Improving the efficiency of a closed-type wind turbine through an integrated approach

Abstract

This paper presents an integrated approach to improve the efficiency of a closed-type wind turbine. The influence of the confuser’s angle of attack on the wind speed in the turbine blades located area has been studied. A computational fluid dynamics (CFD) model of the installation was created using COMSOL Multiphysics software. The contours of speeds and pressures were studied at different wind speeds, as well as under different confuser parameters. Based on the results of the study, a recommendation for the optimal angle of attack of the confuser was made for constructing a closed-type wind turbine, and MXene-based nanomaterials were considered for use in icing prevention systems.

Keywords

wind power plant angle of attack optimal conditions renewable energy sources CFD RANS de-icing MXenes nanocoating

Introduction

Wind energy is one of the fastest-growing areas among various renewable energy sources. Wind power plants are divided into installations with horizontal and vertical axes of rotation. Wind turbines with horizontal axes of rotation are more common due to their high efficiency and are widely used in large-scale and small-scale power generation.

Large wind turbines are used in places where there is open space with relatively high average wind speed and access to the power grid (Wang et al., 2012). On the other hand, such high wind speeds near populated areas are difficult to achieve. Such installations require the use of large towers, so the length of their blades reaches 30–40 m (Kurian et al., 2010). As a result, large-sized wind turbines are not used in residential areas, and instead, low-power wind turbines with a diameter of 3 m to 10 m are used (Tummala et al., 2016). Therefore, various studies are being carried out to increase the efficiency of low-power plants for applications in low wind speed locations (Hasan et al., 2023).

The efficiency of a wind turbine depends on the aerodynamic shapes of the blades. On the other hand, at low wind speeds, wind turbines are not capable of generating energy. In addition, it is necessary to take into account the icing of the turbine, which also reduces its efficiency. To address these issues, it is essential to create effective design elements for the installation that enhance wind velocity in the area where the turbine blades are located, as well as systems to prevent icing that help maintain operational efficiency.

Closed-type wind turbines, due to their higher operating efficiency, can be used in areas with low average annual wind speeds. This is achieved through the use of a confuser and a diffuser in the installation design, which contributes to an increase in the speed of the oncoming airflow in the area where the turbine blades are located (Hashem et al., 2022). Thus, the integrated use of effective design elements and an icing prevention system improves the operation of the plant under various conditions.

Wind turbine blade materials and the effect of icing on installation efficiency

The material of a wind power plant directly affects its cost, efficiency, and durability. During the operation of the wind turbine, it is affected by static, dynamic, and cyclic loads, as well as ultraviolet radiation, which over time can lead to the destruction of the installation. In addition, the tip speed of wind turbine blades can reach 300 km/h. Therefore, the properties of the material used for the blades are very important. The blade must be light and have high rigidity, long service life, and tensile strength.

With the development of wind energy industry, various materials are used in the manufacturing of wind turbine blades, including nanocomposite materials. Composite material is currently widely used in the production of wind turbine blades, which is the reinforcement of fibers in a matrix. Epoxy resin is commonly used as a matrix due to its excellent load-bearing capacity and tensile adhesion strength (Maskepatil et al., 2014).

In addition, E-glass (electric glass), S-glass, carbon fiber, Aarmid fiber, and hybrid fiber are used as reinforcement. E-glass has good mechanical properties and high thermal stability. Glass fibers have moderate rigidity, high strength, and moderate density. Carbon fibers have an excellent combination of high rigidity, light weight, and high strength (Ahmad and Haq, 2012). Aarmid fibers possess the highest strength-to-weight ratio and exceptional strength properties. Various loads, such as static and dynamic, applied to the blade can cause various damages. Therefore, the use of the most effective and durable material is very important (Debel, 2004; Sørensen et al., 2004).

Icing formation is when ice accumulates on the blade surface under certain weather conditions, which will disrupt the installation aerodynamics and reduce the efficiency of energy production, as well as disrupt the load distribution and thus reduce the service life of the wind power plant structural elements (Battisti, 2015; Cattin, 2012).

Engineering analysis of closed-type wind turbine confuser

In recent years, with the development of renewable energy sources and an increase in their share in the energy sector, more and more attention is being paid to increasing the efficiency of renewable energy converters, including wind turbines.

