As a researcher focused on sustainable energy and agricultural integration, I have always been intrigued by the potential of photovoltaic (PV) systems to coexist with farming practices. The concept of agrivoltaics, which combines solar energy generation with crop cultivation, offers a promising path toward enhancing land use efficiency. However, traditional PV arrays with high solar panel densities often cast significant shade, leading to conflicts between crop growth and energy production. This issue can result in reduced agricultural yields and inefficient land utilization, particularly in regions where arable land is scarce. In this study, I aimed to investigate how varying the density of solar panels in PV arrays influences the photothermal environment beneath them. By modifying standard 100% solar panel density arrays to 75% and 50% densities, I conducted detailed environmental monitoring to analyze changes in solar radiation, air temperature, and soil temperature. My goal was to provide actionable insights for designing PV systems that balance energy output with agricultural productivity, ultimately supporting the development of sustainable agrivoltaic projects.
The integration of solar panels into agricultural landscapes has gained traction globally as a means to promote renewable energy without compromising food security. Solar panels, when deployed in high densities, can create microclimates that alter light and heat distribution, potentially hindering crop photosynthesis and growth. For instance, in dense arrays, solar panels block a substantial portion of sunlight, reducing the average solar radiation available to plants. This can lead to decreased biomass accumulation and lower yields for light-sensitive crops. Moreover, the spatial arrangement of solar panels affects how sunlight is distributed across the array, with central areas often receiving more radiation than the edges. In my research, I sought to quantify these effects by examining three different solar panel densities—100%, 75%, and 50%—in a real-world setting. I hypothesized that reducing the density of solar panels would enhance the photothermal conditions underneath, making the environment more suitable for a wider range of crops. This approach not only addresses the “light competition” issue but also explores how solar panels can be optimized for dual-use applications.
To conduct this study, I selected a photovoltaic agricultural park in southern Jiangsu, China, known for its extensive PV installations and mixed cropping systems. The site featured standard PV arrays with a span of 6.8 meters and a length of 150 meters, supported by structural elements like pipe piles and inclined braces. The solar panels were composed of 265 W polycrystalline silicon modules, each measuring 1640 mm by 992 mm, and were mounted at a 24-degree tilt with their lower edges 2.5 meters above the ground. This setup is typical for agrivoltaic systems in the region, where crops such as peanuts and rapeseed are grown beneath the arrays. For the experiment, I modified the existing 100% solar panel density configuration by selectively removing panels to create 75% and 50% densities. This involved rearranging the solar panels in a pattern that maintained structural integrity while allowing more sunlight penetration. The 75% density array had panels spaced to cover three-quarters of the area, and the 50% density array covered half, compared to the full coverage in the 100% array. This design allowed me to simulate different shading levels and assess their impact on the underlying environment.
I established an environmental monitoring system to collect data on solar radiation intensity, air temperature, and soil temperature. The sensors were strategically placed within a single-span array, divided into southern, central, and northern zones to capture spatial variations. Solar radiation sensors and air temperature probes were positioned at a height of 1.0 meters above the ground, corresponding to the crop canopy level, while soil temperature sensors were buried at a depth of 0.15 meters to monitor root zone conditions. Data was recorded at 10-minute intervals over a 20-day period in July, encompassing a mix of sunny and rainy days to account for weather variability. I used high-precision instruments, such as HOBO sensors, to ensure accuracy, with solar radiation measurements ranging up to 1280 W/m² and temperature sensors capable of detecting subtle changes. This comprehensive setup enabled me to analyze how different solar panel densities influenced the microclimate, particularly during daylight hours (06:00–18:00) and nighttime (18:00–06:00). By comparing the internal conditions of the PV arrays with external open areas, I could isolate the effects of the solar panels on the photothermal environment.
