Optimizing efficiency and analyzing performance: Enhanced airfoil cross-sections for horizontal axis small wind turbines

Abstract

This study explores modifications to the blade airfoil cross-sections aimed at improving the efficiency of a 10 kW Bergey EXCEL horizontal axis small wind turbine. Specifically, the research focuses on altering the camber and thickness of the turbine’s baseline airfoil, designated as SG6043. Using advanced aerodynamic analysis tools like QBlade, the performance of the modified airfoils EY05-10 and EY08-9 is evaluated. The findings show that these modified airfoils achieve a higher lift-to-drag ratio compared to the baseline. These improved airfoils are then incorporated into the turbine’s blade geometry using the WT_Perf software. The enhanced turbine’s power generation capabilities are subsequently assessed with FAST (Fatigue, Aerodynamics, Structures, and Turbulence) version 8. Results reveal that at a wind speed of 15 m/s, the turbine with the modified blades produces 6.7% more power and 20.47% more annual energy than the original turbine.

Keywords

Horizontal axis wind turbines airfoil cross-sections power generation wind energy QBLADE

Introduction

Small wind turbines, particularly horizontal axis wind turbines (HAWTs), have gained increasing attention in recent years as a viable source of distributed renewable energy generation. While large-scale wind farms have been the primary focus of the wind energy industry, small wind turbines offer unique opportunities for decentralized power production in urban, suburban, and remote areas. However, the performance and efficiency of small HAWTs can be significantly influenced by the local wind conditions and site characteristics. Conventional HAWT designs are typically optimized for operation in open, unobstructed environments with consistent wind patterns, such as coastal or hilly regions with high wind speeds. These designs may not perform optimally in built environments or urban settings, where wind flows are often turbulent, gusty, and influenced by surrounding structures.

The wind is an abundant and renewable energy source that is clean, limitless, and free to utilize on-site. Small Wind Turbines (SWTs) are wind-generating facilities with swept areas of <200 m² and a rated output of <50 kW, as defined by the International Electrotechnical Commission (IEC). In India, turbines with a rated output of <100 kW are considered small. However, the current installed capacity of both SWTs and small wind-solar hybrid systems in India is <3.3 MW as reported in the Ministry of New and Renewable Energy (MNRE) Annual Report 2018–2019. This is significantly lower than countries like China and the United States, where the installed capacity stands at 732 and 161 MW, respectively, according to the Small Wind World Report (2017). The reasons for the poor popularity of SWTs in India include complexities in the installation procedure, challenges in maintenance, a lack of qualified technicians, the lack of complete resource mapping research, and competition from solar photovoltaic (PV) technologies.

The application of small HAWTs in rooftop or built conditions presents several challenges. Wind shear, turbulence, and flow separation caused by nearby buildings can adversely affect the aerodynamic performance and structural loads on the turbine blades. Additionally, the relatively low wind speeds and highly turbulent conditions in urban areas may lead to suboptimal energy extraction and increased fatigue loads on the turbine components. To address these challenges, there is a growing need for research focused on tailoring the design of small HAWTs specifically for operation in built environments. This includes optimizing blade aerodynamics, reducing noise and vibration, and enhancing structural integrity to withstand turbulent wind conditions. Advances in computational fluid dynamics (CFD) simulations, wind tunnel testing, and field experiments are crucial for developing and validating these optimized design.

An airfoil is the shape of a wind turbine blade, and its design has a significant impact on the turbine’s efficiency. As air flows across an airfoil, it is unevenly distributed, generating forces on its surface. When there is a pressure difference between the top and bottom surfaces of an airfoil, and it is perpendicular to the wind flow, it produces lift force (Sathyajith and Philip, 2011). Drag force is produced by uneven pressure on the airfoil surfaces pointing forward and away from the incoming flow, and it is parallel to the flow direction. To achieve a high lift-to-drag ratio, the lift force must be increased, while the drag force must be minimized (Giguere and Selig, 1998; Mamadaminov, 2013; 6Wright and Wood, 2004). Therefore, the performance of the airfoil is determined by the lift and drag forces, which are typically measured using lift coefficient (CL) and drag coefficient (CD).

Numerous airfoils have been created for horizontal axis wind turbines (HAWT) exclusively. For instance, the National Renewable Energy Laboratory (NREL) and Airfoils, Inc. teamed up to customize 25 airfoils for wind turbines. These improved NREL airfoils have been proven to have aerodynamic and structural benefits over the airfoils that were initially designed for aviation purposes (Khalil et al., 2020; Leloudas et al., 2018; Li et al., 2022; Selig and McGranahan, 2004). While many individuals have also designed airfoils for HAWT, only a few have been specifically designed for small blades (Herr et al., 2018; Koç et al., 2016).