To optimize and increase the performance of wind turbine structural elements, as well as to reduce its cost, computational fluid dynamics (CFD) is used. With the increase in computing power of computers, the use of CFD for engineering analysis and the development of new structural elements of wind turbines have attracted great interest in recent years (Shourangiz-Haghighi et al., 2020).

To improve the energy efficiency during the process of converting wind energy into electrical energy, it is needed to determine the most effective forms and parameters of the structural elements of the installation. The kinetic energy of the wind depends on its speed to the third degree, so even a slight increase in wind speed will have a big effect (Shakenov and Tolemis, 2023). Therefore, in this work, the confuser was analyzed as a structural element of a wind power plant to increase its efficiency, which will help increase the range of wind speeds at which the wind power plant operates.

The wind turbine confuser was analyzed using COMSOL Multiphysics, an engineering analysis program that performs finite element calculations. This method is used in numerical analysis to obtain approximate solutions to engineering problems. Using this method, the governing equations are approximated in each part of the study area, thus the solution area is analytically modeled by discretization. Subsequently, the resulting discrete elements are combined in different ways, which makes it possible to apply this method to objects of any complexity of shape (Jagota et al., 2013). However, due to the appearance of relative motion between the mesh and the material, convective terms arise when determining the time derivatives.

To overcome such emerging difficulties, the Lagrangian description of the medium (LDM) is used. When using this approach, it becomes possible to move grid nodes along with the environment. In this case, these grid nodes will be considered as particles of the corresponding medium. In addition, such a grid changes its shape or is rearranged at each solution step. On the other hand, when solving problems where large deformations occur, the mesh may be subject to excessive distortion, which leads to a loss of calculation accuracy.

There is an arbitrary Langrange-Eulerian description of the medium, which is aimed at overcoming the difficulties that arise when using these approaches separately. In this approach, a reference configuration is selected to reduce mesh distortion and a specific mesh is moved independently of material movement. However, this approach also has limitations in case of large and unexpected deformations of the calculation areas, which also leads to a decrease in calculation accuracy.

To apply the LDM, various methods are used, and one of these methods is PFEM—the particle finite element method (Avancini et al., 2024; Cremonesi et al., 2020). This method takes advantage of particle methods and divides the physical area using a grid. Here the grid nodes move according to the equations of motion, thus the nodes of the previous grid are preserved and behave like particles that have the ability to transfer their momentum and physical properties. If the generated mesh is excessively distorted, a new mesh will be created, which is snapped to the saved nodes of the previous mesh, and a special method is used to find its boundary.

The finite element method with particles is employed to model various physical processes, while various methods are used for the LDM. These include the vortex element method for use in coupled hydroelasticity problems (Dynnikova et al., 2023), and the smoothed particle method SPH for modeling flows where there is a free surface (Mazhar et al., 2021; Saleh et al., 2017). A detailed comparative analysis of these methods is given in (Bravo et al., 2020; Salis et al., 2024).

To simulate flow, the Navier-Stokes system of differential equations is widely used, which provides a general description of the mechanical behavior of the fluid. The Navier-Stokes system of differential equations mainly consists of differential equations for the laws of conservation of momentum and mass, which are based on continuum mechanics and are used in predicting the behavior of fluids. Also an additional equation is used, which ensures the conservation of the system’s total energy, taking into account the temperature of the fluid during its compression and flow.

There are no analytical solutions to the Navier-Stokes differential equations. Some approximations are used to simplify things, but the results obtained may be far from real systems. There is also the issue of the existence and smoothness of the equations mentioned above, for which various methods have been employed (Cai and Zhang, 2024; Cao and Titi, 2011; Diebou, 2024; Zheng and Ke, 2022). Therefore, for complex engineering systems, it is necessary to apply numerical methods to obtain a solution, which is achieved by applying CFD.

Objectives of the present work

The main objective of this research is to conduct an engineering analysis of the wind turbine confuser, with the aim of identifying the most efficient configuration and optimal parameters for increasing wind speed at the turbine blades location. Additionally, the range of operation of the wind power plant will be expanded by reducing its lower threshold of the operating speed.

In order to achieve this objective, the engineering analysis software must use a model of the structural elements that is sufficiently close to the real wind power plant. The grids in the computer model must provide identical and convergent calculation results and take into account all the boundaries and bends of the structure under examination. This will improve the quality of the hydrodynamic calculations and ensure accurate results.

