An Approach for Estimating Solar Photovoltaic Potential Based on Rooftop Retrieval from Remote Sensing Images

Xiaoyang Song, Yaohuan Huang, Chuanpeng Zhao, Yuxin Liu, Yanguo Lu, Yongguo Chang and Jie Yang
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Xiaoyang Song: Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
Yaohuan Huang: Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Chuanpeng Zhao: Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Yuxin Liu: Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
Yanguo Lu: Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
Yongguo Chang: Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
Jie Yang: Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China

Energies, 2018, vol. 11, issue 11, 1-14

Abstract: Solar energy is the most clean renewable energy source and has good prospects for future sustainable development. Installation of solar photovoltaic (PV) systems on building rooftops has been the most widely applied method for using solar energy resources. In this study, we developed an approach to simulate the monthly and annual solar radiation on rooftops at an hourly time step to estimate the solar PV potential, based on rooftop feature retrieval from remote sensing images. The rooftop features included 2D rooftop outlines and 3D rooftop parameters retrieved from high-resolution remote sensing image data (obtained from Google Maps) and digital surface model (DSM, generated from the Pleiades satellite), respectively. We developed the building features calculation method for five rooftop types: flat rooftops, shed rooftops, hipped rooftops, gable rooftops and mansard rooftops. The parameters of the PV modules derived from the building features were then combined with solar radiation data to evaluate solar photovoltaic potential. The proposed method was applied in the Chao Yang District of Beijing, China. The results were that the number of rooftops available for PV systems was 743, the available rooftop area was 678,805 m 2 , and the annual PV electricity potential was 63.78 GWh/year in the study area, which has great solar PV potential. The method to perform precise calculation of specific rooftop solar PV potential developed in this study will guide the formulation of energy policy for solar PV in the future.

Keywords: solar resources; digital surface models (DSM); rooftop feature; rooftop photovoltaic; solar photovoltaic potential; energy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

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