A novel approach for assessing rooftop-and-facade solar photovoltaic potential in rural areas using three-dimensional (3D) building models constructed with GIS

Jiang Liu, Qifeng Wu, Zhipeng Lin, Huijie Shi, Shaoyang Wen, Qiaoyu Wu, Junxue Zhang and Changhai Peng

Energy, 2023, vol. 282, issue C

Abstract: Characterization of solar photovoltaic (PV) potential is crucial for promoting renewable energy in rural areas, where there are a large number of roofs and facades ideal for PV module installation. However, accurately estimating solar PV potential on three-dimensional (3D) rural surfaces has been challenging due to the lack of 3D building models. To address this issue, we proposed a novel approach, which for the first time constructs rural 3D building models from publicly available satellite images and vector maps. Based on these models, it precisely evaluates the solar PV potential of rural rooftops and facades. The approach was validated against two realistic 3D village models and on-site solar radiation measurements. Using the validated approach, case studies in a village and on a large-scale island were conducted, respectively. The results showed that rural rooftops facing south and north, and facades facing south and west, have the highest PV potential ranks. North-facing rooftops with a slope of 30° represent 32.7% of the total rooftop solar PV potential, therefore, they should not be neglected in future evaluations. The proposed approach is cost-effective and valid for accurately assessing micro- and macro-scale rural solar PV potential that can facilitate rural renewable energy penetration.

Keywords: Rural area; Solar photovoltaic potential; GIS; Random forest; 3D building model (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:282:y:2023:i:c:s0360544223023149

DOI: 10.1016/j.energy.2023.128920

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