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Assessment of solar...
Assessment of solar photovoltaic potentials on urban noise barriers using street-view imagery
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- Zhong, T. (author)
- Nanjing Normal University, Nanjing, China
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- Zhang, K. (author)
- Nanjing Normal University, Nanjing, China
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- Chen, M. (author)
- Nanjing Normal University, Nanjing, China
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- Wang, Y. (author)
- Nanjing Normal University, Nanjing, China
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- Zhu, R. (author)
- Senseable City Laboratory, Future Urban Mobility IRG, Singapore-MIT Alliance for Research and Technology, Singapore
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- Zhang, Z. (author)
- Nanjing Normal University, Nanjing, China
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- Zhou, Z. (author)
- Nanjing Normal University, Nanjing, China
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- Qian, Z. (author)
- Nanjing Normal University, Nanjing, China
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- Lv, G. (author)
- Nanjing Normal University, Nanjing, China
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- Yan, Jinyue, 1959- (author)
- Mälardalens högskola,Framtidens energi,KTH,Energiprocesser,School of Business, Society & Engineering, Mälardalen University, Västerås, 72123, Sweden
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(creator_code:org_t)
- Elsevier Ltd, 2021
- 2021
- English.
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In: Renewable energy. - : Elsevier Ltd. - 0960-1481 .- 1879-0682. ; 168, s. 181-194
- Related links:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- Solar energy captured by solar photovoltaic (PV) systems has great potential to meet the high demand for renewable energy sources in urban areas. A photovoltaic noise barrier (PVNB) system, which integrates a PV system with a noise barrier, is a promising source for harvesting solar energy to overcome the problem of having limited land available for solar panel installations. When estimating the solar PV potential at the city scale, it is difficult to identify sites for installing solar panels. A computational framework is proposed for estimating the solar PV potential of PVNB systems based on both existing and planned noise barrier sites. The proposed computational framework can identify suitable sites for installing photovoltaic panels. A deep learning-based method is used to detect existing noise barrier sites from massive street-view images. The planned noise barrier sites are identified with urban policies. Based on the existing and planned sites of noise barriers in Nanjing, the annual solar PV potentials in 2019 are 29,137 MW h and 113,052 MW h, respectively. The estimation results show that the potential PVNB systems based on the existing and planned noise barrier in 2019 have the potential installed capacity of 14.26 MW and 57.24 MW, with corresponding potential annual power generation of 4662 MW h and 18,088 MW h, respectively.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Maskinteknik -- Energiteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Mechanical Engineering -- Energy Engineering (hsv//eng)
Keyword
- Machine learning
- Object detection
- Photovoltaic noise barrier (PVNB)
- Solar radiation assessment
- Street-view images
- Acoustic noise measurement
- Deep learning
- Photovoltaic cells
- Solar cell arrays
- Solar power generation
- Urban growth
- Computational framework
- Estimation results
- Learning-based methods
- Photovoltaic panels
- Renewable energy source
- Solar photovoltaic system
- Solar photovoltaics
- Solar energy
Publication and Content Type
- ref (subject category)
- art (subject category)
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To the university's database
- By the author/editor
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Zhong, T.
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Zhang, K.
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Chen, M.
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Wang, Y.
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Zhu, R.
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Zhang, Z.
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Zhou, Z.
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Qian, Z.
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Lv, G.
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Yan, Jinyue, 195 ...
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- About the subject
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- ENGINEERING AND TECHNOLOGY
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ENGINEERING AND ...
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and Mechanical Engin ...
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and Energy Engineeri ...
- Articles in the publication
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Renewable energy
- By the university
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Mälardalen University
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Royal Institute of Technology