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Computer Science > Information Retrieval

arXiv:2412.01291 (cs)
[Submitted on 2 Dec 2024 ]

Title: Global Estimation of Building-Integrated Facade and Rooftop Photovoltaic Potential by Integrating 3D Building Footprint and Spatio-Temporal Datasets

Title: 基于整合三维建筑轮廓和时空数据的建筑一体化立面和屋顶光伏潜力全局估算

Authors:Qing Yu, Kechuan Dong, Zhiling Guo, Jiaxing Li, Hongjun Tan, Yanxiu Jin, Jian Yuan, Haoran Zhang, Junwei Liu, Qi Chen, Jinyue Yan
Abstract: This research tackles the challenges of estimating Building-Integrated Photovoltaics (BIPV) potential across various temporal and spatial scales, accounting for different geographical climates and urban morphology. We introduce a holistic methodology for evaluating BIPV potential, integrating 3D building footprint models with diverse meteorological data sources to account for dynamic shadow effects. The approach enables the assessment of PV potential on facades and rooftops at different levels-individual buildings, urban blocks, and cities globally. Through an analysis of 120 typical cities, we highlight the importance of 3D building forms, cityscape morphology, and geographic positioning in measuring BIPV potential at various levels. In particular, our simulation study reveals that among cities with optimal facade PV performance, the average ratio of facade PV potential to rooftop PV potential is approximately 68.2%. Additionally, approximately 17.5% of the analyzed samples demonstrate even higher facade PV potentials compared to rooftop installations. This finding underscores the strategic value of incorporating facade PV applications into urban sustainable energy systems.
Abstract: 这项研究解决了在不同时间和空间尺度上估算建筑一体化光伏(BIPV)潜力的挑战,考虑了不同的地理气候和城市形态。我们引入了一种全面的方法来评估BIPV潜力,将三维建筑轮廓模型与多种气象数据源相结合,以考虑动态阴影效应。该方法能够评估不同层次上的光伏潜力——单个建筑、城市街区和全球城市。通过对120个典型城市的分析,我们强调了三维建筑形式、城市景观形态和地理位置在不同层次上衡量BIPV潜力的重要性。特别是,我们的模拟研究表明,在具有最佳立面光伏性能的城市中,立面光伏潜力与屋顶光伏潜力的平均比值约为68.2%。此外,大约17.5%的分析样本显示,其立面光伏潜力甚至高于屋顶安装。这一发现突显了将立面光伏应用纳入城市可持续能源系统的战略价值。
Comments: 17 pages, 5 figures
Subjects: Information Retrieval (cs.IR) ; Emerging Technologies (cs.ET)
Cite as: arXiv:2412.01291 [cs.IR]
  (or arXiv:2412.01291v1 [cs.IR] for this version)
  https://doi.org/10.48550/arXiv.2412.01291
arXiv-issued DOI via DataCite

Submission history

From: Qing Yu [view email]
[v1] Mon, 2 Dec 2024 09:04:16 UTC (8,038 KB)
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