As the world shifts towards sustainable energy, solar panels have become a cornerstone of renewable power generation. Among various tracking technologies, flat uniaxial solar panels are widely deployed due to their cost-effectiveness and high solar energy utilization, especially in low-to-mid latitude regions. However, these solar panels, characterized by large aspect ratios and planar structures, are highly susceptible to wind loads, which can lead to local or global failures during extreme wind events. Understanding the wind load characteristics is crucial for ensuring structural integrity and safety. This study investigates the wind load behavior of flat uniaxial solar panels with large aspect ratios through wind tunnel testing. The research focuses on isolated and array configurations, considering various inclination angles and wind directions, to analyze wind pressure distributions, interference effects, and provide design recommendations. The findings aim to enhance the wind-resistant design of solar panel systems, contributing to more reliable solar energy infrastructure.
Wind loads on solar panels have been extensively studied, but most research focuses on panels with smaller aspect ratios. Previous studies through wind tunnel tests and numerical simulations have highlighted factors such as inclination angle, wind direction, and array spacing influencing wind pressure coefficients. For instance, interference effects between upstream and downstream solar panels can reduce wind loads, while local pressure distributions often show gradient changes due to airflow separation. However, there is a gap in understanding the wind load characteristics of solar panels with large aspect ratios, particularly for flat uniaxial tracking systems. This study addresses this by examining solar panels with an aspect ratio of approximately 14:1, which are common in utility-scale installations. The goal is to derive detailed wind load models that account for complex flow patterns and structural responses, ensuring that solar panels can withstand diverse environmental conditions.
The wind tunnel tests were conducted in the CA-1 wind tunnel laboratory, which features a test section of 15 m length, 3 m width, and 2.5 m height, with a wind speed range of 0–53 m/s and a turbulence intensity below 0.5% in uniform flow. The wind field simulated a Category B terrain according to standard specifications, achieved using spires and roughness elements to replicate the wind profile and turbulence intensity profile. The wind speed at the solar panel axis height was approximately 12.0 m/s, with a scale ratio of 1:2 for velocity. Pressure measurements were taken using electronic pressure scanners with a range of ±254 mm H₂O, coupled with A/D boards and custom data acquisition software. The sampling frequency was 312.5 Hz over a duration of 70.4 s, ensuring accurate capture of wind load fluctuations.
The solar panel models were scaled at 1:12, with each panel having a length (L) of 2276 mm, width (B) of 165.7 mm, and an axis height (H) of 272 mm above ground. The models were constructed from ABS plastic to ensure rigidity, and 156 pressure taps were installed on both upper and lower surfaces to measure net pressure. For array configurations, five solar panels were arranged with a center-to-center spacing of 3B (three times the width), based on typical engineering practices. In array tests, one panel served as the test model while others acted as干扰 models, with data collected by rotating the test panel position. The test matrix included isolated and array setups, with seven inclination angles (α) from 0° to 60° at 10° intervals, and seven wind directions (β) from 0° to 180° at 30° intervals for isolated panels, plus 0° and 180° for arrays, totaling 63工况.
Wind load parameters were defined using dimensionless coefficients. The net pressure coefficient at point i is given by:
$$C_{Pi} = \frac{P_i – P_{\infty}}{P_{r0} – P_{\infty}}$$
where \(P_i\) is the net pressure at point i, \(P_{\infty}\) is the static pressure at the reference point, and \(P_{r0}\) is the total pressure at the reference point. The shape coefficient (or wind force coefficient) accounts for terrain effects and is calculated as:
$$\mu_{si} = \left( \frac{H_G}{Z_i} \right)^{0.3} C_{Pi}$$
Here, \(H_G\) is the reference height, and \(Z_i\) is the height of point i. The overall wind force coefficient for the entire solar panel is derived by integrating local coefficients, and the overturning bending moment coefficient around the axis is defined as:
$$C_{mx} = \frac{\sum_{i=1}^{n} \mu_{si} A_i y_i}{A B}$$
where \(A_i\) is the tributary area of point i, \(y_i\) is the distance from point i to the panel center, \(A\) is the total area of the solar panel, and \(B\) is the width. These formulas are essential for analyzing wind load effects on solar panels.
