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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

This paper introduces a novel method for generating Typical Meteorological Year (TMY) data for microgrids that employ bifacial photovoltaic modules. The method applies Principal Component Analysis (PCA) to five meteorological parameters that influence the power output of bifacial modules: ambient temperature, Direct Normal Irradiance (DNI), Diffuse Horizontal Irradiance (DHI), albedo, and snow depth. The method selects the most representative months from a 10-year historical data set based on the correlation between the principal components and the original data. The performance of the proposed method is compared with existing methods; Sandia method and NSRDB TMY Method (TMY3), in terms of capturing the interannual variability of the meteorological data and minimizing the average deviation. The comparison is based on the z-score metric and the interannual energy gap, which measure the deviation and the variability of the annual energy yield of a microgrid with 60 bifacial modules. The results show that the proposed method yields a lower z-score (0.20) and a smaller interannual energy gap (5.3%) than the other methods, indicating a closer alignment with the average interannual energy and a higher reliability and accuracy of the optimal sizing and design of microgrids that use bifacial modules.

Accurate modeling of bifacial module energy production is conditioned to the correct modeling of the front and rear irradiance. This paper compares the existing approaches used to estimate the incident irradiance on the back side and the front side of a photovoltaic (PV) bifacial module, by studying the performance of each model in terms of accuracy and computation time. In this study, we have selected three software with different approaches. We started with Bifacial_radiance which uses the ray-tracing technique. The second software is Sandia model which is a three-dimensional implementation of view factor method under MATLAB™. We complete our study with pvfactors that employs a two-dimensional configuration factor model. This study aims to propose the most time-efficient way to compute the irradiances received by bifacial panels, which will serve to predict the energy production of power plants. Having a fast model allows to develop efficient real-time management strategies for power supply systems that use bifacial modules. According to this study, pvfactors has the lowest execution time and gives almost the same output results as Bifacial_radiance and Sandia model that use complex algorithms.

Les distributeurs de services de communication doivent installer des tours de télécommunication même dans les zones reculées afin d’assurer une couverture optimale du réseau de télécommunication sans « zones blanches » à leurs clients. Les zones reculées sont trop éloignées pour être desservies par le réseau électrique. L'une des solutions les plus utilisées est le générateur à combustible fossile (groupe électrogène). Le carburant produit beaucoup d'émissions de CO2 et le coût de l'énergie (COE) est élevé. Les systèmes hybrides utilisant des énergies renouvelables et du stockage peuvent s’avérer plus fiables pour fournir de l'électricité et plus respectueux de l’environnement dans ce cas. Ainsi, ce travail porte sur l'optimisation de la fourniture d'énergie par l'utilisation d'un système multi-source à un site télécom éloigné dans le sud-est du Québec. L'objectif principal est de proposer un système économique et à faibles émissions de CO2. Le logiciel HOMER Pro est utilisé pour concevoir et comparer les résultats pour différentes configurations. Trois sources d'énergie différentes ont été utilisées : l'énergie solaire photovoltaïque avec des panneaux bifaciaux, le groupe électrogène et les batteries Li-ion. Les résultats montrent qu’une configuration avec 60% de renouvelable et du stockage est un bon compromis entre le coût économique et le coût écologique (COE = $0,544/kWh, émissions de CO2 = 9 025 kg/an).