A novel acceleration approach to shadow calculation based on sunlight channel for urban building energy modeling

被引:3
作者
Liu, Zhaoru [1 ]
Zhou, Xin [2 ]
Shen, Xiaohan [2 ]
Sun, Hongsan [1 ]
Yan, Da [1 ]
机构
[1] Tsinghua Univ, Bldg Energy Res Ctr, Sch Architecture, Beijing 100084, Peoples R China
[2] Southeast Univ, Sch Architecture, Nanjing 210096, Jiangsu, Peoples R China
关键词
Shadow calculation; Urban environment; Polygon clipping; Building performance simulation; Urban building energy modeling; SOLAR-RADIATION; SIMULATION; INSTALLATION; PERFORMANCE;
D O I
10.1016/j.enbuild.2024.114244
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Shadow effect among buildings has great impacts on the building energy consumption and the performance of building photovoltaic, and calculating shadows on building surfaces in urban building energy modeling (UBEM) faces challenges of inefficiency, especially for dense urban areas. In this study, a novel shadow calculation approach based on sunlight channel is proposed that can streamline the surrounding environment and accelerate the shadow calculation process. The sunlight-channel algorithm can further accelerate the shadow calculation process by dynamically predetermining the shading surfaces according to the actual solar position. In a real urban context, the proposed approach can accelerate the computation process by over 10 times over the baseline and over 34 times over the non-accelerated method, with a mean absolute percentage error (MAPE) of 1.13% for the total solar radiation. The proposed approach copes well with both large-scale urban models and the complexity of building structures, particularly for urban models with complex changes in building heights. This approach can significantly enhance the computational efficiency in complex urban environments, facilitating an accurate and rapid analysis of the energy consumption and solar potential of buildings in dense cities.
引用
收藏
页数:14
相关论文
共 48 条
  • [1] Review of urban building energy modeling (UBEM) approaches, methods and tools using qualitative and quantitative analysis
    Ali, Usman
    Shamsi, Mohammad Haris
    Hoare, Cathal
    Mangina, Eleni
    O'Donnell, James
    [J]. ENERGY AND BUILDINGS, 2021, 246
  • [2] Shadow modeling in urban environments for solar harvesting devices with freely defined positions and orientations
    Arias-Rosales, Andres
    LeDuc, Philip R.
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2022, 164
  • [3] Global Building Morphology Indicators
    Biljecki, Filip
    Chow, Yoong Shin
    [J]. COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 2022, 95
  • [4] Biljecki F, 2017, LECT NOTES GEOINF CA, P31, DOI 10.1007/978-3-319-25691-7_2
  • [5] Acceleration of state-space method based on parallelization for enhancing building thermal process simulation efficiency
    Bu, Fan
    Kang, Xuyuan
    Yan, Da
    Wu, Ruhong
    Sun, Hongsan
    An, Jingjing
    Wang, Xiao
    [J]. ENERGY AND BUILDINGS, 2023, 299
  • [6] Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis
    Chen, Yixing
    Hong, Tianzhen
    Piette, Mary Ann
    [J]. APPLIED ENERGY, 2017, 205 : 323 - 335
  • [7] A pixel counting based method for designing shading devices in buildings considering energy efficiency, daylight use and fading protection
    de Almeida Rocha, Ana Paula
    Reynoso-Meza, Gilberto
    Oliveira, Ricardo C. L. F.
    Mendes, Nathan
    [J]. APPLIED ENERGY, 2020, 262 (262)
  • [8] Performance of 170 grid connected PV plants in northern Germany - Analysis of yields and optimization potentials
    Decker, B
    Jahn, U
    [J]. SOLAR ENERGY, 1997, 59 (4-6) : 127 - 133
  • [9] Using urban building energy modeling to quantify the energy performance of residential buildings under climate change
    Deng, Zhang
    Javanroodi, Kavan
    Nik, Vahid M. M.
    Chen, Yixing
    [J]. BUILDING SIMULATION, 2023, 16 (09) : 1629 - 1643
  • [10] Archetype identification and urban building energy modeling for city-scale buildings based on GIS datasets
    Deng, Zhang
    Chen, Yixing
    Yang, Jingjing
    Chen, Zhihua
    [J]. BUILDING SIMULATION, 2022, 15 (09) : 1547 - 1559