The solar radiation intensity under the PV arrays was significantly affected by the density of the solar panels. On average, the open area exhibited a solar radiation intensity of 336 W/m², while the 50%, 75%, and 100% density arrays showed progressively lower values. For example, during a typical sunny day, the open area reached a peak radiation of 985.6 W/m², whereas the 50% density array had values of 900.6 W/m², 925.6 W/m², and 883.1 W/m² in the southern, central, and northern zones, respectively. This represents reductions of 8.6%, 6.1%, and 10.4% compared to the open area. In contrast, the 75% and 100% density arrays demonstrated more substantial reductions, with the central zone often receiving higher radiation than the edges due to the arrangement of the solar panels. The relationship can be summarized by the formula for solar radiation attenuation under shading: $$ I_{\text{array}} = I_{\text{open}} \times (1 – \alpha \cdot d) $$ where ( I_{\text{array}} ) is the radiation under the array, ( I_{\text{open}} ) is the open area radiation, ( \alpha ) is the attenuation coefficient, and ( d ) is the solar panel density. This equation highlights how increasing the density of solar panels leads to greater light reduction, impacting the energy available for crops.
| Date | Open Area (W/m²) | 50% Density (W/m²) | 75% Density (W/m²) | 100% Density (W/m²) |
|---|---|---|---|---|
| July 1 | 486.6 | 322.3 | 269.3 | 186.2 |
| July 2 | 204.2 | 130.6 | 102.5 | 84.3 |
| July 3 | 420.6 | 279.8 | 221.4 | 160.7 |
| July 4 | 438.6 | 283.0 | 212.0 | 158.6 |
| July 5 | 564.3 | 382.6 | 318.3 | 202.9 |
| July 6 | 427.2 | 300.3 | 251.5 | 170.0 |
| July 7 | 121.3 | 78.7 | 61.5 | 49.1 |
| July 8 | 241.8 | 161.8 | 125.5 | 94.3 |
| July 9 | 438.8 | 295.3 | 227.3 | 162.1 |
| July 10 | 217.6 | 145.0 | 124.8 | 89.6 |
| July 11 | 483.2 | 294.9 | 252.7 | 179.4 |
| July 12 | 461.6 | 309.5 | 242.2 | 175.5 |
| July 13 | 199.8 | 130.0 | 102.5 | 81.3 |
| July 14 | 318.4 | 201.4 | 157.5 | 125.2 |
| July 15 | 200.6 | 130.7 | 103.4 | 83.4 |
| July 16 | 145.0 | 93.1 | 73.7 | 58.3 |
| July 17 | 345.0 | 245.1 | 224.5 | 138.0 |
| July 18 | 426.2 | 302.5 | 254.0 | 164.6 |
| July 19 | 262.4 | 172.0 | 136.6 | 104.8 |
| July 20 | 316.1 | 208.0 | 168.0 | 125.2 |
Air temperature under the PV arrays also varied with solar panel density. During the daytime, the open area had an average air temperature of 33.7°C, while the 50%, 75%, and 100% density arrays showed lower temperatures, indicating a cooling effect provided by the solar panels. For instance, on a sunny day, the open area reached a maximum of 36.4°C, compared to 35.0°C, 34.1°C, and 33.3°C in the 50%, 75%, and 100% density arrays, respectively. This cooling can be attributed to the shading from the solar panels, which reduces direct solar heating. At night, the arrays tended to retain heat slightly, with average nighttime temperatures in the arrays being 0.1–0.3°C higher than in the open area. The temperature dynamics can be modeled using a heat balance equation: $$ \frac{dT}{dt} = \frac{1}{\rho c_p} \left( Q_{\text{solar}} – Q_{\text{convection}} – Q_{\text{radiation}} \right) $$ where ( T ) is temperature, ( t ) is time, ( \rho ) is air density, ( c_p ) is specific heat, and ( Q ) terms represent heat fluxes. Higher densities of solar panels enhance shading, reducing ( Q_{\text{solar}} ) and thus lowering daytime temperatures. This effect is crucial for mitigating heat stress in crops during hot summers.
