the performance parameters commonly used in the aerodynamic of wind turbines. Power coefficient (Cp) is expressed as a measure of performance evaluation in turbines and Power coefficient is comparison with tip speed ratio TSR (λ). cp is formulated as engine power divided by wind power.

C_{p} = \frac{P_{m}}{P_{w}}

(1)

P_{m} = \frac{2 π NT}{60}

(2)

Where;

P_m, N, and T are turbine motor power, turbine revolution and torque, respectively.

P_{w} = \frac{1}{2} \cdot ρ \cdot A \cdot V^{3}

(3)

Where; wind power (Pw), density (ρ), swept area of turbine (A),

TSR = \frac{ω R}{V} = (\frac{2 π N}{60}) \times R / V

(4)

α = \frac{H}{D}

(5)

BR = \frac{H \cdot D}{h \cdot w}

(6)

Where;

TSR: Tip-Speed Ratio

BR: Blockage Ratio

R: Radius of the turbine rotor (m)

D: Diameter of the turbine rotor (m)

T: Brake torque (Nm)

N: Number of revolution (rpm)

ρ: Density of air (kg/m³)

A: Swept area (m²) (A = 2RH)

V: Wind velocity (m/s)

α: Aspect Ratio

H: Rotor height

ω: Rotor angular velocity, (rad/s)

h: Height of wind tunnel of test section

w: Width of wind tunnel of test section

Experimental data of the measurement was determined for producing Savonius rotor. In this study, aspect ratio (α) and blockage ratio are 1.33:1, 8.9.2%. This blockage ratio is less than the advised limit according to the literature. Rotor height and diameter are 200 and 150 mm, respectively. TSR values range from 0.05 to 0.7. General description of the turbine was given in Figure 2. The top view of the turbine is given on the left, while the side perspective view is shown on the right side.

The wind tunnel facility

The experiment of the different Savonius blade models was performed in advanced wind tunnel in Erciyes University Faculty of Aviation and Space. Operating speed range is 3–33 m/s (fan speed range 150–1200 rpm), and tunnel turbulence intensity: <1% (in operating speed range). Contraction rate is 6.1. The cross section of test zone is 570 mm × 570 mm and Test zone output cross-section is 590 mm × 590 mm. Test zone expansion angle is 0.3°. Test zone length is 1.8 m. Number of flow regulating sieves are 2 (third sieve can be installed if required). Sieve feature: 20 Mesh, stainless filter wire, wire thickness 0.37 mm, wire spacing 0.9 mm, clearance 54%. Tunnel fan diameter is 1000 mm and fan motor power is 15 kW. Tunnel width is 1710 mm. Tunnel height is 2300 mm. Overall length is 10.6 mm (Figure 3).

Experimental setup of wind turbine is shown in Figure 4. In order to measure the torque values, torque meter is located downside of tunnel under the test section. The power coefficient values were calculated from the measured torque values.

Shaft to shaft torquemeter (Burster brand), with a maximum measuring capacity of 2.5 Nm, is mounted between the turbine shaft and the motor shaft by using two couplings. Programmable Bk Precision DC Electronic Loads can be used to test and evaluate a variety of DC power supplies. Wide operating ranges up to 500 V and 240 A, flexible operating modes and excellent measurement accuracy, this type of load is widely used in DC Power supplies, DC-DC Converters, batteries, fuel cells, etc. makes it very convenient to characterize. An electronic load device with a power capacity of 240 A and 1200 Watt was used in this experiment. Four different types of loads can be given to the model in the wind tunnel: constant voltage, constant current, constant resistance, and constant power. These given parameters are adjusted differently with the desired values.

The velocity measurements in the tunnel were checked in each repetition of the experiments and when a different geometry was placed in the tunnel. It was determined that the wind speed, which was measured compared to the large empty tunnel, decreased. Therefore, in each new experiment, the wind speed measurement was repeated and healthy results were obtained.

Uncertainties

Measurements and calculations of the measured data provide information about the accuracy of the experiments. The ranges and accuracies of velocity, turbine speed, turbine torque are given in Table 1. Calculated uncertainty for power coefficient has been performed using Cline and McClintock method by using the following equation.

