## 1 Introduction  
Bifacial photovoltaics (PV) has entered the mainstream market in recent years due to enhanced energy yields, which are enabled by the conversion of light impinging on the module's backside into useable photocurrent. A testament to the widespread adoption of bifacial PV is that multi-megawatt-scale bifacial PV projects are now being deployed in latitudes as far north as Denmark (56\({}^{\circ}\) N) in technology neutral auctions [1]. However, the validation of the modeled bifacial performance to the actual performance of fielded systems remains an ongoing task for the PV industry [2; 3; 4; 5; 6]. As more bifacial model validation studies are published from sites around the globe, the expectations that PV buyers and investors have regarding bifacial field performance will be in better alignment with actual field performance. If such validations of bifacial simulations are found to be within acceptable agreement, this has the potential to de-risk bifacial PV investments and thus lower soft costs. A key aim of this study is to contribute to this ongoing bifacial performance model validation effort. The recent bifacial modeling literature contains several studies that include some form of model validation [7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24]. Most bifacial performance model validation to date has been done using small PV systems. A shortcoming of studies on small-scale bifacial systems is that the observed bifacial gains are not representative of bifacial gains at the utility scale. This is because the long and repetitive rows in utility-scale systems lead to a significant amount of self-shading, and since utility-scale strings consist of many modules in series, the backside irradiance enhancement at array edges increases bifacial gain to a much lower extent than on small standalone systems with far less self-shading. Nevertheless, the bifacial validation results reported to date mostly show good agreement to field measurements. For example, the authors in [16] compared the measured irradiance gain and bifacial gain on horizontal single-axis trackers (HSATs) in Eastern Oregon, USA and Albuquerque, USA to view factor (VF) and ray-trace (RT) simulations. They found that the measurements matched their modeled values within the measurement uncertainty. A separate validation study performed by [13] looked at the rear plane of array irradiance (\(G_{POA,Rear}\)) from four simulation tools (pvfactors, bifacialvf, bifacial_radiance, and PVsyst) and compared them to measurements on a fixed-tilt system in Albuquerque, USA and an HSAT system in Davis, USA. Their results showed that the long-term (3 to 12 months) irradiance gain as modeled by these four tools agreed within 1% of their measurements when the ground albedo varied from 0.16 to 0.56. The authors in [20] compared modeled and measured daily energy (kWh) of a single panel within a mechanically maneuverable 12-panel setup in Switzerland. They reported agreement mostly within \(\pm\)1% for static tilt angles from 0\({}^{\circ}\) to 45\({}^{\circ}\). However, the authors mention that a short-coming of their study is that it was only performed over a 3-day period, and go on to conclude that definitive error correlations could emerge if the data were analyzed over longer time scales. The need for bifacial PV model validation on large-scale systems and on long timescales is addressed in this paper. Our objective was to use a consistent set of parameters and meteorological data as input to different bifacial PV software and to analyze the modeled outputs at various steps of the PV performance modeling chain. It was not our intent to analyze the variability that can be introduced by different users of the same software, as this has been studied by other authors [25; 26]. These studies revealed that even expert users can make widely different assumptions for the same parameter or loss factor, and for this reason, we performed a sensitivity analysis on key parameters at the end of this paper.