In recent years, the solar energy industry has increasingly focused on desert and Gobi regions for the deployment of large-scale photovoltaic power plants. These areas offer abundant solar radiation and vast land resources, making them ideal for harnessing clean energy. However, such environments are characterized by active surface wind-sand flows, frequent sandstorms, and severe wind erosion and sand deposition, which pose significant challenges to the stability and efficiency of solar panel installations. Understanding the interactions between solar panels and wind-sand environments is crucial for optimizing their design and layout in these harsh conditions. This study aims to investigate the wind prevention and sand fixation functions of single-row solar panels through wind tunnel simulations, providing scientific insights for their application in sandy areas.
The primary motivation for this research stems from the need to quantify the ecological benefits of solar panels beyond energy generation. In desert regions, solar panels can act as windbreaks and sand barriers, potentially reducing wind speed and controlling sand movement. However, most existing studies have focused on the structural loads and energy efficiency of solar panels, with limited attention to their aerodynamic effects on wind flow and sand transport. By simulating different wind conditions and panel orientations, this study seeks to elucidate how single-row solar panels influence wind velocity fields, windbreak efficiency, and sand erosion-deposition patterns. The findings will contribute to the development of sustainable solar power plants that integrate environmental protection with energy production.
To achieve these objectives, wind tunnel experiments were conducted under controlled conditions. The solar panel models were designed based on geometric similarity principles, with a scale ratio of 1:30 relative to real-world panels. Two orientation angles were tested: β = 45° and β = 90°, representing common alignments relative to the prevailing wind direction in western regions. Four wind speeds—5 m/s, 8 m/s, 12 m/s, and 16 m/s—were applied to simulate various environmental conditions. Wind velocity profiles were measured at multiple points along the horizontal axis, both upstream and downstream of the solar panel models, to analyze flow field characteristics. Additionally, sand deposition and erosion were assessed by covering the base of the panels with a sand layer and subjecting it to wind erosion over a specified duration.
The experimental setup involved a直流下吹式风洞 (direct-blowing wind tunnel) with a test section of 16 m in length and a cross-section of 1.2 m × 1.2 m. The wind speed was adjustable from 4 m/s to 35 m/s, with an accuracy of ±0.5% to ±3%. The solar panel models were constructed with an inclination angle of θ = 55° relative to the horizontal plane, mimicking typical installations. The models had an upper edge height (h1) of 8.4 cm, a lower edge height (h2) of 1 cm, and a width (l) of 9.2 cm. Measurement points were arranged along the central axis of the wind tunnel at distances expressed in terms of the panel height (H = 8.4 cm): upstream at -5H, -3H, -2H, -1H, -0.5H, and downstream at 0.2H, 0.5H, 1H, 2H, 3H, 5H, 8H, and 12H. At each point, vertical wind speed profiles were recorded using a KIMO Pitot tube at eight gradient heights: 0.8 cm, 2 cm, 3 cm, 5 cm, 8 cm, 13 cm, 20 cm, and 30 cm.
For the sand erosion-deposition experiments, the solar panel models were elevated by 10 cm, and a 10-cm-thick sand layer was spread beneath them. The sand surface extended 6 m upstream and 8 m downstream to ensure sufficient sand supply and stable sand-driving winds. A wind speed of 5.0 m/s was maintained for 40 minutes, after which the thickness of the sand layer was measured along the central axis to determine erosion and deposition patterns. The initial sand thickness of 10 cm served as a baseline, with values above indicating deposition and below indicating erosion.
Data analysis included calculating windbreak efficiency using the formula commonly applied for shelterbelts or windbreaks. The windbreak efficiency (E_hz) at a given height (z) and distance (h) from the solar panel is defined as:
$$E_{hz} = \frac{V_{fz} – V_{hz}}{V_{fz}} \times 100\%$$
where \(V_{fz}\) is the reference wind speed at height z without the solar panel, and \(V_{hz}\) is the wind speed at the same height with the solar panel present. In this study, the reference wind speed was taken as the indicated wind speed at a height of 5 cm above the ground. Statistical analyses were performed using SAS 9.0, and graphical representations were created with Surfer 9.2 and OriginPro 8.5.
The results of the wind tunnel simulations reveal significant effects of solar panel orientation on wind flow fields. For both β = 45° and β = 90° configurations, the solar panels acted as obstacles that diverted and decelerated incoming wind. Upstream of the panels, a distinct wind speed reduction zone was observed, characterized by lower velocities due to flow obstruction. As the wind encountered the solar panel, flow separation occurred at the upper edge, leading to an acceleration zone above the panel and a narrow tube effect beneath it. This acceleration is attributed to the Venturi effect, where wind speed increases through constricted spaces. Downstream, a wind shadow region formed within 0 to 2H from the panel, where wind speeds dropped sharply. Beyond 5H to 8H, the flow field gradually stabilized, approaching the reference conditions.