Table 1.

Uncertainty of various parameters.

Parameters	Accuracy
Torque meter (D1N1)	±0.01%
Free Stream Velocity (MonoAir500)	±0.1%
Revolution (Cem AT-6)	±0.05%+1 rpm
Density (MonoAir500)	±0.1%
Area (Delta Go)	±0.1
Parameters	Uncertainty (%)
Tip-Speed Ratio (λ)	Between ± 3.2–3.7
Power coefficient (Cp)	Between ± 4.61–4.66

W_{R} = {[{〈 \frac{\partial R}{\partial x_{1}} w_{1} 〉}^{2} + {〈 \frac{\partial R}{\partial x_{2}} w 〉}_{2}^{2} + {〈 \frac{\partial R}{\partial x_{3}} w_{3} 〉}^{2} + \dots + {〈 \frac{\partial R}{\partial x_{n}} w_{n} 〉}^{2}]}^{1 / 2}

(7)

TSR and Cp uncertainties vales have been calculated about 3.7% and 4.63 %, respectively.

Savonius blade design and manufacturing

In this study, 12 different models have been designed in a CAD program and these Savonius models have been manufactured by three-dimensional printer. A 3D printer has enabled the production of Savonius models designed in complex geometries. These Savonius rotors have three different models and four different blades (2, 3, 4, and 5 blades) for each model. Aspect ratio(α) has been selected as 1.33:1 for all models. This ratio has been used by Lee et al. (2016). The first design, a concave geometry and a concave solid modeling that does not change the height, was done for different blade numbers. Figure 5 shows the designing and manufacturing blade model1 for 2, 3, 4, and 5 blade numbers. In the second design, Savonius rotors have designed to be twisted to receive the wind from all angles. Saad et al. (2020) stated that the twisted savonius turbine is more efficient than the non-twisted turbine. So, model2 Savonius rotors have been designed as twisted for four blade and manufactured. Figure 6 depicts the blade of model2s designed and produced helical.

The Savonius rotor, designed to reduce the negative power of the wind, and to do more suitable aerodynamic geometry is shown in Figure 7. So, the helical model has been modified to reduce the wind resistance and the modified blades have been produced by 3D printer as 2, 3, 4, and 5 blades. Also, these modified Savonius rotors are transmitted the wind power to the turbine shaft more efficiently.

Results

In this section, the results obtained from experiments carried out with different type of models. Each models have four variations. Figures 8 to 10 indicate Cp-TSR graphs of savonius wind turbines consisting of straight, helical and modified blade profile, respectively.

Figure 7 shows C_p (%) values versus the TSR values. As seen this figure, the maximum C_p values and maximum voltage values have been obtained 3.21, 5.55, 3.81, and 2.98; 14, 20, 10, and 6 V, for Model1-A, Model1-B, Model1-C, and Model1-D, respectively. The C_p values of Model1-B are approximately 1.86 times higher than Model1-D. While the C_p values for the Model1B vary within the range of 0.45 to 0.7 of the TSR, in Model1-A, Model1-C, and Model1-D, 0.1 to 0.62 of TSR could be measured.

C_p (%) values for Model2 illustrate in Figure 8. As seen this figure, the maximum C_p value has been obtained as 5.6 at Model2-B. The best measurement values of Model2 belong to Model2-B. At 0.2 to 0.3 TSR values, C_p values of Model2-B and Model2-A are close to each other. When the performances of Model2-B and Model1-B are compared, the maximum C_p values are close to each other. However, in Model1-B, between 0.4 and 0.7 of TSR, measurements could be taken from 0.2 to 0.7 in TSR.

Figure 9 depicts C_p (%) values versus the TSR values. According to this figure, the maximum C_p values have been measured at Model3-B. When Model1, Model2 and Model3 have been investigated, the best values obtained at Model3. The best cp values are obtained 3 bladed Savonius models. Initial rotation speeds of Savonius blades are measured as 3.2, 5.5 and 6.4, for Model3-B, Model2-B, and Model1-B, respectively. The maximum C_p values are 6.1, 7.01, 5.15, and 4.02 for Model3-A, Model3-B, Model3-C, and Model3-D, respectively. The worst performance was tested for the 5-bladed models.