Materials and methods of research

The computational domain, boundary conditions, turbulence model utilized in CFD modeling, and meshing are presented in this section.

Geometry and computational domain

A 3D model of the closed-type wind turbine design and the building roof are shown in Figure 1. The cross-section of the confuser and diffuser is shown in Figure 2 separately. Since this body is a body of rotation and periodic, to simplify calculations, a cross-section of the confuser and diffuser is used. The above model is constructed in the “Geometry” section of the COMSOL Multiphysics engineering analysis software in the middle of the computational domain, the rotation axis of which is horizontal. After this, materials are specified for the current environment and elements of the model under study. Thus, air was chosen as the flowing medium, and iron was chosen for the structural elements of the installation.

Figure 1.

3D model of the closed-type wind turbine design and the building roof.

Figure 2.

Cross-section of the confuser and diffuser.

Boundary conditions and turbulence model

The specific conditions for this study included the inlet and outlet boundaries, with velocities ranging from 5 to 40 m/s at the model inlet and 1 atm at the outlet, and symmetrical walls surrounding the installation’s structural elements. This program simulates fluid flow at various speeds by solving the Navier-Stokes equations in different formulations, allowing for the simulation of low-speed flows, etc. The Reynolds-averaged Navier-Stokes (RANS) equations are used to describe turbulent flows, along with a selection of turbulence models, including the k-ε and the k-ω and SST (Mentera) models. By applying the RANS equations, these equations replace randomly varying flow characteristics, such as speed, density, and pressure with the sum of averaged and pulsation components, resulting in a time-averaged fluid flow description.

For this particular calculation, by describing the turbulent flow was chosen the standard k-ε model. This model transforms the equations of motion into a form that accounts for the influence of average velocity fluctuations and the process of reducing these fluctuations due to its viscosity.

Mesh

By constructing a mesh, there are four methods to partition the model, where each method has its own calibration. These include “general physics,” “fluid dynamics,” “plasma,” and “semiconductor.” After selecting the type of calibration, a predetermined grid size is set. In this case, the grid calibration type “ fluid dynamics ” is selected as the area around the constructed model, and for the structural elements of the installation—the “general physics.” The generated mesh for one of the confuser and diffuser models options is presented in Figure 3. From the figure can be seen that the mesh near and along the confuser and diffuser is refined, allowing for a precise description of flow processes in these critical areas. The mesh was constructed in the form of a triangle, as the model is two-dimensional and the triangle gives the best approximation when splitting. This shape is also convenient for this form of installation design.

Figure 3.

The constructed mesh for one of the confuser and diffuser models options.

The wind velocity converges at a maximum element size of 0.026 m. Further reducing the mesh size only results in a 0.7% relative change between the case of element size 0.026 m and element size 0.01 m. It also results in increasing the computing time. The data on the constructed mesh is given in Table 1.

Table 1.

Parameters of the mesh.

Parameters	Values
Maximum element size	0.026 m
Minimum element size	2.1e−4 m
Maximum element growth rate	1.05
Number of elements	13,860
Curvature factor	0.1

Results and discussion

To determine the optimal shape and parameters of the structural elements of a wind turbine, it is necessary to study them under different conditions.

The analysis of the structural elements of the installation was carried out by changing the angles of attack of the confuser. When carrying out various calculations, their results can be obtained in the form of a variety of charts and graphs for the parameters being studied for their analysis. A diagram of the wind velocity contours for one of the confuser design is shown in Figure 4. It can be seen here that by approaching the middle of the housing, the confuser narrows, and accordingly, the wind speed increases and then its speed begins to decrease as it moves away from the center of the installation. Behind the installation body there is a slight decrease in wind speed with the formation of a turbulent flow due to the influence of near-wall zones.

Figure 4.

Diagram of wind velocity contours along a closed-type wind power plant housing.

Figure 5 shows a pressure loop diagram for this design. It can be seen here that by approaching the middle of the housing, the air pressure decreases and reaches a minimum value in the middle of the housing where the turbine blades are located, then at the outlet of the installation the air pressure increases again. In this zone of minimum air pressure the maximum wind speed is reached.

Figure 5.

A pressure loop diagram along the housing of a wind power plant.

To accurately measure the wind speed in the middle of the housing where the turbine blades are located, it is necessary to build a dependence with the speed values in this area. Figure 6 shows a vertical red line for measuring wind speed data in the turbine blade area. Figure 7 shows a graph of the measured air flow speed in this area. The graph shows that the maximum wind speed is achieved at the edges of the area where the installation blades are located.