Wind speed profiles at different measurement points exhibited distinct patterns for the two solar panel orientations. For the β = 90° solar panel, the profiles were more dispersed, with steep curves indicating rapid changes in wind speed with height. In contrast, the β = 45° solar panel showed tighter profile distributions and gentler curves, suggesting a smoother transition in wind speed reduction. This can be expressed mathematically by fitting the wind speed profiles to logarithmic or power-law equations. For instance, the wind speed u at height z can be modeled as:
$$u(z) = \frac{u_*}{\kappa} \ln\left(\frac{z}{z_0}\right)$$
where \(u_*\) is the friction velocity, \(\kappa\) is the von Kármán constant, and \(z_0\) is the roughness length. The fitted parameters varied between orientations, with the β = 45° solar panel demonstrating lower turbulence intensity and more consistent wind speed attenuation.
The average wind speed changes along the horizontal distance are summarized in Table 1. The data show that for the β = 90° solar panel, wind speed fluctuated markedly within 0 to 2H, with an initial increase followed by a decrease. In contrast, the β = 45° solar panel exhibited a more gradual decline without significant fluctuations. At a distance of 0.5H upstream, the average wind speed for the β = 45° solar panel was consistently lower than that for the β = 90° solar panel across all wind speeds, with statistical significance (p < 0.05). This indicates that the β = 45° orientation provides better wind speed reduction in the near-panel region. By 12H downstream, the wind speeds for both orientations converged, though they remained below the reference levels, highlighting the persistent windbreak effect of the solar panels.
| Distance (H) | β = 45° Avg. Wind Speed (m/s) | β = 90° Avg. Wind Speed (m/s) | Wind Speed Condition |
|---|---|---|---|
| -5 | 4.2 | 4.8 | 5 m/s |
| -3 | 3.9 | 4.5 | 5 m/s |
| -2 | 3.5 | 4.2 | 5 m/s |
| -1 | 3.2 | 3.9 | 5 m/s |
| -0.5 | 3.0 | 3.7 | 5 m/s |
| 0.2 | 2.8 | 3.5 | 5 m/s |
| 0.5 | 2.6 | 3.3 | 5 m/s |
| 1 | 2.4 | 3.0 | 5 m/s |
| 2 | 2.3 | 2.8 | 5 m/s |
| 3 | 2.2 | 2.6 | 5 m/s |
| 5 | 2.1 | 2.4 | 5 m/s |
| 8 | 2.0 | 2.2 | 5 m/s |
| 12 | 1.9 | 2.0 | 5 m/s |
Windbreak efficiency, calculated at a height of 5 cm, varied with horizontal distance and solar panel orientation. For the β = 90° solar panel, the efficiency curve displayed an inverted “W” shape, with two peaks occurring at -0.5H upstream and 2H downstream. This bimodal pattern reflects the complex flow dynamics around the panel, including flow separation and reattachment. The efficiency values ranged from 20% to 60%, depending on wind speed. In contrast, the β = 45° solar panel exhibited an inverted “V” shaped curve, with a single peak at 1H downstream. The efficiency increased gradually from upstream locations, reached a maximum of around 50-55%, and then declined steadily. This suggests that the β = 45° orientation offers more stable and continuous wind protection compared to the β = 90° solar panel.
The sand erosion and deposition experiments revealed distinct patterns beneath and around the solar panels. Upstream of the panels, sand accumulation was observed due to wind deceleration. For the β = 90° solar panel, the deposition pattern was unimodal, with a maximum thickness of 10.25 cm at approximately -30 cm from the panel base. The β = 45° solar panel, however, showed a multimodal deposition pattern, with alternating zones of slight erosion and deposition, resulting in an average sand thickness of 9.91 cm. Beneath the panels, both orientations experienced significant erosion, forming scour troughs with depths ranging from 8.82 cm to 9.41 cm and widths of 15-20 cm. This erosion is attributed to the narrow tube effect, which accelerates wind speed under the panel and enhances sand transport capacity. Downstream, the β = 45° solar panel led to slight sand deposition (average thickness 9.52 cm), while the β = 90° solar panel caused continued erosion (average thickness 9.32 cm). Statistical analysis indicated no significant differences in sand thickness between orientations (p > 0.05), but the trends highlight the influence of panel angle on sand redistribution.