Wenehenubun et al. have investigated on number of blades in Savonius turbines. They compared 2, 3, and 4 blades and they obtained the maximum performance in three bladed Savonius turbine (Wenehenubun et al., 2015). When the experimental results obtained were compared with study of Lee et al. (2016), it was seen that maximum Cp values were obtained at similar TSR values. So, experimental results are suitable for literature.

Conclusion

As the TSR value increases, the C_p value increases and starts to decrease after reaching the maximum point.

This study shows the comparison of Cp values of three different blade models by changing the motor frequency values. The results of this study can be summarized as follows:

It has been that Maximum C_p value in model 1 series is Model 1B. It has three blades.

Model 1A, model 3A, and model 4A have more working range but C_p values were obtained low.

It has been that Maximum C_p value in model 2 series is Model 2B. It has three blades.

Model 2B has more working range than model 1B.

It has been that Maximum C_p value in model 3 series is Model 3B. It has three blades as in Model 1 and Model 2

Model 3B has more working range than all blade models

The best performance results in the number of blades (2, 3, 4, and 5) were determined in the 3-blade model.

These results show that Model 3 more efficient than Model 1 and Model 2.

Consequently, to increase the performance of Savonius turbines and to decrease the negative torque aerodynamic structure, aspect ratio, TSR, attack angle and etc. are very important. In this study, importance of aerodynamic structure has been emphasis. In the future studies, different vertical axis turbines can be improved and this study can be compared with the new the aerodynamic structural Savonius wind rotors.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by BAP (Scientific Research Projects) Erciyes University, Republic of Turkey (BAP project code number of 8657). Also, the authors would like to thanks the Scientific and Technological Research Council of Turkey (TUBITAK) under project No. 315M478 for funding the research Project.

ORCID iD

Teksin Suleyman

References

Abdelaziz

Nawar

MAA

Ramadan

, et al. (2022) Performance improvement of a Savonius turbine by using auxiliary blades. Energy 244: 122575.

Aboujaoude

Beaumont

Murer

, et al. (2022) Aerodynamic performance enhancement of a Savonius wind turbine using an axisymmetric deflector. Journal of Wind Engineering and Industrial Aerodynamics 220: 104882.

Akansu

Dagdevir

Kahraman

(2017) Numerical investigation of the effect of blade airfoils on a vertical axis wind turbine. Journal of Thermal Science and Technology 37(1): 115–125.

Ali

(2013) Experimental comparison study for Savonius wind turbine of two and three blades at low wind speed. International Journal of Modern Engineering Research 3(5): 2978–2986.

Azman

Akyurek

Akcan

, et al. (2015) Turkey’s new energy source: Wind energy and it’s regional capacity. The Journal of MacroTrends in Energy and Sustainability 3(1): 46–57.

Bai

Chan

Zhu

, et al. (2019) A numerical study on the performance of a Savonius-type vertical-axis wind turbine in a confined long channel. Renewable Energy 139(139): 102–109.

Chen

C-A

Huang

Chen

(2015) Novel Plant Development of a parallel matrix system of Savonius wind rotors with wind deflector. Journal of Renewable and Sustainable Energy 7: 013135.

Chowdhury

Mustary

Loganathan

, et al. (2015) Adjacent wake effect of a vertical axis wind turbine. Procedia Engineering 105: 692–697.

Danao

Edwards

Eboibi

, et al. (2014) A numerical investigation into the influence of unsteady wind on the performance and aerodynamics of a vertical axis wind turbine. Applied Energy 116: 111–124.

10.

Deda Altan

Altan

Kovan

(2016) Investigation of 3D printed Savonius rotor performance. Renewable Energy 99: 584–591.

11.

Hassanzadeh

Mohammadnejad

(2019) Effects of inward and outward overlap ratios on the two-blade Savonius type of vertical axis wind turbine performance. International Journal of Green Energy 16(15): 1485–1496.

12.

Hsu

Bazilevs

(2012) Fluid–structure interaction modeling of wind turbines: Simulating the full machine. Computational Mechanics 50(6): 821–833.

13.