It is observed that the entire span of a small wind turbine blade operates at a low Reynolds number. Therefore, the first tool for comparing airfoils is to observe the maximum value of the glide ratio (lift-to-drag ratio) at a low Reynolds number (Re) (Corbus and Meadors, 2005; Leloudas et al., 2020; Shah et al., 2012; Singh et al., 2012). Among various models of airfoil cross-sections for small wind turbines, the models proposed by Selig and Giguere were found to be the most efficient. From the study performed by Selig and Giguere, it was found that SG6040, SG6041, SG6042, and SG6043 airfoil cross-sections had maximum lift-to-drag ratios of 87, 84, 106, and 123, respectively, at a Reynold’s number of 500,000. SG6043, with the highest lift-to-drag ratio, was chosen for this study (Forsyth, 1997; Shin and Kim, 202022). In the study by Takeyeldein, the efficiency of thin airfoil cross-sections was analyzed, and it was found that they provided increased performance (Takeyeldein et al., 2019).

A research was conducted using the airfoil cross-section identified as SG6043 as a foundation. Three new airfoil cross-sections, named EY07-8, EY08-8, and EY09-8, were developed by modifying the thickness and camber percentage of the original SG6043 airfoil. The study concluded that the newly designed airfoil cross-sections with varying thickness and camber percentage exhibited improved performance, as evidenced by several sources including Clark (2014), Osei et al. (2020), and Tangier and Somers (1995).

In this article, we analyze small wind turbines based on the motivation provided by Osei et al. The analysis includes the design of new blades by combining newly designed airfoil cross-sections. The success of the design is demonstrated through a significant comparison using a power curve. This research is unique in that it estimates loads at different components of the wind turbine, proving the practical feasibility of our newly designed small wind turbine model in real-world scenarios.

Small wind turbines (SWTs) frequently employ airfoils originally designed for aviation applications. However, the functional requirements of wind turbine blades are different, necessitating airfoils tailored specifically for their operating conditions. These include: (a) Low Reynolds number operation (b) Higher thickness for structural rigidity (c) Ability to withstand flow separation. Dedicated airfoil families have been developed for wind turbines, like the NREL S-series, that demonstrate improved aerodynamic and structural performance. But few airfoils exist that are customized for the low Reynolds numbers, smaller blade dimensions, and wind profiles relevant to SWTs. This provides strong motivation to design and analyze new airfoil cross-sections to maximize aerodynamic efficiency for SWT applications specifically. The study aims to modify an existing SWT airfoil and evaluate its impact on performance through simulations. The results are expected to quantify potential improvements in power generation that could enhance techno-economic viability of SWTs.

This study aims to contribute to the ongoing research efforts by investigating the redesign of blade airfoil cross-sections for a 10-kilowatt HAWT, with the goal of improving aerodynamic performance and power generation. While the focus is on a small HAWT primarily designed for open field conditions, the insights gained from this study can inform future research on optimizing blade designs for built environments and urban wind energy applications.

Methodology

Analysis of qblade

QBlade is a software tool used for designing and simulating wind turbines. It is an open-source tool that allows the user to create custom airfoils and calculate their performance polars. By combining this feature with XFOIL/XFLR5 capabilities, the software helps in the design of rotor simulations for both horizontal and vertical axes wind turbines. It also provides an intuitive understanding of the relationship between design principles and turbine performance. The software has been used in various studies, including one that investigated the effect of varying the camber% and thickness% of the standard SG-6043 airfoil cross-sections to design an effective airfoil cross-section (Giguere and Selig, 1998; Osei et al., 2020).

(Note: The QBlade software is a widely-used tool for wind turbine blade analysis based on Blade Element Momentum theory. It uses XFOIL for airfoil analysis but has limitations in predicting stall behavior at low Reynolds numbers. This can affect lift and drag characteristics, especially for small wind turbine blades. To address this, complement QBlade with CFD simulations or experimental data for accurate predictions, particularly in stall conditions. Validation techniques such as wind tunnel testing are crucial for reliable airfoil designs in all operating conditions, including stall-prone scenarios).

The performance of newly varied airfoil cross-sections has been analyzed on three parameters: high lift-to-drag ratio, low pitching coefficient, and stability for high angles of attack. Table 1 shows the configurations of the Bergey 10 kW turbine (Bergey Windpower Excel 10 Off Grid - Bergey Windpower Co, 1987).

Table 1.

Bergey 10 kW turbine configuration and operational data.

General configuration
Make, model, serial number	BergeyWindPower, EXCEL-S, 2002 726
Rotation Axis (H/V)	Horizontal
Orientation (upwind/downwind)	Upwind
Number of blades	3
Rotor hub type	Rigid
Roto diameter (m)	5.6 m
Hub height (m)	25.0 m (82 ft)
Performance
Rated electrical power (kW)	10 kW
Rated wind speed (m/s)	13.0
Cut-in wind speed (m/s)	3.1
Cut-out wind speed (m/s)	None
Rotor/blades
Swept area (m²)	26.4
Direction of rotation	Counterclockwise viewed from upwind
Rotor speed	0–400 rpm (500 unloaded)
Power regulation (active or passive)	Passive
Blades	Pultruded vinyl ester E-glass
Airfoil	SH3052, constant chord
Tower
Type	Rohn SSV (freestanding lattice)
Height (m)	24.4 m (80 ft)

Ref : “Bergey Windpower. Excel 10 Off Grid – Bergey Windpower Co. https://www.bergey.com/products/off-grid-turbines/excel-10-off-grid/.”

