An accurate and up-to-date model of a photovoltaic (PV) power plant is essential for its optimal operation and maintenance. However, such a model may not be easily available. This work introduces a novel approach for PV power plant mapping based on aerial overview images. It enables the automation of the mapping process while removing the reliance on third-party data. The presented mapping method takes advantage of the structural layout of the power plants to achieve detailed modeling down to the level of individual PV modules. The approach relies on visual segmentation of PV modules in overview images and the inference of structural information in each image, assigning modules to individual benches, rows, and columns. We identify visual keypoints related to the layout and use these to merge detections from multiple images while maintaining their structural integrity. The presented method was experimentally verified and evaluated on two different power plants. The final fusion of 3D positions and semantic structures results in a compact georeferenced model suitable for power plant maintenance.

翻译：光伏电站的精确且更新的模型对其优化运行和维护至关重要，然而此类模型往往难以直接获取。本研究提出一种基于航拍全景图像的光伏电站测绘新方法。该方法实现了测绘过程的自动化，同时消除了对第三方数据的依赖。所提出的测绘方法利用电站的结构布局，实现了精细至单个光伏组件的建模。该方法依赖于全景图像中光伏组件的视觉分割及单张图像结构信息的推理，将组件分配至具体的阵列、行与列。我们识别与布局相关的视觉关键点，并利用这些关键点融合多幅图像的检测结果，同时保持其结构完整性。所提方法在两个不同电站上进行了实验验证与评估。三维位置与语义结构的最终融合生成了适用于电站维护的紧凑地理参考模型。