Building integrated photovoltaics that move beyond rooftops
Pingan Ni, Hanjie Zheng, Hongli Sun, Fuming Lei, Yihuan Wang, Jianjun Qin, Wanjiang Wang, Junkang Song, Yingjun Yue, Shanshan Yao, Wenbei Bi, Duo Zhang, Xue Zhang, Jiaqing Yan, Tao Ye, Zengfeng Yan, Guojin Qin, Borong Lin, Bao‐Jie He
Abstract
Building-integrated photovoltaics (BIPVs) are essential for urban decarbonization, yet their potential beyond rooftops remains underexplored. Leveraging multi-source heterogeneous data, high-precision shading computation, and machine learning, this study presents a high-accuracy prediction model for multi-dimensional potential indicators. We identify 10.5 billion m 2 of building surfaces across 75 major cities in China, revealing that the rooftops' mean shading ratio is 2%–10%, while facades range from 15% to 50%. These surfaces can capture 5.73 trillion kWh/a of total solar energy, with rooftops and facades each contributing 50%. The BIPV's effective utilization potential reaches 278 billion kWh/a, 140 billion kWh/a more than rooftops alone, sufficient to meet the annual electricity demands of 334 million urban residents. Furthermore, via BIPV-based electricity supply-demand scenarios simulation and model interpretability analysis, we identify key factors for variation in improving energy-matching ratios in various regions, providing critical insights for national BIPV policy and urban energy planning.