| Work Detail |
US researchers have created a novel model that can help developers evaluate corn growth in agrovoltaic installations. They also propose using spatiotemporal shade distribution (SSD) to optimize crop yield and energy production.
A research group led by scientists at Purdue University in Indiana has created a novel model to evaluate corn growth in agrivoltaic installations and has proposed using a spatiotemporal shade distribution (SSD) model to optimize crop yield and energy production.
The new method is based on the Agricultural Production Systems Simulator (APSIM) plant model, which is based on finer temporal resolution and whose validity is supported by the literature. The SSD model, which takes into account the shadow cast by the photovoltaic panels, was used in conjunction with radiation data from the National Renewable Energy Laboratory (NREL). These combined data were calibrated and validated with the results of their field measurements.
The field experiment was conducted at a Purdue University agrivoltaic farm in West Lafayette, Indiana (USA). There, the photovoltaic panels were deployed in two arrangements: 300 W modules placed side by side or 100 W modules arranged in an alternating checkerboard pattern. All used single-axis trackers and were 6.1 meters high. The installation was tested between April and October 2020.
“For validation, 12 plots are considered,” the academics said. “Corn cobs were hand-picked from three representative plants in each of these plots. In total, 570 corn plants from the region without VP and 36 corn plants from the region with VP were used in the analysis, respectively. The cobs were cleaned, imaged and processed using a DuPont pioneering cob photometer.”
Field measurements showed that maize yield in the non-PV area was 10,955 kg/ha, compared to a yield of 10,182 kg/ha in the PV area. This was consistent with the new model, which predicted 10,856 kg/ha for the non-PV area and 10,102 kg/ha for the PV area.
The researchers then used the model to test the impact on performance of tracker height, spacing between arrays, panel angle, and tracking system activation. First, they found that designs that reduced tracker height without impeding the movement of plant machinery should be considered, as overall average corn yield is a weak function of tracker height up to 2.44 m.
“However, variability from one corn row to another increases as tracker height is reduced,” they further explained. “Another interesting finding is that for our PV module sizes, increasing the distance between adjacent PV rows beyond 9.1 m, while keeping total power constant across the field, does not lead to an increase in corn yield based on total field area.”
They also found that anti-tracking (AT) around solar noon provided the most significant increase in corn yield. “However, this 5.6% corn yield increase is quite modest and must be weighed against a substantial decrease in solar energy,” the group stressed.
The proposed model was presented in “ Optimizing corn agrivoltaic farming through farm-scale experimentation and modeling ,” published in Cell Reports Sustainability . Academics from the Danish University of Aarhus also participated in the research group. |