The results for isolated solar panels reveal significant dependencies on inclination angle and wind direction. The overall wind force coefficient increases with higher inclination angles, particularly when the wind direction is perpendicular to the panel axis (β = 0° or 180°). For instance, at β = 0°, the wind force coefficient rises from near zero at α = 0° to approximately 2.0 at α = 60°. The overturning bending moment coefficient, which indicates the tendency for the solar panel to rotate, is negative for β = 0° and positive for β = 180°, showing that wind loads always push the panel toward a more vertical orientation. The most critical wind directions for both wind force and moment are 0° and 180°, as these maximize wind exposure. The table below summarizes the overall wind force coefficients for isolated solar panels at various inclination angles and wind directions.
| Wind Direction (β) | Inclination Angle (α) | Wind Force Coefficient (μs) |
|---|---|---|
| 0° | 0° | 0.05 |
| 10° | 1.42 | |
| 20° | 1.58 | |
| 30° | 1.70 | |
| 40° | 1.89 | |
| 50° | 2.08 | |
| 60° | 2.15 | |
| 180° | 0° | 0.04 |
| 10° | -1.48 | |
| 20° | -1.52 | |
| 30° | -1.72 | |
| 40° | -1.92 | |
| 50° | -2.12 | |
| 60° | -2.18 |
Local wind pressure distributions on isolated solar panels exhibit gradient changes along the wind direction. For example, at α = 40° and β = 0°, the shape coefficient decreases from the windward edge to the leeward edge, causing a bending moment around the axis. At β = 30°, the maximum local coefficient occurs at the windward corner due to flow separation, with values reaching up to 2.5. As the wind direction shifts to 60°, the gradient becomes less pronounced but covers a larger area. When the wind is parallel to the axis (β = 90°), coefficients approach zero. These patterns highlight the complexity of wind loads on solar panels, necessitating detailed analysis for design.
For array configurations, interference effects significantly alter wind loads. The first row of solar panels in the wind direction experiences the highest wind force, but values are lower than for isolated panels due to shielding. Subsequent rows show reduced coefficients, with the second row dropping by about 50% compared to the first, after which coefficients stabilize. The overturning bending moment coefficient decreases with increasing inclination angle, indicating that for steeper solar panels, wind force dominates over moment effects. The table below presents wind force coefficients for arrayed solar panels at β = 0° and various inclination angles, demonstrating the shielding effect.
| Row Position | Inclination Angle (α) | Wind Force Coefficient (μs) |
|---|---|---|
| First Row | 0° | 0.04 |
| 10° | 1.35 | |
| 20° | 1.50 | |
| 30° | 1.62 | |
| 40° | 1.80 | |
| 50° | 1.98 | |
| 60° | 2.05 | |
| Second Row | 0° | 0.03 |
| 10° | 0.65 | |
| 20° | 0.78 | |
| 30° | 0.85 | |
| 40° | 0.95 | |
| 50° | 1.10 | |
| 60° | 1.18 | |
| Fifth Row | 0° | 0.02 |
| 10° | 0.70 | |
| 20° | 0.82 | |
| 30° | 0.88 | |
| 40° | 0.98 | |
| 50° | 1.12 | |
| 60° | 1.20 |
Local pressure distributions in arrays show similar gradients but with reduced magnitudes due to upstream interference. The windward corners of solar panels still experience peak coefficients, but the patterns become more fragmented, indicating complex flow interactions. This underscores the importance of considering array effects in wind load assessments for solar panel farms.