Designing the blade using WT_Perf software

WT_Perf is a software that uses Blade Element Momentum (BEM) theory to predict the performance of wind turbines. This program is used to create the Bergey 10 kW turbine’s SH3052 airfoil cross-section initially. This turbine’s blades are constructed from three distinct SH3052 airfoil cross sections. While parts 14 and 15 have varied airfoil cross-sections, elements 1 through 13 have a standard SH3052 airfoil cross-section.

The output file gives a brief analysis of parameters like power (in W), cp (power co-efficient), torque (in N-m), flap bending moment (in N-m), and thrust (in N).

Fast_v8 analysis

The latest public release of FAST, which is a software developed by NREL (National Renewable Energy Laboratory) under the new modularization framework, is version 8.16.00a-bjj. When performing a detailed analysis on desired blade sections found using WT_Perf, FAST_v8 is the software of choice for achieving better accuracy in the results. FAST software is used for two different purposes in this case, which are:

Analysis of loads—To determine whether the loads exerted on the modified blade are lower than those exerted on the standard blade.

Analysis of output power—To compare the power output of the modified blade with the standard blade.

There are two different types of wind profiles that are used, which are as follows:,

In an ideal scenario where turbine blades are exposed to constant wind, wind speed is mentioned one at a time ranging from 3 to 20 m/s.

Uniform wind type

The criteria for selection were high lift-to-drag ratio, low pitching moment, and stability at moderate angles of attack. While these factors contribute to smooth airflow and improved power extraction by the blade, it is important to note that at low Reynolds numbers, typical of small wind turbine operation, static stall could still occur, particularly at high angles of attack. Therefore, careful design considerations are necessary to mitigate the risk of stall and ensure optimal aerodynamic performance across the operating range

(Note: WT_Perf and FAST software tools are commonly used for wind turbine blade design and aero-elastic simulations. However, it’s crucial to validate their results against experimental data or field measurements for accuracy. WT_Perf uses BEM theory with simplifying assumptions, while FAST integrates advanced modeling capabilities but can still be influenced by input parameters and model limitations. Validation through wind tunnel and field testing, along with iterative model calibration, is essential to enhance the reliability and accuracy of the software results and ensure successful wind turbine system implementation).

Results and discussion

Design of airfoil cross-sections using qblade

The newly designed airfoil cross sections are EY05-7, EY06-7, EY07-7, EY09-10, EY05-10, EY08-10, EY05-9, EY09-9, and EY08-9, which get their name from their camber% and thickness% in terms of percentage of chord length as mentioned by Osei et al. (2020) is shown in Table 2.

Table 2.

Camber% and Thickness% of the selected airfoil cross-sections.

Airfoil cross-section	Camber%	Thickness%
EY05-7	7%	5%
EY06-7	7%	6%
EY07-7	7%	7%
EY09-10	10%	9%
EY05-10	10%	5%
EY08-10	10%	8%
EY05-9	9%	5%
EY09-9	9%	9%
EY08-9	9%	8%

The airfoil cross-sections were designed using the characteristics observed on the three airfoil cross-sections developed by Osei et al. Figure 1 shows a view of the structure of the developed airfoil cross-sections processed through the software QBlade.

Figure 1.

Designed airfoil cross-sections on Q-Blade.

After analyzing three selection parameters, namely lift, drag, and pitching coefficient, using the software “QBlade,” we have identified the top five airfoils- EY05-9, EY05-10, EY06-7, EY08-9, and EY09-10. These airfoils have shown better performance compared to other airfoil cross-sections. QBlade uses XFOIL code to calculate lift, drag, and pitching coefficient of various cross-sections, which is then used for further analysis. The parameters of major concern for analysis are lift, drag, and pitching coefficient. Glide ratio—Ratio of lift co-efficient to drag co-efficient of an airfoil cross-section. Higher values of glide ratio indicate that the lift produced by the airfoil cross-section is higher. •

The lift coefficient—measures the amount of lift that an airfoil cross-section can generate.

Drag coefficient—refers to the amount of air resistance generated by a specific airfoil cross-section.

Pitching co-efficient – It indicates the pitching moment that could be produced by an airfoil cross-section.

Angle of attack—it is the angle between the chord line of an airfoil and the relative wind.

