Estimation of building surface solar irradiance based on photogrammetry matching point cloud

doi:10.13474/j.cnki.11-2246.2023.0271

Abstract

Abstract: Aiming at the problems that the current solar irradiance evaluation methods of buildings are difficult to take into account both the roof and the facade of the building, and the laser point cloud data cost is high, which is not suitable for obtaining the point cloud of the building surface in a large range and high density. In this paper, an integrated evaluation method for building surface solar irradiance based on dense matching point clouds of slanted images is proposed. The main content of this method is to obtain the 3D building model of the area of interest by using the UAV oblique image, and to simulate the shadow and calculate the solar irradiance of the building surface by combining the shadow simulation algorithm and the simplified solar radiation model. The experimental results show that this method can accurately calculate the solar irradiance of the building surface, which not only expands the application range of tilt photogrammetry, but also provides reliable data support for assisting architects in designing the building surface and maximizing the use of solar energy on the building surface.

Key words: oblique photogrammetry, dense matching point cloud, building 3D model, solar energy, shadow simulation

CLC Number:

P237

DAI Zhisheng, WANG Pengfei, ZHOU Guangjian. Estimation of building surface solar irradiance based on photogrammetry matching point cloud[J]. Bulletin of Surveying and Mapping, 2023, 0(9): 93-99.

References

[1] 滕吉文,张永谦,阮小敏. 发展可再生能源和新能源与必须深层次思考的几个科学问题——非化石能源发展的必由之路[J]. 地球物理学进展,2010,25(4):1115-1152.
[2] 商佳棋,杨旭,陈颖,等. 基于PVsyst的既有建筑光伏一体化系统仿真与优化[J]. 能源研究与管理,2021(2):130-134.
[3] CATITA C,REDWEIK P,PEREIRA J,et al. Extending solar potential analysis in buildings to vertical facades[J]. Computers & Geosciences,2014,66:1-12.
[4] DESTHIEUX G,CARNEIRO C,CAMPONOVO R,et al. Solar energy potential assessment on rooftops and facades in large built environments based on LiDAR data,image processing,and cloud computing. methodological background,application,and validation in Geneva (solar cadaster)[J]. Frontiers in Built Environment,2018,4:14.
[5] ZHANG Xianfeng,LÜ Yang,TIAN Jie,et al. An integrative approach for solar energy potential estimation through 3D modeling of buildings and trees[J]. Canadian Journal of Remote Sensing,2015,41(2):126-134.
[6] LI Ziqi,ZHANG Zidong,DAVEY K. Estimating geographical PV potential using LiDAR data for buildings in downtown San Francisco[J]. Transactions in GIS,2015,19(6):930-963.
[7] 眭海刚,陈松林,朱庆. 基于数码城市GIS的日照分析系统的设计与实现[J]. 计算机应用研究,2004,21(6):164-167.
[8] LINGFORS D,BRIGHT J M,ENGERER N A,et al. Comparing the capability of low-and high-resolution LiDAR data with application to solar resource assessment,roof type classification and shading analysis[J]. Applied Energy,2017,205:1216-1230.
[9] JOCHEM A,HÖFLE B,RUTZINGER M. Extraction of vertical walls from mobile laser scanning data for solar potential assessment[J]. Remote Sensing,2011,3(4):650-667.
[10] 梁福逊,杨必胜,黄荣刚,等. 基于多源点云的建筑物立面太阳能潜力估计[J]. 测绘学报,2018,47(2):225-233.
[11] HUANG Pengdi,CHENG Ming,CHEN Yiping,et al. Solar potential analysis method using terrestrial laser scanning point clouds[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2017,10(3):1221-1233.
[12] YU Bailang,LIU Hongxing,WU Jianping,et al. Investigating impacts of urban morphology on spatio-temporal variations of solar radiation with airborne LiDAR data and a solar flux model:a case study of downtown Houston[J]. International Journal of Remote Sensing,2009,30(17):4359-4385.
[13] VO A V,LAEFER D F,SMOLIC A,et al. Per-point processing for detailed urban solar estimation with aerial laser scanning and distributed computing[J]. ISPRS Journal of Photogrammetry and Remote Sensing,2019,155:119-135.
[14] 孙钰珊,张力,艾海滨,等. 倾斜影像匹配与三维建模关键技术发展综述[J]. 遥感信息,2018,33(2):1-8.
[15] 陈晓勇,何海清,周俊超,等. 低空摄影测量立体影像匹配的现状与展望[J]. 测绘学报,2019,48(12):1595-1603.
[16] 李百战,罗庆,姚润明. 城市地面对天空热辐射角系数问题的求解[J]. 重庆大学学报(自然科学版),2006,29(2):86-89.
[17] 吴杰,张宇峰,林宇. 基于参数化三维模型的城市天空遮挡简化算法[J]. 建筑科学,2017,33(6):32-40.
[18] CHENG Liang,XU Hao,LI Shuyi,et al. Retraction notice to use of LiDAR for calculating solar irradiance on roofs and façades of buildings at city scale:methodology,validation,and analysis[J]. 2018,138:12-29.
[19] EL MGHOUCHI Y,EL BOUARDI A,CHOULLI Z,et al. Models for obtaining the daily direct,diffuse and global solar radiations[J]. Renewable and Sustainable Energy Reviews,2016,56:87-99.
[20] 邱国全,夏艳君,杨鸿毅. 晴天太阳辐射模型的优化计算[J]. 太阳能学报,2001,22(4):456-460.
[21] NOORIAN A M,MORADI I,ALI KAMALI G. Evaluation of 12 models to estimate hourly diffuse irradiation on inclined surfaces[J]. Renewable Energy,2008,33(6):1406-1412.
[22] VERSO A,MARTIN A,AMADOR J,et al. GIS-based method to evaluate the photovoltaic potential in the urban environments:the particular case of Miraflores de la Sierra[J]. Solar Energy,2015,117:236-245.