Researchers in Spain assessed six models used to calculate angle of incidence modifier (IAM) losses in photovoltaic systems. They identified the Martín-Ruiz model as the most comprehensive, as it uniquely accounts for additional angular losses caused by contamination.
Researchers from the Technical University of Madrid have completed a comprehensive review of modeling tools used to measure the angle of incidence modifier (IAM) – a factor that describes how the optical efficiency of photovoltaic (PV) modules changes as the sun’s rays deviate from a line perpendicular to the module surface.
The team explained that IAM losses in PV systems are mainly reflection losses caused by changes in the optical properties of materials when light passes from the air to the solar cells. These losses are more pronounced on panels affected by contamination. “Annual IAM losses, commonly referred to as annual angle losses (AAL), represent between 1% and 5% of annual energy yield in utility-scale PV installations,” the researchers pointed out. “This is significant enough to consider when modeling system performance.”
The research team described six IAM models: the ASHRAE model, the simplest approach, adopted by the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE); the Air-Glass model, which only considers the air-glass interface and uses a single refractive index value(s); the Martín-Ruiz model, specifically recommended in the IEC 61853-2 standard for describing corresponding IAM experimental results; the Sandia IAM database, which the scientists described as “no longer supported” and “outdated”; the physical model, based on Snell and Bouguer’s laws; and the Eye-Sensitivity model, which simulates how the human eye adapts to varying light levels, especially in high dynamic range environments.
After evaluation, the team rejected the Sandia model because it was not supported and the physical model because of its complexity. The remaining four models were implemented to simulate the front and back of PV modules in SISIFO, a PV performance simulation tool available in both free and premium versions.
“This was followed by an extensive simulation exercise, which included both static and tracked PV arrays at three different latitudes, aimed at understanding the impact of IAM losses and the compatibility between the different IAM models,” they explained. “This allows software improvements to be validated against real PV installations, reducing uncertainty in annual energy calculations.”
To assess the real impact of IAM losses and the effectiveness of the proposed models, the researchers performed simulations of front AAL radiation losses at three locations at different latitudes, using two types of monofacial PV installations based on solid structure and single-axis trackers, respectively.
The results indicated that the Air-Glass model overestimates the annual angular losses for direct and reflected irradiation, while underestimating the losses for isotropic diffuse irradiation. Meanwhile, the Eye-Sensitivity model consistently predicted a significantly lower AAL than the other models.
The Martín-Ruiz model stood out as the only model capable of calculating annual additional angular loss due to contamination. “As a reference, for a 2% loss of perpendicular irradiation due to pollution, this model estimates an additional AAL of 0.5%, 0.9%, and 1.2% for single-axis trackers in Chile, Spain, and Sweden, respectively, and 1.0%, 1.3%, and 1.7% for static PV installations. This underlines our recommendation to include this additional loss in other models that do not take it into account,” the team noted.
The researchers concluded that their assessment provides a valuable tool for measuring IAM losses in PV modules with clear glass or anti-reflective (AR) coatings. “Annual losses in all models were consistent within 0.2%, ensuring reliable accuracy in all cases. Overall, annual energy losses range from 1% to 5% depending on the IAM model used,” they stated.
Their work is presented in “Angular losses in photovoltaic energy estimation: a review of models and a comparative analysis using the improved SISIFO simulation tool”, published in Renewable and sustainable energy assessments.
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