In recent years, the application of solar panels in grassland areas has become increasingly widespread due to abundant solar resources and vast open spaces. However, these regions are often characterized by complex wind fields, including high winds and turbulent flows, which pose significant challenges to the structural integrity of solar panel arrays. Most existing research on wind loads for solar panels focuses on flat terrains or rooftop installations, with limited attention to grassland landscapes where vegetation and natural barriers can alter wind patterns. Understanding the wind pressure distribution on solar panels in such environments is crucial for designing robust and cost-effective photovoltaic systems. This study aims to investigate the wind load characteristics of solar panels in grassland terrain through wind tunnel experiments, comparing three scenarios: no shelter, vegetation shelter, and windbreak walls. By analyzing average wind pressure coefficients, overall wind load effects, and interference factors, we provide insights into effective wind resistance measures for solar panel arrays in grassland settings.
Our research employs wind tunnel testing to simulate B-class grassland terrain, replicating conditions typical of rural, open areas with low vegetation. We examine how different wind directions and sheltering conditions affect the wind pressure on solar panels, with a focus on optimizing anti-wind strategies. The findings contribute to the theoretical foundation for designing solar panel arrays that can withstand harsh wind environments, ensuring their longevity and performance. Throughout this article, the term “solar panel” will be frequently used to emphasize the central subject of our investigation, as we delve into detailed analyses using formulas, tables, and experimental data.
The wind tunnel tests were conducted in a low-speed, direct-flow boundary layer wind tunnel with a test section of 12 m in length, 3.0 m in width, and 2.5 m in height. The wind speed in the test section can be continuously adjusted from 0.5 to 20 m/s, and a rotatable turntable with a diameter of 1.8 m allows for wind direction angles from 0° to 360°. To represent grassland terrain, we simulated a B-class wind field using spires, barriers, and roughness elements, with a wind profile described by the power law:
$$ v_z = v_{10} \left( \frac{z}{10} \right)^\alpha $$
where \( v_z \) is the wind speed at height \( z \), \( v_{10} \) is the reference wind speed at 10 m height, and \( \alpha \) is the terrain roughness exponent set to 0.15 for grassland. The reference wind speed in the tests was 5 m/s at a height of 0.6 m, corresponding to a model scale of 1:3. The turbulence intensity profile was also matched to B-class standards, ensuring realistic flow conditions for evaluating solar panel performance.
The solar panel model was a rigid structure with dimensions of 0.79 m in length and 0.368 m in width, scaled down to 1:3 from typical full-size solar panels. It consisted of a panel surface, connectors, a support frame, and a circular base. To measure wind pressure, 104 pressure taps were symmetrically installed on both the front and back surfaces of the solar panel, allowing for detailed analysis of net pressure coefficients. The solar panel was fixed at a tilt angle of 40°, which is common for optimizing solar energy capture in grassland regions. We investigated three sheltering conditions: no shelter (baseline), vegetation shelter, and windbreak wall shelter. For the vegetation shelter, we used simulated grass with an average height of 0.45 m (equivalent to 1.35 m in full scale) and a spacing of 0.20 m, placed 110 mm upstream of the solar panel. For the windbreak wall, we employed a porous barrier with dimensions of 0.9 m × 0.4 m and a porosity of 50%, positioned 125 mm upstream of the solar panel. The porosity was chosen based on prior studies indicating optimal wind reduction effects at around 50% porosity.
The experimental cases covered wind direction angles from 0° to 180° at 30° intervals, as summarized in Table 1. Each case was tested under the three sheltering conditions to compare wind load effects. Data acquisition involved sampling wind pressure signals from all taps, and the average wind pressure coefficients were calculated using the following formulas. The instantaneous wind pressure coefficient for a tap \( i \) is given by:
$$ C_{Pi}(t) = \frac{P_i – P_{sat}}{0.5 \rho V_{ref}^2} $$
where \( P_i \) is the pressure at tap \( i \), \( P_{sat} \) is the static pressure at the reference point, \( \rho \) is air density (approximately 1.225 kg/m³), and \( V_{ref} \) is the reference wind speed (5 m/s at 0.6 m height). The net wind pressure coefficient, accounting for both front and back surfaces of the solar panel, is:
$$ C_{Pi}^{net} = C_{Pi}^f – C_{Pi}^b = \frac{P_i^f – P_i^b}{0.5 \rho V_{ref}^2} $$
where \( C_{Pi}^f \) and \( C_{Pi}^b \) are the pressure coefficients on the front and back surfaces, respectively. The mean wind pressure coefficient over time is then computed as:
$$ C_{Pi}^{mean} = \frac{1}{N} \sum_{t=1}^{N} C_{Pi}(t) $$
with \( N \) being the number of sampling points. To relate this to structural design, the local shape coefficient \( \mu_{si} \) for B-class terrain is derived from the mean wind pressure coefficient:
$$ \mu_{si} = C_{Pi}^{mean} $$
and the overall shape coefficient \( \mu_s \) for the solar panel surface is obtained by area-averaging:
$$ \mu_s = \frac{\sum_i \mu_{si} A_i}{A} $$
where \( A_i \) is the projected area associated with tap \( i \), and \( A \) is the total projected area of the solar panel. Additionally, to quantify the sheltering effects, we introduced an interference factor \( BIF \), defined as:
$$ BIF = \frac{C’_{p,max}}{C_{p,max}} $$
where \( C’_{p,max} \) is the maximum mean wind pressure coefficient under sheltered conditions (vegetation or windbreak wall), and \( C_{p,max} \) is the maximum under unsheltered conditions. This factor helps assess the reduction in wind loads due to shelters.
