Research on 3D voxel-based cumulus cloud modeling method using ground-based cloud images

Abstract

[Objective] The rapid formation and movement of cumulus clouds are the main meteorological factors causing fluctuations in photovoltaic(PV) power output, and their shading effects on solar irradiance significantly affect the operational stability of PV systems and the accuracy of power prediction. However, traditional cumulus cloud modeling method based on 2D images fail to reflect the structural variation of clouds in the vertical direction and lack effective expression of key physical parameters such as cloud base height, cloud thickness, and internal particle distribution, making it difficult to meet the modeling requirements for high resolution, real-time performance, and physical consistency in PV applications. [Methods] To address this, a 3D voxel-based cumulus cloud modeling method using ground-based cloud images was proposed. The geographic positioning of cumulus regions was achieved through image preprocessing and spatial registration. An automatic extraction method for cloud base height and cloud thickness for cumulus clouds was proposed, and a cloud particle density parameter was introduced to construct a voxel expression model with physical constraints. Combined with a GPU rendering pipeline, efficient modeling and visualization of cumulus cloud morphology and internal characteristics were realized. [Results] The experimental result showed that the calculated cloud base height had a relative error within 5% compared to remote sensing inversion result. The cloud particle density distribution was consistent with CloudSat profile observations. The GPU-based method outperformed traditional method in modeling efficiency and rendering performance, maintaining stable frame rates in 3D scene interaction. [Conclusion] The findings demonstrate that this method can achieve rapid reconstruction and efficient visualization of cumulus clouds, verifying the feasibility and accuracy of extracting key parameters based on ground-based cloud images and providing an effective model and data support for PV power prediction.

Keywords

ground-based cloud image / 3D cumulus cloud modeling / voxel modeling / cloud particle density / GPU rendering / influencing factors