Accelerating the simulation of annual bifacial illumination of real photovoltaic systems with ray tracing

Abstract

Summary Accurate modeling of bifacial illumination is critical to improve the prediction of the energy yield of bifacial solar systems. Monte Carlo ray tracing is the most powerful tool to accomplish this task. In this work, we accelerate Monte Carlo ray tracing of large solar systems by nearly 90%. Our model achieves root-mean-square error values of 7.9% and 37.2% for the front and rear irradiance compared against single-axis tracking field reference data, respectively. The rear irradiance modeling error decreases to 18.9% if suspected snow periods are excluded. Crucially, our full system simulations show that surrounding ground surfaces affect the rear irradiance deep into the system. Therefore, unit system simulations cannot necessarily ignore the influence of the perimeter of large installations to accurately estimate annual yield. Large-scale simulations involving high-performance supercomputing were necessary to investigate these effects accurately, calibrate our simplified models, and validate our results against experimental measurements.

Spectro-angular analysis of roadside-integrated bifacial solar power systems with reflecting sound barriers

“…Not only do we observe a clear difference in magnitude between the irradiance spectra for direct and diffuse irradiance, but also a difference in the spectral content of their curves. Cloud scattering [19] causes the peak wavelength range for diffuse irradiance to be shorter (around 470 nm) compared to direct irradiance (around 680 nm). Finally, figure 5 shows the total integrated diffuse and direct irradiance for all the wavelengths and months.…”

“…Unlike conventional monofacial modules, bifacial modules capture more irradiance by accepting light from both front and rear sides, leading to typically 4%-15% higher energy yield in large PV solar farms and over 20% in rooftop applications [16,17], varying with module mounting height, tilt and ground reflectance, i.e. albedo [17][18][19][20]. Furthermore, adding reflectors in the vicinity of such structures can increase energy yield [12,21], depending on their optical properties.…”

Large‐scale spatiotemporal calculation of photovoltaic capacity factors using ray tracing: A case study in urban environments

“…However, a practical disadvantage of the ray tracing approach is the comparatively high computational demand. Recently, Ernst et al 20 published a ray tracing approach that uses binning of Sun positions for the reduction of computational demand. We extend this approach by using clustering of Sun positions and show that the introduction of relative irradiances can be used for global PV potential calculations.…”

Assessment of solar load models for bifacial PV panels

“…These two values were used in equations developed by Yang (2016), Sun et al (2012), andNoorian et al (2008) to calculate front and rear side irradiance of bifacial solar panel along with view factors which accommodate diffuse surface to surface radiation. To model bifacial illumination of full photovoltaic systems using ray tracing annually, Ernst et al (2022) utilized acceleration strategies that reduced heavy ray tracing requirements by nearly 90%. In Zhao et al (2021)used DIVA for Rhino, a program that uses backward ray tracing method based on Perez model (Perez et al, 1990) and a cumulative sky approach (Robinson and Stone, 2004) to analyze shading and mismatch loss.…”