Islam

Ting

Fartaj

(2008) Aerodynamic models for Darrieus-type straight-bladed vertical axis wind turbines. Renewable and Sustainable Energy Reviews 12(4): 1087–1109.

14.

Jeon

Jeong

Pan

J-K

, et al. (2015) Effects of end plates with various shapes and sizes on helical Savonius wind turbines. Renewable Energy 79: 167–176.

15.

Jin

Zhao

Gao

, et al. (2015) Darrieus vertical axis wind turbine: Basic research methods. Renewable and Sustainable Energy Reviews 42(1): 212–225.

16.

Kishore

Priya

(2013) Design and experimental verification of a high efficiency small wind energy portable turbine (SWEPT). Journal of Wind Engineering and Industrial Aerodynamics 118: 12–19.

17.

Kothe

Möller

Petry

(2020) Numerical and experimental study of a helical Savonius wind turbine and a comparison with a two-stage Savonius turbine. Renewable Energy 148: 627–638.

18.

Lee

Lim

(2016) Effect of twist angle on the performance of Savonius wind turbine. Renewable Energy 89: 231–244.

19.

Marinic-Kragic

Vučina

Milas

(2022) Global optimization of Savonius-type vertical axis wind turbine with multiple circular-arc blades using validated 3D CFD model. Energy 241: 122841.

20.

Mckenna

Leye

POVD

Fichtner

(2016) Key challenges and prospects for large wind turbines. Renewable and Sustainable Energy Reviews 53: 1212–1221.

21.

Morshed

Rahman

Molina

, et al. (2013) Wind tunnel testing and numerical simulation on aerodynamic performance of a three-bladed Savonius wind turbine. International Journal of Energy and Environmental Engineering 4(1): 18.

22.

Mosbahi

Lajnef

Derbel

, et al. (2021) Performance improvement of a Savonius water rotor with novel blade shapes. Ocean Engineering 237: 109611.

23.

Mrigua

Toumi

Zemamou

, et al. (2020) CFD investigation of a new elliptical-bladed multistage Savonius rotors. International Journal of Renewable Energy Development 9(3): 383–392.

24.

Pagnini

Burlando

Repetto

(2015) Experimental power curve of small-size wind turbines in turbulent urban environment. Applied Energy 154: 112–121.

25.

Pallotta

Pietrogiacomi

Romano

(2020) HYBRI – A combined Savonius-Darrieus wind turbine: Performances and flow fields. Energy 191: 116433.

26.

Putri

Yuwono

Rustam

, et al. (2019) Experimental studies on the effect of obstacle upstream of a Savonius wind turbine. SN Applied Sciences 1(10): 1216.

27.

Saad

El-Sharkawy

Ookawara

, et al. (2020) Performance enhancement of twisted-bladed Savonius vertical axis wind turbines. Energy Conversion and Management 209: 112673.

28.

Saeidi

Sedaghat

Alamdari

, et al. (2013) Aerodynamic design and economical evaluation of site specific small vertical axis wind turbines. Applied Energy 101: 765–775.

29.

Tekşin

Kurt

(2021) Investigation of the solidity ratio in a horizontal wind turbine. Energy, Environment and Storage 1: 11–16.

30.

Thiyagaraj

Rahamathullah

Anbuchezhiyan

, et al. (2021) Influence of blade numbers, overlap ratio and modified blades on performance characteristics of the savonius hydro-kinetic turbine. Materials Today Proceedings 46: 4047–4053.

31.

Tian

Mao

Zhang

, et al. (2018) Shape optimization of a Savonius wind rotor with different convex and concave sides. Renewable Energy 117(117): 287–299.

32.

U.S. Energy Information Administration (2022) Today in energy. Available at: https://www.eia.gov/energyexplained/wind/history-of-wind-power.php (accessed 1 June 2021).

33.

Wenehenubun

Saputra

Sutanto

(2015) An experimental study on the performance of Savonius wind turbines related with the number of blades. Energy Procedia 68(68): 297–304.

34.

Yang

Zhang

, et al. (2017) Investigation on aerodynamics and active flow control of a vertical axis wind turbine with flapped airfoil. Journal of Mechanical Science and Technology 31: 1645–1655.