Comparison Between AgriPV Simulation and Field Data: Soybean Case
Abstract
This study evaluates the accuracy of an integrated radiative and crop-growth simulation framework for predicting soybean yields in Agrivoltaic (AgriPV) systems. Given global concerns about sustainable agriculture and renewable energy, accurately predicting crop yields under AgriPV conditions is critical. Using TMY-based irradiance data, geometric shading analysis, and crop physiological modeling, the study quantified Photosynthetically Active Radiation (PAR) availability and simulated biomass production during a summer cropping season. Results indicated PAR represented 40.93% of Global Horizontal Irradiance (GHI), reflecting significant photovoltaic module shading. Simulated yields differed by only 8.68% from measured field data, demonstrating strong correlation and validating the model’s reliability. These findings confirm the developed radiative and crop modeling framework's applicability for AgriPV system planning, offering a robust tool for optimizing integrated energy-crop production while ensuring agricultural viability.
Keywords
Agrivoltaics, Radiative Modeling, Crop Modeling, PAR