Shading-Aware Rooftop PV Placement

2026-09-19

AI Summary

本文针对屋顶光伏板布局问题，提出了一种考虑阴影影响的方法，通过模拟日照和计算阴影来优化现有及新安装的光伏板布局，以提高发电效率。

Abstract

Rooftop photovoltaic (PV) design requires careful panel placement to make effective use of potentially limited roof space and available sunlight. Existing simplified roof models can miss objects and superstructures that shade panels. We simulate rooftop irradiance using hourly weather and a terrain horizon, computing shadows from nearby buildings, trees, and roof superstructures rendered from the Sun's viewpoint. Our method (i) infers existing panel layouts from imagery and estimates their yield, (ii) relocates these panels to improve the yield, and (iii) generates shading-aware layouts for new installations. We compare modeled yield with production records from 11 Swiss installations and evaluate new layouts in simulation on 19 additional rural roofs. Without knowledge of any electrical or system specifications, we obtain a median daily correlation with measured production of 0.982. Absolute energy estimates remain sensitive to system specifications. Comparing new layouts with equal panel counts, accounting for neighborhood and roof-detail shading changes the position or orientation of an average of 38.9\% of panels per roof. These layouts increase modeled annual yield by up to 7.91\% compared with layouts designed without accounting for neighborhood and roof-detail shadows. We publicly release our tool for modeling and designing rooftop PV installations with terrain, neighborhood, and roof-detail shading at https://github.com/tobiasvonarx/shading-aware-pv.

Problem

• Rooftop Photovoltaic
• Shading
• Panel Placement
• Roof Space
• Sunlight

Innovation

• shading-aware
• rooftop PV placement
• yield improvement
• shadow simulation
• image-based panel layout inference