POTENTIAL EVALUATION OF ROOFTOP DISTRIBUTED PHOTOVOLTAICS BASED ON AERIAL IMAGE RECOGNITION

Li Guiqi; Jin Yi

doi:10.19912/j.0254-0096.tynxb.2024-0594

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (8) : 404-410. DOI: 10.19912/j.0254-0096.tynxb.2024-0594

POTENTIAL EVALUATION OF ROOFTOP DISTRIBUTED PHOTOVOLTAICS BASED ON AERIAL IMAGE RECOGNITION

Li Guiqi, Jin Yi

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Abstract

Using aerial rooftop images as the research object, the photovoltaic power generation potential of regional building roofs was evaluated by image recognition and software simulation. To address the problem of inaccurate extraction of building contours, a gradually optimized multi-scale feature fusion network SOV-net was designed, which takes into account both the global semantics in high-level features and the local details in low-level features, improving the accuracy of roof boundary extraction and the integrity of the contour. Subsequently, available areas were screened, and the roof was classified into folur categories according to spatial structure. This study visualizes the photovoltaic arrays laying scheme and evaluates the maximum photovoltaic power generation potential of the region. The results show that 51754 photovoltaic modules can be laid in this region, with a total annual power generation of 18.65 GWh.

Key words

photovoltaic power / image recognition / deep learning / building extraction / photovoltaic potential

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Li Guiqi, Jin Yi. POTENTIAL EVALUATION OF ROOFTOP DISTRIBUTED PHOTOVOLTAICS BASED ON AERIAL IMAGE RECOGNITION[J]. Acta Energiae Solaris Sinica. 2025, 46(8): 404-410 https://doi.org/10.19912/j.0254-0096.tynxb.2024-0594

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