Skip to main navigation Skip to search Skip to main content

Photosynthetically active radiation separation model for high-latitude regions in agrivoltaic systems modeling

  • S. Ma Lu*
  • , D. Yang
  • , M. C. Anderson
  • , S. Zainali
  • , B. Stridh
  • , A. Avelin
  • , P. E. Campana
  • *Corresponding author for this work
  • Mälardalen University
  • School of Electrical Engineering and Automation, Harbin Institute of Technology
  • United States Department of Agriculture

Research output: Contribution to journalArticlepeer-review

Abstract

Photosynthetically active radiation is a key parameter for determining crop yield. Separating photosynthetically active radiation into direct and diffuse components is significant to agrivoltaic systems. The varying shading conditions caused by the solar panels produce a higher contribution of diffuse irradiance reaching the crops. This study introduces a new separation model capable of accurately estimating the diffuse component from the global photosynthetically active radiation and conveniently retrievable meteorological parameters. The model modifies one of the highest-performing separation models for broadband irradiance, namely, the Yang2 model. Four new predictors are added: atmospheric optical thickness, vapor pressure deficit, aerosol optical depth, and surface albedo. The proposed model has been calibrated, tested, and validated at three sites in Sweden with latitudes above 58 °N, outperforming four other models in all examined locations, with R2 values greater than 0.90. The applicability of the developed model is demonstrated using data retrieved from Sweden's first agrivoltaic system. A variety of data availability cases representative of current and future agrivoltaic systems is tested. If on-site measurements of diffuse photosynthetically active radiation are not available, the model calibrated based on nearby stations can be a suitable first approximation, obtaining an R2 of 0.89. Utilizing predictor values derived from satellite data is an alternative method, but the spatial resolution must be considered cautiously as the R2 dropped to 0.73.

Original languageEnglish
Article number013503
JournalJournal of Renewable and Sustainable Energy
Volume16
Issue number1
DOIs
StatePublished - 1 Jan 2024
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Fingerprint

Dive into the research topics of 'Photosynthetically active radiation separation model for high-latitude regions in agrivoltaic systems modeling'. Together they form a unique fingerprint.

Cite this