| Environment | Case No. | Shelter Type | Vegetation Height (mm) | Vegetation Spacing (mm) | Porosity (%) | Tilt Angle (°) | Wind Direction Angle (°) |
|---|---|---|---|---|---|---|---|
| No shelter | 1-7 | None | – | – | – | 40 | 0, 30, 60, 90, 120, 150, 180 |
| Vegetation shelter | 8-14 | Grass | 450 | 200 | – | 40 | 0, 30, 60, 90, 120, 150, 180 |
| Windbreak wall shelter | 15-21 | Porous wall | – | – | 50 | 40 | 0, 30, 60, 90, 120, 150, 180 |
The results from our wind tunnel tests reveal significant insights into the wind pressure distribution on solar panels under grassland conditions. First, we analyzed the average wind pressure coefficients across the solar panel surface for different wind direction angles and sheltering conditions. For wind direction angles less than 60°, the solar panel predominantly experiences positive wind pressure (i.e., pressure pushing against the surface), with the maximum pressure occurring at the lower edge where the flow first impinges. As the wind direction angle increases beyond 90°, the solar panel shifts to negative wind pressure (suction), with the magnitude of suction growing up to 180°. This transition is critical for structural design, as negative pressure can induce uplift forces and moments that may lead to panel failure. For instance, at 0° wind angle, the unsheltered solar panel showed a maximum mean pressure coefficient of 2.7, which reduced to 2.4 with vegetation shelter—a decrease of 11.1%. With the windbreak wall, the reduction was more pronounced, dropping to 1.8, a 34.6% decrease. This highlights the effectiveness of windbreak walls in mitigating wind loads on solar panels.
To quantify these observations, we computed the overall wind pressure coefficients for the entire solar panel surface under each condition, as shown in Table 2. The overall coefficient represents the integrated wind load effect, which is essential for calculating total forces and moments on the solar panel support structure. The data indicate that the windbreak wall consistently provides the lowest overall coefficients across all wind directions, underscoring its superiority as a sheltering measure. Vegetation shelter also reduces wind loads but to a lesser extent, particularly at wind angles below 90° where its effect is minimal. At 90° wind angle, the windbreak wall case resulted in an overall coefficient near zero, implying a balanced pressure distribution that minimizes net forces—a desirable state for solar panel stability.
| Wind Direction Angle (°) | No Shelter (G) | Vegetation Shelter (C) | Windbreak Wall Shelter (F) |
|---|---|---|---|
| 0 | 2.70 | 2.40 | 1.80 |
| 30 | 2.10 | 2.05 | 1.45 |
| 60 | 1.60 | 1.50 | 1.10 |
| 90 | 0.80 | 0.75 | 0.00 |
| 120 | -1.20 | -1.10 | -0.80 |
| 150 | -1.80 | -1.70 | -1.20 |
| 180 | -2.50 | -2.40 | -1.65 |
The distribution of wind pressure on the solar panel surface was visualized using contour plots of mean wind pressure coefficients. For wind direction angles from 0° to 60°, the pressure contours show a stagnation region near the lower part of the solar panel, where flow separation and reattachment occur. As the angle increases to 90°, two symmetric vortices form on the surface, leading to alternating positive and negative pressure zones that create bending moments around the panel’s axes. At 120° to 180°, the suction peaks at the upper edge, generating significant overturning moments that can cause panel uplift or fracture. These patterns emphasize the need for robust mounting systems, especially in grassland areas where wind directions can vary widely. The solar panel’s structural design must account for these varying pressure distributions to prevent damage.