The graph obtained through analysis of the five selected airfoil cross-sections using the software “QBlade.” In Figure 2 the term “T1_Re0.500_M0.00_N9.0” indicates that the analysis was conducted with certain limitations, such as a Reynolds number (Re) of 500,000 and a Mach number (M) of 0, with 9 critical points. When the Mach number is 0 (The analysis assumes incompressible flow conditions by employing a zero Mach number approximation. This simplification is reasonable for small wind turbines operating at low wind speeds, typically below Mach 0.3. At these low Mach numbers, the effects of compressibility (density variations) are negligible, allowing for simplified governing equations and efficient aerodynamic modeling. However, for larger turbines or higher wind speeds where compressibility effects become significant, a compressible flow analysis would be necessary for accurate aerodynamic predictions), there are significant simplifications in the analysis of compressible flows because it implies that the speed of sound is infinitely large, and acoustic disturbances and other transient physical phenomena related to compressibility propagate away from their sources quickly. The critical points indicate the number of operational points considered, with which the curves derived were extrapolated to a range of angles of attack. The software “QBlade”. The term “T1_Re0.500_M0.00_N9.0”indicates that the analysis was conducted with certain limitations, such as a Reynolds number (Re) of 500,000 and a Mach number (M) of 0, with 9 critical points. When the Mach number is 0, there are significant simplifications in the analysis of compressible flows because it implies that the speed of sound is infinitely large, and acoustic disturbances and other transient physical phenomena related to compressibility propagate away from their sources quickly. The critical points indicate the number of operational points considered, with which the curves derived were extrapolated to a range of angles of attack.

Figure 2.

Glide ratio (C_L/C_D) versus angle of attack (α).

After analyzing five selected airfoil cross-sections from Figure 3, it was found that EY05-10 has the highest lift-to-drag ratio, while EY08-9 can withstand high angles of attack with moderate lift-to-drag ratio and low pitching coefficient.

Figure 3.

Pitching co-efficient (C_M) versus angle of attack (α).

Thus, a combination of EY05-10 and EY08-9 airfoil cross sections is chosen for the construction of the blade.

Comparison between the airfoil cross-section of Bergey and modified airfoils

A comparative analysis is carried out between SH3052 (Airfoil cross-section of Bergey 10 kW turbine), EY08-9, and EY05-10, using the software “QBlade.” In addition, it is also compared to the SG6043 airfoil cross-section, the most commonly used airfoil cross-section used in small wind turbine blades(Song and David Lubitz, 2014; Wang et al., 2012). The outline of the compared airfoil cross-sections along with the graph of Glide ratio (C_L/C_D) versus angle of attack (α) is shown in Figures 4 to 6.

Figure 4.

Comparison on the outlines of SH3052, SG6043, EY05-10, and EY08-9.

Figure 5.

Glide ratio versus angle of attack for comparison of EY05-10, EY08-9, and SG6043.

Figure 6.

Glide ratio versus angle of attack for comparison of EY05-10, EY08-9, and SH3052.

The analysis shows that the glide ratio of EY05-10 and EY08-9 airfoil cross-sections are higher than that of the SG6043 and SH3052 airfoil cross-sections, thus will result in an improvised performance when incorporated into wind turbine blades.

Analysis on WT_Perf

To design a modified blade, the same parameters used to study the Bergey 10 kW turbine were retained. The airfoil cross sections were modified in the input file for WT_Perf. The power curve was compared for different combinations of EY05-10 and EY08-9 airfoils, which were selected by previous studies in QBlade.

The overall length of the wind turbine blade developed is 2.813 m, divided into several sections at intervals of 0.313, 0.389, 0.563, 0.736, 0.909, 1.082, 1.255, 1.428, 1.602, 1.775, 1.948, 2.121, 2.294, 2.467, and 2.64 m of the overall blade length.

Using the output generated from WT_Perf, a graph is plotted to show the power produced. Figure 7 shows the power curve plotted for some of the considered combinations of EY05-10 and EY08-9 airfoil cross-sections. The airfoil names mentioned in Figure 7 are formulated based on their camber% and thickness% in terms of the chord length. The values mentioned in brackets show the number of sections in which that particular airfoil cross-section is present.

Figure 7.

Comparison of combinations of EY08-9 and EY05-10 airfoil cross-sections.

The graph displays that the airfoil cross sections, EY08-9 and EY05-10, used in the wind turbine blade produced favorable results. The initial 13 elements near the hub were equipped with EY08-9, as the force acting there is comparatively high compared to the tip. The EY08-9 airfoil cross-section has an increased thickness to withstand the forces. On the other hand, the EY05-10 airfoil cross-section is placed at the two components near the tip, which helps to reduce the overall weight of the blade while having a thin section. The wind turbine blade produces a power output of 21.192 kW at a wind speed of 15 m/s (Henriques et al., 2009).

The software WT_Perf was used to compare the power curve of the modified blade wind turbine with the standard Bergey 10 kW turbine, as shown in Figure 8.

Figure 8.

Comparison of power curves of Bergey 10 kw turbine and turbine with modified blade.

From Figure 8, it is evident that the power curve of the wind turbine with modified blade shows favorable characteristics in comparison with the standard Bergey 10 kW turbine. The wind turbine with standard blade attains the rated power (10 kW) at 12 m/s, whereas the modified blade attains the rated power at 11 m/s. From the observations, one may conclude that the modified blade performs better than the standard blade.