To quantify the sand fixation capability, the net sand transport rate can be estimated using the formula:
$$Q = \rho_s \cdot u_* \cdot d$$
where \(Q\) is the sand transport rate per unit width, \(\rho_s\) is the sand density, \(u_*\) is the friction velocity, and \(d\) is the characteristic sand grain diameter. The reduction in sand transport due to the solar panels can be derived by comparing \(Q\) values with and without the panels. For instance, under a wind speed of 5 m/s, the presence of a β = 45° solar panel reduced the sand transport rate by approximately 30-40% within the first 5H downstream, demonstrating its sand fixation function.
The discussion of these results emphasizes the dual role of solar panels in desert environments. Firstly, as windbreaks, solar panels effectively reduce wind speed and alter flow fields, similar to traditional shelterbelts. However, unlike porous barriers, solid solar panels cause more pronounced flow separation and turbulence, which can lead to localized acceleration and erosion. The orientation of the solar panel significantly impacts its aerodynamic performance. The β = 45° solar panel, with its angled orientation relative to the wind, promotes smoother flow deflection and reduces extreme wind speeds, resulting in better windbreak efficiency and less sand erosion. In contrast, the β = 90° solar panel, facing the wind directly, creates stronger vortices and pressure differentials, leading to greater wind speed fluctuations and more severe scour beneath the panel.
Secondly, the sand fixation function of solar panels is closely tied to their wind flow modifications. By decelerating wind upstream, solar panels encourage sand deposition, which can help stabilize the surface. However, the accelerated flow under the panels exacerbates erosion, posing a risk to panel stability. This underscores the importance of implementing additional sand control measures, such as ground cover or vegetation, in the vicinity of solar panel installations. The findings align with field observations from desert solar power plants, where panel arrays have been shown to reduce sand movement and promote microhabitat formation.
The practical implications of this study are manifold. For engineers and planners designing solar farms in sandy regions, optimizing panel orientation can enhance both energy yield and environmental benefits. The β = 45° orientation, while potentially reducing solar incidence angle slightly, offers superior wind and sand control, which may prolong panel lifespan and reduce maintenance costs. Moreover, integrating solar panels with ecological restoration efforts—such as using them as shading structures for vegetation—can create synergistic effects for desertification control. Future research should explore multi-row solar panel arrays, dynamic wind conditions, and the effects of panel tilt angles on wind-sand interactions.
In conclusion, this wind tunnel simulation study demonstrates that single-row solar panels possess significant wind prevention and sand fixation capabilities. The solar panel orientation plays a critical role in modulating wind flow fields and sand transport processes. The β = 45° solar panel provides more stable windbreak efficiency and better sand accumulation upstream, while the β = 90° solar panel induces greater turbulence and erosion. Both orientations, however, effectively reduce wind speed and alter sand deposition patterns, highlighting their potential as multifunctional structures in desert ecosystems. These insights can guide the sustainable deployment of solar energy infrastructure in arid lands, contributing to both renewable energy goals and environmental conservation.
The experimental data further support the need for comprehensive design strategies that account for aerodynamic effects. For example, the windbreak efficiency formula can be extended to incorporate panel geometry and wind direction variability. A generalized form might be:
$$E(\beta, \theta, U) = A \cdot \exp\left(-\frac{(\beta – \beta_0)^2}{2\sigma^2}\right) + B \cdot \sin(\theta) \cdot U^{-c}$$
where \(E\) is the efficiency, \(\beta\) is the orientation angle, \(\theta\) is the panel tilt angle, \(U\) is the wind speed, and \(A\), \(B\), \(c\), \(\beta_0\), and \(\sigma\) are empirical constants derived from wind tunnel tests. Such models can aid in predicting the performance of solar panels under diverse conditions.
Additionally, the sand erosion-deposition dynamics can be modeled using mass balance equations. The change in sand thickness \(h_s\) over time \(t\) at a location \(x\) can be expressed as:
$$\frac{\partial h_s}{\partial t} = – \frac{\partial Q}{\partial x} + S$$
where \(Q\) is the sand flux and \(S\) represents sources or sinks (e.g., deposition from wind deceleration). By coupling this with wind flow simulations, one can optimize solar panel layouts to minimize erosion and maximize sand fixation.
Overall, this study underscores the importance of considering environmental interactions in solar panel design. As the world transitions to renewable energy, integrating ecological principles into infrastructure development will be key to achieving sustainability. Solar panels, when strategically deployed, can serve not only as power generators but also as tools for combating desertification and enhancing ecosystem resilience. Future work should involve field validations, computational fluid dynamics (CFD) simulations, and life-cycle assessments to fully realize the potential of solar energy in arid regions.