| Parameter | 50% Density (°C) | 75% Density (°C) | 100% Density (°C) | Open Area (°C) |
|---|---|---|---|---|
| Daily Mean Air Temperature | 29.6 | 29.4 | 29.2 | 30.3 |
| Daytime Mean Air Temperature | 32.2 | 31.8 | 31.2 | 33.7 |
| Nighttime Mean Air Temperature | 26.9 | 27.0 | 27.0 | 26.8 |
| Days with Max Temp ≥35°C | 15 | 13 | 8 | 20 |
| Days with Max Temp ≥38°C | 8 | 6 | 2 | 10 |
| Days with Min Temp ≥29°C | 19 | 19 | 19 | 20 |
Soil temperature followed a similar trend, with the open area having higher daytime temperatures than the PV arrays. The average daytime soil temperature in the open was 28.7°C, while the 50%, 75%, and 100% density arrays had values of 27.9°C, 27.8°C, and 27.4°C, respectively. This indicates that solar panels provide a cooling effect on the soil, which can benefit root development and water retention. On sunny days, the differences were more pronounced; for example, the open area soil temperature peaked at 30.1°C, compared to 28.8°C, 28.6°C, and 28.9°C in the central zones of the 50%, 75%, and 100% arrays. The soil heat transfer can be described by Fourier’s law: $$ q = -k \frac{dT}{dz} $$ where ( q ) is heat flux, ( k ) is thermal conductivity, and ( \frac{dT}{dz} ) is the temperature gradient. With fewer solar panels, more sunlight reaches the soil, increasing ( q ) and raising temperatures. However, in denser arrays, the shading from solar panels reduces this flux, leading to cooler soil conditions. Spatially, the central zones of the arrays often had more stable soil temperatures than the edges, especially in the 75% and 100% densities, where the solar panels created a more uniform shade cover.
In rainy conditions, the photothermal environment under the PV arrays was less variable but still showed density-dependent effects. Solar radiation intensity in the open area averaged 199.8 W/m² on a rainy day, while the 50%, 75%, and 100% density arrays had values of 130.0 W/m², 102.5 W/m², and 81.3 W/m², respectively. Air and soil temperatures also remained lower under the arrays, with the 100% density providing the most consistent cooling. This suggests that even in overcast weather, the solar panels influence the microclimate, though to a lesser extent. The reduced variability highlights the importance of solar panel density in buffering environmental fluctuations, which could be advantageous for crops sensitive to extreme weather. For instance, the formula for net radiation under cloudy conditions can be adjusted: $$ I_{\text{net}} = I_{\text{global}} \cdot \tau \cdot (1 – d) $$ where ( I_{\text{net}} ) is the net radiation under the array, ( I_{\text{global}} ) is global radiation, ( \tau ) is transmissivity, and ( d ) is solar panel density. This shows how denser solar panels further reduce radiation, affecting crop light availability.
My findings align with broader research on agrivoltaics, where solar panel density is a critical factor in balancing energy and agricultural outputs. For example, studies have shown that reducing solar panel density can improve light penetration for crops like lettuce and grains, potentially increasing yields. In my experiment, the 50% density array allowed up to 90% of the open area radiation in some zones, making it more suitable for light-demanding crops. Conversely, higher densities of solar panels, such as 100%, created shadier conditions that might only support shade-tolerant species. This trade-off underscores the need for customized solar panel arrangements based on local climate and crop requirements. Moreover, the cooling effect of solar panels during daytime can reduce water evaporation from soil, enhancing water use efficiency in arid regions. By integrating these insights, farmers and developers can design PV systems that optimize both energy generation and food production.
The implications of this study extend to policy and practical applications in renewable energy and agriculture. For instance, in regions with high solar insolation, using lower densities of solar panels could enable dual-use of land without significant yield losses. This approach aligns with global sustainability goals, such as those outlined in the Paris Agreement, by promoting clean energy while preserving agricultural land. Future work could explore dynamic solar panel systems that adjust density seasonally or incorporate bifacial solar panels to capture reflected light. Additionally, economic models could assess the profitability of different solar panel densities, considering factors like energy output, crop yields, and maintenance costs. As I reflect on this research, I believe that agrivoltaics represents a viable pathway toward resilient food-energy systems, and optimizing solar panel density is a key step in that direction.
In conclusion, my investigation into the effects of solar panel density on the photothermal environment of PV arrays reveals that lower densities enhance solar radiation, air temperature, and soil temperature conditions beneath the arrays. The 50% density array provided the most favorable environment for crop growth, with radiation levels closer to open areas and moderate cooling effects. These results emphasize the importance of tailoring solar panel configurations to local agricultural needs, ensuring that agrivoltaic projects contribute positively to both energy and food security. By continuing to refine the integration of solar panels into farming landscapes, we can harness solar energy more sustainably and support the coexistence of technology and nature.