Overhead agrivoltaics, where photovoltaic (PV) panels are installed above agricultural crops, are increasingly being deployed as a way to produce clean energy while enhancing agricultural productivity. However, recent studies have shown that these systems could have a detrimental effect on the reception of signals from global navigation satellite systems (GNSS), which are essential for precision agriculture technologies such as autonomous tractors, drones, irrigation systems, and crop monitoring tools. The interference with GNSS signals could significantly disrupt the effectiveness of these technologies, potentially hindering their ability to perform tasks with high accuracy.
A study conducted by a team of researchers from the Fraunhofer Institute for Solar Energy Systems, the University of Freiburg, and the Spanish National Research Council focused on investigating how overhead agrivoltaic systems affect GNSS signal quality and its implications for precision agriculture. The researchers compared two different orchards in Germany’s Kressbronn am Bodensee area, one of which featured an agrivoltaic system and the other served as a conventional orchard without PV panels. Both orchards grew pome fruit, and the agrivoltaic system featured semi-transparent, double-glass PV modules mounted above the crops.
The agrivoltaic system’s panels had varying light transparency depending on their location. In the southern zone, the panels allowed 40% light transparency, while in the northern zone, the transparency was higher at 51%. The power outputs also varied, with the southern zone’s panels generating 260 W and the northern zone’s generating 170 W. These configurations were compared against the conventional orchard, which did not have any PV panels. Data for the study was collected using a GNSS receiver attached to a smartphone, which logged GNSS data while the device was moved through the agrivoltaic and conventional orchard areas, as well as along roads within the study zone. The data was used to assess the strength and quality of the GNSS signals under both conditions.
The findings revealed that the installation of PV panels above the orchard did reduce the quality of the GNSS signal. The average carrier-to-noise density ratio (C/N₀), a measure of GNSS signal strength, decreased from 30.62 dB-Hz in the conventional orchard to 26.92 dB-Hz in the agrivoltaic system. Although the agrivoltaic system showed a reduction in signal strength, the average number of satellites with C/N₀ above the threshold of 24 dB-Hz remained over 22 in both areas, suggesting that satellite visibility was not greatly impacted.
The primary challenge identified by the researchers was the reduction in signal strength rather than satellite visibility. However, the positioning accuracy, measured using the position dilution of precision (PDOP), horizontal dilution of precision (HDOP), and vertical dilution of precision (VDOP), remained high in the agrivoltaic orchard. The system demonstrated an excellent PDOP of 0.82, HDOP of 0.52, and VDOP of 0.62. These values are indicative of good positioning accuracy, which is essential for precision tasks such as crop planting, irrigation, and harvesting. The horizontal and vertical accuracy of the GNSS signals were also measured. In the agrivoltaic orchard, horizontal accuracy was 5.30 meters and vertical accuracy was 3.10 meters, which were slightly worse than the conventional orchard’s 3.8 meters and 2.5 meters, respectively.
Additionally, the researchers found that the U/A flag ratio, which describes the proportion of satellites actively used in position calculation compared to the total satellites available, was slightly higher in the agrivoltaic system than in the conventional orchard. This suggests that while the agrivoltaic system faced some interference, it still made effective use of the available satellites for positioning.
The study concluded that while agrivoltaics may reduce GNSS signal quality, the impact on positioning accuracy was not severe enough to make these systems unsuitable for precision agriculture. However, the researchers highlighted the importance of addressing signal interference to ensure the integration of advanced agricultural technologies, such as drones and autonomous robots. They suggested potential solutions, including the use of real-time kinematic (RTK) correction or simultaneous localization and mapping (SLAM) techniques, to mitigate the effects of signal disruption and enhance GNSS performance in agrivoltaic environments.
As agrivoltaics become more widespread, it is crucial to balance the benefits of solar energy production with the operational needs of precision agriculture. Understanding and mitigating the effects of signal interference will ensure that these technologies can work in tandem to improve agricultural productivity while contributing to the transition to renewable energy.
