English

Optimization and Performance of Bifacial Solar Modules: A Global Perspective

Applied Physics 2018-02-22 v3 Optics

Abstract

With the rapidly growing interest in bifacial photovoltaics (PV), a worldwide map of their potential performance can help assess and accelerate the global deployment of this emerging technology. However, the existing literature only highlights optimized bifacial PV for a few geographic locations or develops worldwide performance maps for very specific configurations, such as the vertical installation. It is still difficult to translate these location- and configuration-specific conclusions to a general optimized performance of this technology. In this paper, we present a global study and optimization of bifacial solar modules using a rigorous and comprehensive modeling framework. Our results demonstrate that with a low albedo of 0.25, the bifacial gain of ground-mounted bifacial modules is less than 10% worldwide. However, increasing the albedo to 0.5 and elevating modules 1 m above the ground can boost the bifacial gain to 30%. Moreover, we derive a set of empirical design rules, which optimize bifacial solar modules across the world, that provide the groundwork for rapid assessment of the location-specific performance. We find that ground-mounted, vertical, east-west-facing bifacial modules will outperform their south-north-facing, optimally tilted counterparts by up to 15% below the latitude of 30 degrees, for an albedo of 0.5. The relative energy output is the reverse of this in latitudes above 30 degrees. A detailed and systematic comparison with experimental data from Asia, Europe, and North America validates the model presented in this paper. An online simulation tool (https://nanohub.org/tools/pub) based on the model developed in this paper is also available for a user to predict and optimize bifacial modules in any arbitrary location across the globe.

Keywords

Cite

@article{arxiv.1709.10026,
  title  = {Optimization and Performance of Bifacial Solar Modules: A Global Perspective},
  author = {Xingshu Sun and Mohammad Ryyan Khan and Chris Deline and Muhammad Ashraful Alam},
  journal= {arXiv preprint arXiv:1709.10026},
  year   = {2018}
}
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