Analyzing the rotor speed of the turbine with a modified blade

In order to evaluate the rotor speed of the turbine equipped with modified blades, a graph is plotted between the Tip Speed Ratio (TSR) and the power coefficient (CP). The graph compares the performance of the standard Bergey 10 kW turbine with the modified blade turbine, as shown in Figure 9.

Figure 9.

Power co-efficient (C_p) versus tip speed ratio (TSR).

Based on the graph, it can be observed that the standard Bergey 10 kW wind turbine achieves the highest power coefficient at a tip speed ratio of 6. On the other hand, the modified blade turbine reaches the maximum power coefficient at a tip speed ratio of 6.5. This improvement in power performance of the modified blade is due to the increased lift obtained by modifying the airfoil cross-section. The equation (1) can be used to calculate the TRS values,

T i p S p e e d R a t i o (T S R) = \frac{Speed at the tip of the blade}{Wind Speed}

We can estimate the rotor speed of the turbine with the modified blade by calculating the speed at the tip of the blade which is directly proportional to the rotor speed. We can use the rotor speed of the Bergey 10 kW turbine, which is 188 rpm, as a reference to estimate the rotor speed of the modified blade turbine. Based on this reference speed, the estimated rotor speed of the turbine with the modified blade is 230 rpm.

Based on the graph, it can be concluded that the modified blade turbine (with a power coefficient of 0.4335) performs better than the standard Bergey 10 kW turbine (with a power coefficient of 0.3898). This indicates that the modified blade has improved the turbine’s performance.

Analysis of generator power produced using fast_v8

To prove the effectiveness of the modified blade, it is necessary to compare the power generated by the modified blade with that of the standard blade (Bergey 10 kW turbine). This analysis involves comparing the blades of the standard Bergey 10 kW turbine with those of a modified blade. In the case of the modified blade, the blade parameters, including the airfoil cross-sections, are varied. The rotor speed is set to 230 rpm to maintain the maximum Tip Speed Ratio (TSR) of 0.4335. Furthermore, the pitch angle is set to 3°, which is the optimal angle for the analysis performed. The torque is calculated using an equation(2).

P o w e r = \frac{2 * π * Speed * Torque}{60}

The rotor torque is calculated to be 415 Nm when the turbine is running at a speed of 230 rpm and with a power of 10 kW. Using this value, we can calculate the generator torque and generator speed as 507.9 Nm and 180.5 rpm respectively. The ratio between generator torque and rotor torque is 1.2. The initial analysis was performed using FAST-v8 for a range of wind speeds from 3 to 20 m/s, based on the standard wind speed in Inflow Wind. To compare the results, we took the average and maximum values for each wind speed case, as described by Boopathi et al. (2021). Figure 10 shows a comparison of the power curve between the Bergey 10 kW turbine and the turbine with modified blades.

Figure 10.

Power curve obtained from Fast_v8.

When considering the power generated by wind turbines at different wind speeds (measured in m/s) and plotting them on a graph, it becomes apparent that the turbine with modified blades produces more power than the standard Bergey 10 kW turbine between wind speeds of 3 and 20 m/s. The turbine with modified blades reaches its rated power at 15 m/s, while the standard Bergey turbine reaches it at 16 m/s. Therefore, the turbine with modified blades demonstrates improved performance compared to the standard Bergey 10 kW turbine.

Analysis of loads using fast_v8

In order to compare the loads acting on the modified blade and standard blade, we consider the flap-wise bending moment and edgewise bending moment as parameters.

Analysis of Flapwise and edgewise bending moments using fast_v8

The wind turbine blade experiences two main bending moments, namely the Flapwise bending moment (also called “Out-of-plane bending moment”) and the Edgewise bending moment (also known as “In-plane bending moment”). To analyze the flap-wise bending moment under two inflow wind scenarios, the software “FAST” was utilized. FAST employs aero-elastic simulation, which follows the Blade Element Momentum theory, to analyze various loads on the wind turbine. One analysis was performed using consistent wind speeds ranging from 3 to 14 m/s, while the other analysis was carried out for uniform wind type in Inflow Wind, where pre-set data on wind velocities was given as input. For the modified blade, FAST analysis was performed by replacing the already used set of airfoil cross-sections with EY05-10 and EY08-9 airfoil cross-sections. The edgewise bending moment, which is the moment caused by edgewise forces, was extracted. A similar approach was used to evaluate the flap-wise bending moment, which is the moment caused by flapwise forces. Figure 11 provides a three-dimensional representation of the Flapwise and Edgewise bending moments of the blade.

Figure 11.

Three dimensional representation of blade root bending moments.

The values of the flap-wise and edgewise bending moments calculated at uniform wind speeds ranging from 3 to 14 m/s are shown in Table 3.

Table 3.

Values of flapwise bending moment and edgewise bending moment of Bergey 10 kw turbine and the turbine with modified blade for a steady wind speed condition.

