LiDAR‐Enhanced Modeling of Vertical Bifacial Photovoltaic Systems: Collaborative Insights from a Round‐Robin Simulation Study

Vertical bifacial photovoltaic (PV) systems offer significant advantages in land‐use efficiency and energy yield, yet their performance is highly sensitive to environmental factors such as terrain topography, vegetation, module orientation, and ground albedo. Accurate prediction of energy yield is therefore critical for economic assessment and project bankability, but remains challenging due to complex rear‐side irradiance contributions and diffuse light capture. This study investigates a linear vertical bifacial PV installation in the Rhône valley, southeastern France, employing high‐resolution drone‐based LiDAR data to create a detailed 3D representation of terrain, vegetation, and PV modules. Within the H2020 SERENDI‐PV project, four partners—CEA, Cythelia, Lucisun, and Solargis—applied their proprietary PV modeling tools to simulate module‐level and plant‐scale energy yields, shading losses, and direct/diffuse irradiance profiles. A round‐robin framework enabled cross‐comparison and validation against high‐resolution monitoring data from microinverters, revealing that all tools reproduced the characteristic double‐peak diurnal energy profile of vertical bifacial arrays, while residual discrepancies were mainly associated with low‐angle shading transitions. Key insights include the dominance of shading and diffuse light in energy variability, the critical role of high‐fidelity site characterization, and the complementary strengths of GPU‐accelerated and harmonized modeling approaches. At the plant scale, annual energy prediction deviations were reduced to 2%–4%, demonstrating that LiDAR‐enhanced modeling combined with advanced simulation tools provides a robust, bankable framework for vertical bifacial PV performance assessment. These results highlight pathways for improved modeling, including spectrally‐resolved irradiance, dynamic albedo incorporation, and standardized LiDAR‐to‐simulation workflows.

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Publication Details

Journal
Solar RRL
Published
2025-11-11
DOI
https://doi.org/10.1002/solr.202500763
Primary Topic
Solar Radiation and Photovoltaics
Type
article
Field-Weighted Citation Impact
0.00

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article

LiDAR‐Enhanced Modeling of Vertical Bifacial Photovoltaic Systems: Collaborative Insights from a Round‐Robin Simulation Study

Hervé Colin, Ismaël Lokhat, Branislav Schnierer, Martin Opatovsky et al.
Solar RRL
Solar Radiation and Photovoltaics
article

LiDAR‐Enhanced Modeling of Vertical Bifacial Photovoltaic Systems: Collaborative Insights from a Round‐Robin Simulation Study

Hervé Colin, Ismaël Lokhat, Branislav Schnierer, Martin Opatovsky, John A. Tsanakas, Stéphane Mollier, Jesús Robledo, Jonathan Leloux, S. Prithivi Rajan, Michal Zrubec, Daniel Chrkavy
article en

Abstract

Vertical bifacial photovoltaic (PV) systems offer significant advantages in land‐use efficiency and energy yield, yet their performance is highly sensitive to environmental factors such as terrain topography, vegetation, module orientation, and ground albedo. Accurate prediction of energy yield is therefore critical for economic assessment and project bankability, but remains challenging due to complex rear‐side irradiance contributions and diffuse light capture. This study investigates a linear vertical bifacial PV installation in the Rhône valley, southeastern France, employing high‐resolution drone‐based LiDAR data to create a detailed 3D representation of terrain, vegetation, and PV modules. Within the H2020 SERENDI‐PV project, four partners—CEA, Cythelia, Lucisun, and Solargis—applied their proprietary PV modeling tools to simulate module‐level and plant‐scale energy yields, shading losses, and direct/diffuse irradiance profiles. A round‐robin framework enabled cross‐comparison and validation against high‐resolution monitoring data from microinverters, revealing that all tools reproduced the characteristic double‐peak diurnal energy profile of vertical bifacial arrays, while residual discrepancies were mainly associated with low‐angle shading transitions. Key insights include the dominance of shading and diffuse light in energy variability, the critical role of high‐fidelity site characterization, and the complementary strengths of GPU‐accelerated and harmonized modeling approaches. At the plant scale, annual energy prediction deviations were reduced to 2%–4%, demonstrating that LiDAR‐enhanced modeling combined with advanced simulation tools provides a robust, bankable framework for vertical bifacial PV performance assessment. These results highlight pathways for improved modeling, including spectrally‐resolved irradiance, dynamic albedo incorporation, and standardized LiDAR‐to‐simulation workflows.

Solar RRLVol. 9(24)
Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR), Laboratoire d’Innovation pour les Technologies des Énergies Nouvelles et les nanomatériaux (FR), Cythelia (France) (FR), GeoModel Solar (Slovakia) (SK), Haute École de la Ville de Liège (BE), Université Grenoble Alpes (FR)
Compagnie Nationale du Rhône, European Commission, Agence Nationale de la Recherche, Horizon 2020 Framework Programme
Openalex Percentile: Top 82%
Solar Radiation and Photovoltaics
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