Comparing wind load provisions from international codes reveals discrepancies with experimental data. The Chinese code (GB 50009-2012) specifies shape coefficients for single-slope structures up to 30° inclination, but values are conservative for larger angles. The Japanese standard (JIS C 8955-2017) provides formulas for angles from 5° to 60°, yielding higher coefficients than tested. The Australian/New Zealand code (AS/NZS 1170.2:2011) offers two-zone distributions but underestimates loads for small angles. The American standard (ASCE/SEI 7-16) treats solar panels as components, with coefficients depending on location and area, but some values exceed test results. Based on this study, a refined wind load model is proposed for flat uniaxial solar panels with large aspect ratios. The solar panel is divided into zones along the span: Zone A (leeward), Zone B (middle), and Zone C (windward). Recommended shape coefficients for design are summarized in the table below, considering worst-case wind directions (β = 0° and 180°).
| Wind Direction (β) | Inclination Angle (α) | Zone C (μs3) | Zone B (μs3) | Zone A (μs3) | Zone C (μs4) | Zone B (μs4) | Zone A (μs4) |
|---|---|---|---|---|---|---|---|
| 0° | 0° | -0.50 | 0.02 | 0.04 | 0.04 | 0.04 | 0.09 |
| 10° | 0.43 | 1.40 | 1.49 | 0.28 | 0.61 | 0.70 | |
| 20° | 0.98 | 1.56 | 1.45 | 0.42 | 0.95 | 0.99 | |
| 30° | 1.55 | 1.67 | 1.58 | 0.78 | 1.08 | 1.04 | |
| 40° | 1.68 | 1.96 | 1.84 | 0.98 | 1.23 | 1.22 | |
| 50° | 1.95 | 2.15 | 2.03 | 1.32 | 1.53 | 1.47 | |
| 60° | 1.97 | 2.19 | 2.08 | 1.48 | 1.67 | 1.60 | |
| 180° | 0° | -0.51 | 0.09 | 0.13 | 0.08 | 0.01 | 0.07 |
| 10° | -1.51 | -1.45 | -1.31 | -0.29 | -0.62 | -0.52 | |
| 20° | -1.64 | -1.39 | -1.34 | -0.70 | -0.83 | -0.77 | |
| 30° | -1.80 | -1.69 | -1.57 | -0.95 | -0.97 | -0.87 | |
| 40° | -1.97 | -1.93 | -1.81 | -1.08 | -1.12 | -1.05 | |
| 50° | -2.20 | -2.15 | -2.02 | -1.37 | -1.40 | -1.30 | |
| 60° | -2.21 | -2.22 | -2.05 | -1.58 | -1.59 | -1.50 |
These coefficients account for gradient effects and can guide the design of support structures for solar panels, ensuring adequate wind resistance. The formulas for calculating wind loads on solar panels incorporate these zonal values to optimize safety and performance.
In conclusion, this study provides comprehensive insights into wind loads on flat uniaxial solar panels with large aspect ratios. Key findings include: (1) The most critical wind directions for solar panels are 0° and 180°, where wind force and overturning moment are maximized. (2) Wind force coefficients increase with inclination angle, while moment coefficients decrease, implying that for steep solar panels, wind force dominates design considerations. (3) Local pressure distributions show gradients, with peak values at windward corners due to flow separation, emphasizing the need for detailed pressure mapping on solar panels. (4) Array configurations exhibit shielding effects, reducing wind loads on downstream solar panels, but the first row remains most vulnerable. (5) International codes vary in their provisions, and the proposed zonal coefficients offer a more accurate design basis for solar panels. Future work could explore dynamic effects, such as wind-induced vibrations, and optimize array layouts to minimize wind loads on solar panels. This research enhances the resilience of solar energy systems, supporting the global transition to sustainable power.
The implications for engineering practice are significant. Designers of solar panel installations should consider both isolated and array effects, using the recommended coefficients to calculate wind loads accurately. For large-scale solar farms, optimizing panel spacing and orientation can reduce wind exposure, lowering material costs and improving longevity. Additionally, regular maintenance and monitoring of solar panels in wind-prone areas are advised to detect early signs of damage. As solar energy continues to expand, integrating advanced wind load models will be essential for safe and efficient solar panel deployments. This study underscores the importance of wind engineering in renewable energy infrastructure, contributing to a greener future.