Solutions/Lusim

Modélisation 3D basée sur le GPU

While simplified geometrical models are sufficient for many photovoltaic systems, they reach their limits when spatial variability and geometry-driven effects play a dominant role. Applications involving complex terrain, surrounding structures, bifacial modules, or agrivoltaic layouts require an explicit three-dimensional representation to evaluate irradiance reliably.

LuSim aborde ces cas grâce à une approche de modélisation 3D basée sur le GPU, conçue pour capturer les interactions géométriques et l'hétérogénéité spatiale sans avoir recours à des hypothèses trop simplifiées.

Explicit 3D representation of photovoltaic systems

LuSim is built on an explicit three-dimensional representation of photovoltaic systems and their surroundings. Terrain, support structures, modules, and nearby objects are modelled directly in space, rather than being reduced to simplified two-dimensional assumptions.

This approach is intended for cases where geometry-driven effects and spatial variability have a direct impact on irradiance distribution and system performance. Shading, mutual interactions between surfaces, and local environmental effects are therefore treated as first-order modelling elements rather than secondary corrections.

Evaluating these effects at high spatial resolution introduces significant computational complexity. In LuSim, this complexity is addressed through a GPU-based simulation framework that allows geometric interactions to be evaluated efficiently while remaining compatible with engineering workflows.

GPU-based computation inspired by real-time 3D graphics

The GPU-based approach adopted in LuSim draws on computational techniques originally developed for real-time 3D graphics and video games, where complex scenes must be rendered efficiently while preserving geometric accuracy.

In computer graphics, these techniques are designed to evaluate visibility, occlusions, and surface interactions across large and detailed three-dimensional environments. The underlying computational problem is structurally similar to irradiance modelling in complex PV systems, where the exchange of radiation depends on geometry, orientation, and mutual visibility between surfaces.

By adapting these mature and highly optimised GPU-based techniques to solar energy modelling, LuSim leverages a computational paradigm that is well suited to handling complex geometries at high spatial resolution. This makes it possible to perform detailed irradiance evaluations while keeping computation times compatible with parametric studies, batch simulations, and uncertainty analyses.

Modélisation de l'irradiation basée sur le facteur de vue

Au cœur de LuSim se trouve une formulation de l'échange d'irradiance entre les surfaces, basée sur le facteur de vue. Chaque élément de surface interagit avec le ciel, le sol et les objets environnants en fonction de leur orientation relative, de leur visibilité et de leurs propriétés optiques.
This formulation is applied consistently in three dimensions and at high spatial resolution. It is used for direct, diffuse, and reflected irradiance components, allowing irradiance to be evaluated locally on photovoltaic modules, ground surfaces, crops, or other targets, rather than being limited to aggregated or lumped values.
By working with spatially resolved irradiance quantities, LuSim makes it possible to analyse heterogeneity effects that are often averaged out in simplified models, such as partial shading, non-uniform albedo, localised bifacial gains, or complex interactions between structures and terrain.

Représentation des matériaux et des surfaces

Surfaces in LuSim are associated with material properties that govern their interaction with incoming radiation. These properties influence reflected irradiance, light redistribution within the scene, and bifacial energy gains. Rather than relying on uniform assumptions or fixed correction factors, materials are represented explicitly in space. This allows the impact of partial coverage, local treatments, heterogeneous ground conditions, or crop characteristics to be analysed consistently within the irradiance model. The level of material detail can be adapted to the objectives of the study, ensuring coherence between modelling effort, physical relevance, and expected accuracy.

Résolution spatiale et temporelle

LuSim évalue l'irradiance avec une résolution spatiale et temporelle explicite. Les cibles peuvent être définies à différentes échelles, depuis les régions de modules individuels jusqu'aux zones agrégées représentant des composants de systèmes plus importants.
This enables the analysis of time-dependent effects such as shading evolution, tracking behaviour, and seasonal variability, as well as spatial patterns that influence system performance, mismatch losses, degradation mechanisms, and uncertainty.
Les choix de résolution sont faits pour équilibrer la pertinence physique et l'efficacité de calcul, en fonction de l'objectif de l'analyse.

Relations avec d'autres approches de modélisation

LuSim supports complete photovoltaic energy yield assessments within a single modelling framework, and is particularly well suited to systems where geometry-driven effects and spatial variability play a dominant role.
Compared to ray tracing approaches, the GPU-based view factor methodology adopted in LuSim offers a different balance between physical detail and computational cost. This makes it particularly well suited for systematic design exploration, multiparameter analyses, and uncertainty studies in complex environments.
The choice of modelling approach should always be guided by the nature of the system being modelled and the questions being addressed.