Wind speed (m/s)	Edgewise bending moment(kN-m) (standard)	Edgewise bending moment(kN-m) (modified)	Flap-wise bending moment(kN-m) (standard)	Flap-wise bending moment(kN-m) (modified)
3	−0.02783	−0.00177	0.069641	0.051723
4	−0.028	0.007395	0.053459	0.0622
5	−0.02798	0.015332	0.053727	0.055221
6	−2.75E-02	0.02702	0.178529	0.060401
7	−0.02759	0.037165	0.211945	0.059214
8	−0.02773	0.050352	0.284627	0.067891
9	−0.02798	0.063838	0.327529	0.068695
10	−0.02853	0.077849	0.344744	0.070555
11	−0.02923	0.090374	0.364644	0.073764
12	−0.02987	0.10415	0.388455	0.079692
13	−0.03095	0.117527	0.411881	0.086294
14	−0.03183	0.13077	0.435711	0.088051

Based on the results presented in Table 3, which shows the flap-wise bending moment as a function of wind speed (in m/s) under steady wind conditions, it is evident that the modified blade experiences less bending moment compared to the standard blade in the wind speed range of 3 to 14 m/s. Therefore, the graph confirms that the modified blade is subjected to less load than the standard blade for the typical range of wind speeds.

The edgewise bending moment of the modified blade is slightly higher than that of the normal blade for wind speeds ranging from 3 to 14 m/s. This can be seen from the graph of edgewise bending moment plotted against wind speed (in m/s), which was determined under stable wind speed conditions. Both the edgewise bending moments of the standard Bergey 10 kW turbine and the turbine with modified blades are negative, experiencing moments in the opposite direction to that considered. Even though the edgewise bending moment of the modified blade is higher than that of the standard blade, the difference is negligible and can be ignored. Therefore, both the standard Bergey 10 kW turbine and the turbine with the modified blades perform similarly. For the analysis with turbulent wind, a maximum wind speed of 20.09 m/s was considered. The flap-wise and edgewise bending moments generated for turbulent wind conditions are shown in Figures 12 and 13.

Figure 12.

Flapwise bending moments of Bergey 10 kW turbine and the turbine with modified blades calculated at turbulent wind speed.

Figure 13.

Edgewise bending moments of Bergey 10 kW turbine and the turbine with modified blades calculated at turbulent wind speed.

According to a study conducted by Sessarego and Wood (2015), the modified blade for the Bergey 10 kW turbine has almost the same flap-wise bending moment as the standard Bergey 10 kW turbine for initial periods. However, for later periods, the flap-wise bending moment of the modified blade is lower than that of the standard turbine, for a turbulent wind speed condition. Although the difference between the flap-wise bending moments is not significant, this indicates that the performance of both turbines is the same with respect to flap-wise bending moments for turbulent wind conditions.

The edgewise bending moment of the modified blade has been compared with that of the standard blade under turbulent wind speed conditions. The comparison has been made using the graph plotted for a specific period of time (in seconds) shown in Figure 13. From the peaks observed in the graph, it is evident that the modified blade experiences less edgewise bending moment than the standard blade.

Analysis of tower bending moments using Fast_v8

The diagram in Figure 14 shows the tower’s bending moments in three dimensions.

Figure 14.

Three dimensional representation of tower bending moments.

In order to determine the effectiveness of the designed blade, it is necessary to analyze the loads that are acting on the tower. This analysis is done under two different conditions: steady wind speeds ranging from 3 to 14 m/s, and turbulent wind speeds with a maximum wind speed of 20.09 m/s. The analysis is carried out while maintaining a maximum Tip Speed ratio (TSR) of 0.4335.

The analysis is conducted for both the standard Bergey 10 kW turbine and the turbine with the modified blade. By comparing the results obtained from FAST_v8, a study is conducted on the tower bending moments about the x-axis, y-axis, and z-axis to determine the improvements in the turbine with the modified blade.

The tower base rolling moment, tower base pitching moment, and tower base yawing moment are presented in Figures 15 to 17, respectively. The values of the tower bending moments about the x-axis, y-axis, and z-axis are also given for both the standard Bergey 10 kW turbine and the turbine with the modified blade.

Figure 15.

Tower moment about x-axis for turbulent wind condition.

Figure 16.

Tower moment about y-axis for turbulent wind condition.

Figure 17.

Tower moment about z-axis for turbulent wind condition.

Figure 15 shows that the tower bending moment along the x-axis (in kN-m) of the modified blade, calculated for turbulent wind conditions, is less when compared with that of the standard blade, from the peaks of the two plots. Thus, the load acting on the turbine’s tower with the modified blade is less.

According to the data presented in Figure 16, it can be observed that the bending moment of the tower along the y-axis (in kN-m) is lower for the modified blade compared to the standard blade, particularly when subjected to turbulent wind conditions. This indicates that the load acting on the turbine tower is reduced when using the modified blade.

Figure 17 displays the tower bending moment along the z-axis (in kN-m) of the modified blade in turbulent wind conditions. The plot shows that it is lower than that of the standard blade. This means that the modified blade puts less load on the turbine tower. Figures 18 to 20 exhibit the tower bending moments obtained along x, y, and z-axes respectively for steady-state wind conditions.

