https://doi.org/10.1051/epjpv/2024025
Original Article
A comprehensive performance evaluation of bifacial photovoltaic modules: insights from a year-long experimental study conducted in the Canadian climate
1
L2EP, University of Lille, Arts et Metiers Institute of Technology, Centrale Lille, Junia, ULR, Lille, France
2
Laboratoire Nanotechnologies Nanosystèmes (LN2) − CNRS UMI-3463 Institut Interdisciplinaire d'Innovation Technologique (3IT), Université de Sherbrooke, Sherbrooke, Québec, Canada
3
e-TESC Lab, Université de Sherbrooke, Sherbrooke, Québec, Canada
* e-mail: ghas2002@usherbrooke.ca
Received:
14
November
2023
Accepted:
29
July
2024
Published online: 10 September 2024
Bifacial photovoltaic (PV) modules, capable of capturing solar energy from both sides of the cells, are becoming increasingly popular as their manufacturing costs approach those of traditional monofacial modules. Accurate estimation of their power generation capacity is essential for optimizing their use. This study evaluates a power production model for bifacial PV modules using local irradiance data from Razon+ in Sherbrooke, Canada, and Solcast irradiance data derived from satellite imagery and weather models. The model's performance was assessed throughout the year, with particular attention to the impact of snow coverage during winter. To address computational efficiency, the study evaluated ray tracing and a 2D view factor model, selecting the more time-efficient method. Experimental validation showed that, using local irradiance data, the model achieved Normalized Root Mean Square Errors (NRMSE) of 18.77%, 4.94%, 3.93%, and 6.22% for winter, spring, summer, and fall, respectively. With Solcast data, the NRMSEs were 22.76%, 15.32%, 14.72%, and 17.78% for the corresponding seasons. While the model performed satisfactorily in spring, summer, and fall, it was less accurate in winter. To enhance winter accuracy, the model incorporated snow coverage, using snow depth as a metric to detect snow on the front surface. This adjustment improved the accuracy by 51.1%.
Key words: Photovoltaic / bifacial PV panels / power model / raytracing technique / view factor approach / snow losses
© S. Ghafiri et al., Published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
