A simplified evaluation method of rooftop solar energy potential based on image semantic segmentation of urban streetscapes. (December 2021)

• Record Type: Journal Article
• Authors: Lan, Haifeng; Gou, Zhonghua; Xie, Xiaohuan
• Is Part Of: Solar energy. Volume 230(2021)
• Page Start: 912
• Page End: 924
• Publication Date: 2021-12
• Subjects: Solar energy potential -- Sky view factor -- Sun coverage factor -- Image semantic segmentation -- Simplified method; Solar energy -- Periodicals; Solar engines -- Periodicals; 621.47
• DOI: 10.1016/j.solener.2021.10.085
• Languages: English
• ISSNs: 0038-092X

Abstract

Highlights: A simplified model based on two indicators: sky view factor and sun coverage factor. A model between the two indicators with simulated solar energy yield was established. A validation study showed that the average relative error of the model was 6.6%. The model reduced the computation time while preserving accuracy. Abstract: The evaluation of rooftop solar energy potential in cities has a fundamental role in the development and utilization of solar energy. The irradiance-based approach of evaluation is a repetitive calculation process combined with the complex geometry of urban forms. This research paper proposes a framework that utilizes urban streetscapes to quickly estimate the urban solar energy potential using a simplified solar energy yield model based on two indicators: sky view factor (SVF) and sun coverage factor (SCF). First, 327 Google Street View images were converted into fisheye images, which were semantically segmented based on the deep-learning Full Convolutional Network (FCN). Then, the SVF and SCF were calculated based on the method of pixel statistics. Finally, a model with the simulated solar energy yield was established. Furthermore, a validation study was conducted using rooftop solar production data, which showed that the maximum estimation error of the proposed model was less than 8% and the average relative error was 6.6%. Generally, the proposed model reduced the required computation time while preserving a satisfactory degree of accuracy.