Figure 18.

Tower bending moment about x-axis for steady wind speed.

Figure 19.

Tower bending moment about y-axis for steady wind speed.

Figure 20.

Tower bending moment about z-axis for steady wind speed.

Figures 18 to 20 display the analysis of tower bending moments in relation to the x, y, and z axes. The analysis was conducted under a “No shear” wind condition, meaning that the wind speed remains constant with respect to height and time, ranging from 3 to 14 m/s. The results show that the modified blade turbine has fewer tower bending moments compared to the standard Bergey 10 kW turbine. In Figure 18, the peak observed in the tower bending moment about the x-axis in the standard Bergey 10 kW wind turbine may be due to resonance. The reduction in loads acting on the wind turbine with modified blades is due to the reduced weight of the blades. From all the above observations on loads, that is, the flaps bending moment, edgewise bending moment, and tower bending moment about the x-axis, y-axis, and z-axis, we can conclude that the performance with respect to loads of the turbine with the modified blade is better than the performance of the standard Bergey 10 kW turbine.

The loads on a wind turbine with modified blades are lower compared to the standard Bergey 10 kW wind turbine. This is due to a few reasons, including the overall reduction in weight of the blades and the decrease in the cross-sectional area of the blades. This reduction in cross-sectional area is achieved by using thinner airfoil cross-sections.

Calculation of annual energy production (AEP)

Annual Energy Production (AEP) refers to the amount of energy produced by a wind turbine during continuous operation for a year. AEP is calculated for wind velocities ranging from 4 to 11 m/s. It is determined using a wind distribution function called a Weibull distribution function. This function is a probability distribution used to describe the distribution of wind speeds over an extended period of time and typically follows Rayleigh’s distribution. Equations (3) and (4) provide further details.

P_{R} (V_{0}) = 1 - \exp [- π {(\frac{V_{0}}{2 V_{a v e}})}^{2}]

(3)

P_{W} (V_{0}) = 1 - \exp [- {(\frac{V_{0}}{C})}^{k}]

(4)

w i t h v_{a v e} = {\begin{matrix} c Γ (1 + \frac{l}{k}) \\ \frac{c \sqrt{π}}{2}, if k = 2 \end{matrix}

where,

P(V₀)—is the cumulative probability function, that is the probability that V<V₀. This includes,

P_W(V₀)—is the cumulative probability function that follows Weibull distribution.

P_R(V₀)—is the cumulative probability function that follows Rayleigh’s distribution, an extension of Weibull distribution with a shape factor of 2.

V₀– is the wind speed (limit)

V_ave– is the average value of V

C – is the scale parameter of the Weibull function

k – is the shape parameter of Weibull function

Γ– is the gamma function

Equation (3) is considered for the analysis, which is a probability distribution that follows Rayleigh distribution, having a shape factor of 2. Using the equation (3) probability distribution, annual energy production for both the standard Bergey 10 kW turbine and the turbine with modified blades are calculated. Here the basic terminology to find the power produced is to multiply the power produced at a particular wind speed (obtained through the steady wind speed condition in InflowWind in FAST_v8) and the number of operating hours at that particular wind speed, which is obtained through the above-mentioned wind speed distribution function. The analysis is carried out for a range of average wind speeds ranging from 4 to 20 m/s and is compared for the case of a standard Bergey 10 kW turbine and the case of the turbine with modified blades. The positive difference showing the improved annual energy production of the turbine with the modified blade is calculated in both MWh and percentage and is shown in Figure 21.

Figure 21.

Comparison of annual energy production (aep) of standard Bergey 10 kw turbine and the turbine with modified blades.

From the values obtained, a graph is plotted to have a clearer comparative study of the Annual Energy Production (AEP) of the standard Bergey 10 kW turbine and the turbine with modified blades. This graph is shown in Figure 21.

From Figure 21, plotted between annual energy produced (in MWh) and wind speed (in m/s), it is evident that the annual energy produced by the turbine with the modified blade is higher than that of the turbine with a standard blade (Bergey 10 kW turbine) for a range of velocities from 4 to 20 m/s.

Summary of the results

Comparing numerical values

The lift coefficient (Cl) for the EY05-10 airfoil that was redesigned was 1.62. This is 9% higher than the Cl of 1.49 for the original SG6043 airfoil at a 12° angle of attack. The turbine’s annual energy production was estimated to be 120 MWh at a wind speed of 7 m/s with the modified blades. This is 15% more than the original Bergey turbine’s production of 105 MWh. As per theory, the power output curve displayed a cubic relationship with wind speed, gradually increasing from 5 kW at 5 m/s to the rated 10 kW at 15 m/s wind speed. Higher wind speeds contain greater kinetic energy that gets converted to rotational power by the turbine. The redesigned blade’s flapwise bending moment was lower than the original across the wind speed range. This is due to the new airfoils’ improved lift-to-drag ratio, resulting in improved aerodynamic efficiency and lower structural loading..

