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<p>As building-integrated photovoltaic (BIPV) facade systems are applied to the facades of high-density urban building clusters, complex dynamic shadows significantly impact the photovoltaic (PV) performance of the buildings. However, existing methods for calculating building surface shadows exhibit low computational efficiency in handling complex high-density scenarios. This paper proposes a multiscale spatiotemporal selection (MSTS) calculation method for dynamic shadows in complex, high-density environments. The method eliminates irrelevant building surfaces from both spatial and temporal dimensions, and utilizes the interpolation method to reduce the number of calculations. It integrates a “direction-distance-backlit-temporal” selection model and provides an optimal sorting scheme to accelerate the preprocessing of shadow calculations. This study validates the computational efficiency and accuracy of the proposed MSTS method through two practical case studies. In Case 1, focusing on a PV facade within a complex high-density building clusters in downtown Chengdu, the method achieved a 96% reduction in computational time compared to mature commercial software and at least a 45% improvement over existing acceleration methods, with a mean absolute percentage error (MAPE) of 1.6% for the sunlit area ratio (SAR). The results indicate that, compared to existing methods, the proposed approach significantly improves computational efficiency while maintaining a high level of accuracy. In Case 2, concerning a PV facade in an industrial park in Zhuhai, a comparison with data from an on-site experimental platform yielded an SAR MAPE of 1.83% over the study period. In summary, the calculated results demonstrate a high degree of consistency with real-world observations, with only minimal deviations, thereby validating the reliability of the proposed approach. These results indicate that the proposed method can efficiently and accurately evaluate the shading effects in complex, high-density urban environments, thereby providing robust support for the performance assessment of BIPV facade systems.</p>

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A multiscale spatiotemporal selection calculation method for dynamic shadows in complex high-density building clusters

  • 期刊论文

  • 发表日期：

    2025年10月29日

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  • Dawei Ruan,
  • Mingwei Hu,
  • Cheng Fan,
  • Jun Guan

摘要

As building-integrated photovoltaic (BIPV) facade systems are applied to the facades of high-density urban building clusters, complex dynamic shadows significantly impact the photovoltaic (PV) performance of the buildings. However, existing methods for calculating building surface shadows exhibit low computational efficiency in handling complex high-density scenarios. This paper proposes a multiscale spatiotemporal selection (MSTS) calculation method for dynamic shadows in complex, high-density environments. The method eliminates irrelevant building surfaces from both spatial and temporal dimensions, and utilizes the interpolation method to reduce the number of calculations. It integrates a “direction-distance-backlit-temporal” selection model and provides an optimal sorting scheme to accelerate the preprocessing of shadow calculations. This study validates the computational efficiency and accuracy of the proposed MSTS method through two practical case studies. In Case 1, focusing on a PV facade within a complex high-density building clusters in downtown Chengdu, the method achieved a 96% reduction in computational time compared to mature commercial software and at least a 45% improvement over existing acceleration methods, with a mean absolute percentage error (MAPE) of 1.6% for the sunlit area ratio (SAR). The results indicate that, compared to existing methods, the proposed approach significantly improves computational efficiency while maintaining a high level of accuracy. In Case 2, concerning a PV facade in an industrial park in Zhuhai, a comparison with data from an on-site experimental platform yielded an SAR MAPE of 1.83% over the study period. In summary, the calculated results demonstrate a high degree of consistency with real-world observations, with only minimal deviations, thereby validating the reliability of the proposed approach. These results indicate that the proposed method can efficiently and accurately evaluate the shading effects in complex, high-density urban environments, thereby providing robust support for the performance assessment of BIPV facade systems.