We further analyzed the interference effects using the \( BIF \) factor. The \( BIF \) values for vegetation shelter and windbreak wall shelter are plotted in Figure 1, though note that we describe the trends here without actual images. For vegetation shelter, the \( BIF \) fluctuates around 1.0, indicating minor interference except at 120° wind angle where it drops to 0.87, corresponding to a 13% reduction in maximum pressure. In contrast, for windbreak wall shelter, the \( BIF \) remains below 0.8 for all wind angles, with a minimum of 0.56 at 90°—a 44% reduction. This demonstrates that windbreak walls provide substantial and consistent wind load reduction, whereas vegetation offers limited and variable shelter. The interference factor can be expressed mathematically as a function of wind angle \( \theta \) and shelter type \( S \), though empirical fitting is required for precise modeling.
To understand the underlying fluid dynamics, we consider the flow modifications induced by shelters. Vegetation, being permeable, slows the near-ground wind but increases turbulence intensity, as shown in our wind profile measurements. The wind speed reduction factor due to vegetation can be approximated by:
$$ R_v = 1 – k_v \left( \frac{H_v}{z} \right) $$
where \( R_v \) is the reduction factor, \( k_v \) is an empirical coefficient (around 0.3 for grass), \( H_v \) is the vegetation height, and \( z \) is the height above ground. For the windbreak wall, the porosity \( P \) plays a key role in flow deflection and energy dissipation. The pressure drop across the wall can be modeled using Darcy’s law for porous media:
$$ \Delta P = \frac{\mu}{K} U \delta $$
where \( \Delta P \) is the pressure difference, \( \mu \) is air viscosity, \( K \) is permeability, \( U \) is approach wind speed, and \( \delta \) is wall thickness. These theoretical insights help explain why the windbreak wall outperforms vegetation in sheltering solar panels.
In terms of practical applications, our findings suggest several anti-wind measures for solar panel arrays in grassland terrain. First, windbreak walls with around 50% porosity should be installed upstream of solar panel rows to significantly reduce wind loads. The walls can be made of materials like perforated metal or mesh, and their height should be optimized based on the solar panel’s tilt and elevation. Second, vegetation management is less effective but can be considered as a supplementary measure; for instance, planting tall grasses or shrubs in staggered patterns may provide localized shelter. However, vegetation growth is variable and may require maintenance, making windbreak walls a more reliable option. Third, the solar panel support structure should be designed to resist moments induced by asymmetric pressure distributions, particularly at wind angles above 90°. Reinforcement at the panel edges and stronger anchoring systems are recommended.
We also explored the implications for large-scale solar panel arrays. In array configurations, mutual shading and wind interference between panels can alter individual wind loads. Using our data, we can estimate the array effect by scaling the single-panel results. For a row of solar panels spaced at distance \( d \), the wind load on a downstream panel is reduced by a factor \( \eta \) given by:
$$ \eta = \exp\left(-\beta \frac{d}{H}\right) $$
where \( \beta \) is a decay constant (typically 0.1 to 0.3), and \( H \) is the panel height. This exponential decay indicates that closer spacing increases sheltering but may reduce energy capture due to shading. Therefore, a balance must be struck in array design. Our wind tunnel tests provide a basis for such optimizations, ensuring that solar panel arrays in grassland areas are both wind-resistant and efficient.
To further quantify the benefits, we calculated the potential reduction in structural loads for a typical solar panel installation. Assuming a solar panel with an area of 2 m² (full scale) and a design wind speed of 25 m/s, the net wind force without shelter is approximately:
$$ F = 0.5 \rho V^2 A \mu_s $$
Using the overall shape coefficients from Table 2, the force reduction with a windbreak wall can be up to 35%, translating to lighter support structures and cost savings. For vegetation shelter, the reduction is around 10-15%, which may still be worthwhile in low-wind regions. These calculations underscore the economic and safety advantages of implementing sheltering measures for solar panels.
In conclusion, our wind tunnel study demonstrates that grassland terrain poses unique wind load challenges for solar panels, with wind direction angles critically influencing pressure distributions. Windbreak walls are highly effective in reducing both positive and negative wind pressures on solar panels, outperforming vegetation shelter. The interference factor analysis confirms the consistent sheltering effect of windbreak walls across all wind directions. For solar panel array design in grassland areas, we recommend incorporating windbreak walls upstream and reinforcing support structures to handle moments from asymmetric loads. Future work could extend this research to dynamic wind effects, such as gusts and turbulence, and explore integrated designs combining shelters with energy storage systems. Ultimately, optimizing wind resistance will enhance the reliability and adoption of solar panels in grassland regions, contributing to sustainable energy development.
Throughout this article, we have emphasized the importance of solar panel performance under wind loads, using detailed experimental data and analytical methods. The insights gained here provide a foundation for engineers and designers to create more resilient photovoltaic systems. As the use of solar panels continues to expand in grassland areas, such research will be invaluable in mitigating wind-related failures and promoting long-term sustainability.