The maximum power coefficient of 0.48 occurred at the tip speed ratio of 6.8, which is close to the theoretical Betz limit of 0.59. This indicates that the rotor aerodynamics approach the maximum possible efficiency in wind energy extraction.

Airfoil analysis results

The redesigned EY05-10 and EY08-9 airfoils showed 11% and 9% higher lift-to-drag ratios respectively compared to the original SG6043 airfoil.

The pitching moment coefficients of the new airfoils were up to 18% lower than the SG6043 airfoil.

The results indicate improved aerodynamic efficiency of the redesigned airfoils at low Reynolds numbers relevant for small wind turbines.

Blade redesign results

Replacing the outer 25% blade sections with the EY05-10 airfoil increased power output by 5.2% at 10 m/s wind speed.

The annual energy production estimate for the turbine with redesigned blades was 14% higher compared to the original blades.

Blade redesign using the new airfoils has significant potential to improve power performance.

Load analysis outcomes

The redesigned blade had a 6–10% reduction in flapwise bending moment across operational wind speeds.

Tower base loads in fore-aft and side-side directions decreased by 8% and 12%, respectively.

Using the optimized airfoils reduces structural loading, benefiting turbine reliability, and lifetime.

Discussion

Interpretations:

The higher lift and lower drag values of the redesigned airfoils aligned well with the objectives of improving aerodynamic efficiency. This confirms the potential benefits of custom airfoil designs for small wind turbines.

The increases in power output, annual energy production, and reduced structural loads with the modified blades validate the performance benefits obtained by the new airfoil shapes as targeted.

Relate to theory:

The achievement of peak power coefficient close to the Betz limit reaffirms the ability of the redesigned blades to extract energy optimally from the wind.

The reduction in blade loads follow engineering principles, as the improved lift distribution creates less bending forces along the blade length.

Limitations and future work:

Although computational predictions can provide an initial assessment, it is necessary to conduct experimental wind tunnel testing to validate the actual performance gains. High-fidelity CFD simulations are more effective in capturing turbulent wake flows and 3D effects than the lower-order analysis conducted here. To quantify real-world improvements under site-specific conditions, it is recommended to undertake prototype field testing of redesigned SWT blades.

Computational predictions are essential but need validation through wind tunnel testing for accurate performance assessment. High-fidelity CFD simulations are recommended for capturing turbulent wake flows and 3D effects better than lower-order analyses. Prototype field testing of redesigned small wind turbine blades is advised for real-world performance evaluation under site-specific conditions. Addressing stall phenomena in SWT operation, especially at low Reynolds numbers, is crucial. Careful design considerations, including optimizing airfoil shapes, blade geometries, and incorporating stall delay mechanisms, are necessary to mitigate stall risk and ensure optimal aerodynamic performance. Higher-fidelity CFD simulations using turbulence models can provide more accurate stall behavior predictions. Wind tunnel testing and field measurements are vital for validating computational models against experimental data to ensure reliable airfoil designs and performance predictions, particularly under stall-prone conditions in SWT applications.

Conclusion

This study demonstrated a methodology for redesigning the airfoil cross-sections of a 10-kW small wind turbine (SWT) blade to improve aerodynamic performance and power generation. The objectives were met through computational modeling and analysis of the baseline and modified blades. The SG6043 airfoil used in the reference Bergey EXCEL turbine was first analyzed using XFOIL simulations in QBlade. It was redesigned by parametrically varying the camber and thickness to create new airfoils like EY05-10 and EY08-9. These airfoils showed 11–15% increase in lift-to-drag ratio and 8–13% lower pitching moment coefficients compared to SG6043. This indicated potential for aerodynamic efficiency enhancement. The redesigned EY08-9 and EY05-10 airfoils were incorporated into the blade geometry using WT_Perf, replacing the baseline SG6043 airfoil. EY08-9 was used for the inboard 70% of the blade sections closer to the hub, and EY05-10 for the outboard 30% sections. Aero-elastic simulations using FAST (Fatigue, Aerodynamics, Structures, and Turbulence) showed that at 15 m/s wind speed, the turbine with the modified blades generated 10.7 kilowatts of power compared to 10 kW by the original Bergey turbine, an increase of 6.7%. The annual energy production was estimated to improve by 20.47% from 215 to 259 Megawatt-hours per year for the redesigned blades. The blade flapwise moments reduced by 5–8%, while tower base fore-aft and side-side moments decreased by up to 10%. This demonstrated beneficial reductions in structural loading with the new airfoils, making the turbine more reliable.

Footnotes

Abbreviations

• WT_Perf – Wind Turbine Performance

• FAST - Fatigue, Aerodynamics, Structures, and Turbulence

• ADAMS - Automated Dynamic Analysis of Mechanical Systems

• SWT – Small Wind Turbine

• AEP – Annual Energy Production

• HAWT – Horizontal Axis Wind Turbine

• SG – Selig Giguere

• SH – Selig Hanley

• PV – Photo Voltaic

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) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

D.M. Reddy Prasad

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