- Aware of the potential of co-locating food crops with solar panels and the potential for conflicting objectives of agrivoltaics site selection and design, researchers at Cornell University in the United States have developed a novel optimisation model.
To demonstrate the technology, they applied it to Cornell University’s solar power plants and its nearby agricultural experiment stations (AES). The university is located in the U.S. state of New York (NYS) in the northeastern part of the country. Its AES contributes to food security, while its solar farm projects support renewable energy initiatives for the Cornell campus, the local community, and NYS.
The goal was a case study for site selection and design that prioritised economic and environmental objectives while considering irrigation and conservation of water. “A main challenge was managing conflicting objectives, especially balancing economic gains, environmental benefits, and irrigation efficiency,” Fengqi You, the corresponding author told pv magazine.
Four models were developed: Two mixed-integer nonlinear programs (MINLP) models to perform a techno-economic and environmental analysis of co-locating solar PV with crops, independently targeting either economic gains or operational emission reductions; and two fractional programming (FP) models to assess water-use efficiency relative to economic and environmental goals, complementing standard monetary and emission evaluation metrics.
FP’s fractional format facilitates analysis without the need for weight coefficients, according to the paper, handling multi-objective goals, like maximising yield while minimising irrigation. They are especially useful when goals differ in units and scales, such as monetary benefit per unit volume.
To make crop production economically competitive with solar energy, the researchers assigned an agricultural assessment value (AAV) to enhance crop value and enforce minimum cropland constraints, ensuring productive land use and optimal AgV configurations. In addition, the land equivalent ratio (LER) was used to assess improvements in land use efficiency, comparing AgV with traditional practices.
A variety of fixed monocrystalline silicon PV panels, polycrystalline silicon, dual-axis tracking monocrystalline, and copper indium gallium diselenide (CIGS) thin-film technologies were evaluated.
The researchers found that prioritising solar installation in the FP models minimises irrigation requirements, but economic benefits increase as the models allocate more land to crops. They said that “a 90% cropland allocation yields the highest revenues, ranging from 10.78% to 186.77% ($5.86–34.88/m3) and achieving a land equivalent ratio of 4.40.”
“The FP environmental model suggests limiting cropland to below 60% for optimal emission reductions, reducing emissions to 54.01–112.18 metric tons of CO2 eq/m3, which is lower than emissions from conventional separate crop and solar systems,” noted the scientists.
Assessing the other findings, they said that the models offer benefits, such as identifying diversified revenue streams, promotion of sustainable AgV strategies, or environmental benefits such as reduced irrigation demands, emissions offsets, and minimised land conversion.
“A key takeaway for the PV industry is the considerable increase in land-use efficiency provided by agrivoltaic systems,” said You. “A notable surprise was how strongly optimisation models favoured converting farmland entirely into solar PV areas without careful constraints.”
The researchers see the potential to use the models to prioritise economic, environmental, or balanced system efficiencies, addressing “real-world concerns,” such as agricultural land policy incentives and penalties that are relevant to industry stakeholders, policymakers, and landowners.
“The FP models effectively manage conflicting objectives involving critical resources like irrigation water, complementing the land allocation optimisation achieved by the MINLP models,” said the researchers, adding that topics for future research are uncertainties in water resource availability, market price fluctuations, emission coefficients, incentive interventions, and AgV product yield variability.
Further findings and study details are described in “Techno-economic and environmental optimisation of agrivoltaics: A case study of Cornell University,” in Applied Energy.
When asked about what is next, Fah Kumdokrub, the first author of the research told pv magazine, “Our model prioritizes solar PV over cultivation due to several key factors. However, we are keen to further explore the potential benefits of AgV and refine our approach to address additional considerations in future research.”
“The next steps involve validating and expanding the model across different geographic and climatic regions, enhancing the broader applicability and effectiveness of agrivoltaic practices,” said You
Author: Valerie Thompson
This article was originally published in pv magazine and is republished with permission.