Figure 6.

Section for recording the air flow velocity graph.

Figure 7.

Graph of airflow speed at the blades zone of a wind power plant.

During the study, the angles of attack of the confuser changed from 7.97° to 34.99°, and the initial wind speeds changed in the range from 5 m/s to 40 m/s. The values obtained as a result of the study of the confuser are presented in Table 2.

Table 2.

Data obtained from the results of the confuser study.

ϑ₁, m/s	α, °	ϑ_mbz, m/s	ϑ₁, m/s	α, °	ϑ_mbz, m/s
5	7.97	7.33	25	7.97	37.2
	8.84	7.49		8.84	38.1
	9.93	7.43		9.93	37.6
	11.31	7.31		11.31	36.8
	13.13	7.43		13.13	37.6
	15.64	7.04		15.64	35.4
	19.29	7.01		19.29	35.2
	25.02	6.92		25.02	34.8
	34.99	6.91		34.99	34.7
10	7.97	14.8	30	7.97	44.8
	8.84	15.1		8.84	45.8
	9.93	14.9		9.93	45.2
	11.31	14.7		11.31	44.3
	13.13	14.9		13.13	45.2
	15.64	14.1		15.64	42.5
	19.29	14		19.29	42.3
	25.02	13.9		25.02	41.8
	34.99	13.8		34.99	41.7
15	7.97	22.2	35	7.97	52.4
	8.84	22.7		8.84	53.6
	9.93	22.5		9.93	52.9
	11.31	22		11.31	51.8
	13.13	22.5		13.13	52.9
	15.64	21.2		15.64	49.7
	19.29	21.1		19.29	49.5
	25.02	20.8		25.02	48.9
	34.99	20.8		34.99	48.7
20	7.97	29.7	40	7.97	60
	8.84	30.4		8.84	61.5
	9.93	30		9.93	60.6
	11.31	29.4		11.31	59.4
	13.13	30		13.13	60.6
	15.64	28.3		15.64	56.9
	19.29	28.1		19.29	56.6
	25.02	27.8		25.02	56
	34.99	27.7		34.99	55.7

According to the study’s results, the maximum wind speed in the area where the turbine blades are located at various initial wind speeds corresponds to the angle of attack of the confuser of 8.84°. As a result, when planning and сonstructing a wind power plant, it is advisable to keep the confuser’s angle of attack about 9°.

This design is capable of increasing wind speed by 1.5 times. However, ice formation can reduce the efficiency and service life of the wind power plant’s structural elements. Therefore, various icing prevention systems are being developed using different materials. One promising material is the two-dimensional nanomaterial called MXenes.

Studies have shown that using fully exfoliated MXenes, a homogeneous and highly conductive nanocoating can be obtained. The effect of ambient temperature on the electrical properties of the MXene coating was analyzed over the range of −15 to 60°C and showed a consistent increase in electrical resistance by 1.2% per 10°C. The MXene coating resulted in uniform heat distribution across the entire sample and did not show any wire overheating. In addition, the average rise in coating temperature at the same power level and time was 84% higher for MXenes. This resulted in three times faster ice removal compared to fiber-based coatings. The excellent electrical properties and heating characteristics of nanocoatings based on MXenes indicate the promise of their use in full-scale de-icing systems (Monastyreckis et al., 2022). Thus, an integrated approach contributes to the efficient and continuous operation of the wind turbine.

Conclusions

In this study, an engineering analysis of a closed-type wind power plant is carried out. The design of a wind turbine includes a confuser that is specifically designed to increase the speed of the airflow. This element is critical to the overall performance of the wind power plant.

An investigation was conducted to evaluate the impact of various factors on the performance of the wind power installation confuser. This study was conducted for several elements of the installation, such as the housing and the confuser, by changing the angles of attack.

Based on the results of this investigation, the most effective design option for a wind power plant was identified. This design option results in the greatest acceleration of the oncoming airflow and it is recommended that the confuser’s angle of attack be set in the range of 9° for optimal wind power plant performance.

Footnotes

ORCID iD

Kalizhan Shakenov

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research has been/was/is funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. AP19576865 and BR24992873).

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.

Data Availability Statement

Data will be made available on request.*

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