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<p>This study investigates the accuracy of PVsyst version 7.4 in predicting the performance of bifacial photovoltaic modules. To validate the simulation results, a comprehensive experimental study was conducted, systematically varying the tilt angle of the module and recording its energy output. The analysis revealed that both simulation and experimental data indicated a similar trend, with peak performance observed at a tilt angle of approximately 30 degrees. Beyond this angle, a decline in energy output was noted. These results highlight the importance of optimizing tilt angles for maximizing energy output from bifacial photovoltaic installations. However, a significant discrepancy emerged between the simulated and experimental results. The PVsyst model consistently underestimated the actual energy output, with a substantial mean bias error of − 54%. This substantial difference implies that the software may require further refinement to accurately predict the performance of bifacial modules. The Mean Squared Error and Root Mean Squared Error of 0.376 and 0.613, respectively indicates statistical measure of the simulation’s deviation from empirical data. This research highlights the critical role of ground surface reflectivity, especially when ground surface is painted using white paint, in improving the performance of bifacial PV modules. The research suggests the need for further investigation into seasonal variations, meteorological conditions, and other factors affecting solar panel performance to improve simulation accuracy and optimize energy output. By comparing simulated and experimental data, this study contributes to the growing body of knowledge on bifacial photovoltaic technology and simulation software accuracy. The findings can guide solar energy professionals in optimizing module installations and help software developers enhance their simulation tools. Ultimately, these advancements will contribute to more efficient and reliable solar energy systems, supporting the transition to sustainable energy sources.</p>

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Assessing the accuracy of PVsyst for modelling bifacial PV systems: a field validation study

  • 期刊论文

  • 发表日期：

    2026年7月11日

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  • Achintya Basak,
  • Suprava Chakraborty,
  • Aruna Kumar Behura

摘要

This study investigates the accuracy of PVsyst version 7.4 in predicting the performance of bifacial photovoltaic modules. To validate the simulation results, a comprehensive experimental study was conducted, systematically varying the tilt angle of the module and recording its energy output. The analysis revealed that both simulation and experimental data indicated a similar trend, with peak performance observed at a tilt angle of approximately 30 degrees. Beyond this angle, a decline in energy output was noted. These results highlight the importance of optimizing tilt angles for maximizing energy output from bifacial photovoltaic installations. However, a significant discrepancy emerged between the simulated and experimental results. The PVsyst model consistently underestimated the actual energy output, with a substantial mean bias error of − 54%. This substantial difference implies that the software may require further refinement to accurately predict the performance of bifacial modules. The Mean Squared Error and Root Mean Squared Error of 0.376 and 0.613, respectively indicates statistical measure of the simulation’s deviation from empirical data. This research highlights the critical role of ground surface reflectivity, especially when ground surface is painted using white paint, in improving the performance of bifacial PV modules. The research suggests the need for further investigation into seasonal variations, meteorological conditions, and other factors affecting solar panel performance to improve simulation accuracy and optimize energy output. By comparing simulated and experimental data, this study contributes to the growing body of knowledge on bifacial photovoltaic technology and simulation software accuracy. The findings can guide solar energy professionals in optimizing module installations and help software developers enhance their simulation tools. Ultimately, these advancements will contribute to more efficient and reliable solar energy systems, supporting the transition to sustainable energy sources.