IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v369y2024ics0306261924009504.html
   My bibliography  Save this article

Unleashing the green potential: Assessing Hong Kong's building solar PV capacity

Author

Listed:
  • Liang, Hanwei
  • Shen, Jieling
  • Yip, Hin-Lap
  • Fang, Mandy Meng
  • Dong, Liang

Abstract

The global shift towards renewable energy highlights the significance of building photovoltaic (PV) systems as a sustainable solution. Assessing a building's solar PV potential is essential for advancing green energy initiatives. This study establishes an integrated system for analyzing both roofs and facades, incorporating physical, geographical, and technical dimensions. Utilizing the Perez model for solar irradiance, Hillshade analysis for shading effects, and Ladybug tools for facade obstruction simulation, we assess the PV potential and its spatial-temporal variations across 180,349 buildings in Hong Kong. The results show that Hong Kong's roofs and facades have a physical potential of 4.00 × 1013 Wh and 2.48 × 1014 Wh, respectively. The feasible installation areas are identified as 14.44 km2 for roofs and 71.31 km2 for façades, yielding geographical potentials of 1.48 × 1013 Wh and 3.44 × 1013 Wh. Based on this, the estimated installed capacities are 1.27 GW for roofs and 12.75 GW for facades, which could generate between 2.07 × 1012–2.66 × 1012 Wh and 3.61 × 1012–4.65 × 1012 Wh, respectively. These projections account for 12.68%–16.32% of Hong Kong's total electricity consumption in 2022. This study underlines the substantial role of building-integrated solar PV systems in Hong Kong's transition towards a low-carbon future, offering valuable insights for policymaking and implementation strategies.

Suggested Citation

  • Liang, Hanwei & Shen, Jieling & Yip, Hin-Lap & Fang, Mandy Meng & Dong, Liang, 2024. "Unleashing the green potential: Assessing Hong Kong's building solar PV capacity," Applied Energy, Elsevier, vol. 369(C).
    • Handle: RePEc:eee:appene:v:369:y:2024:i:c:s0306261924009504
    DOI: 10.1016/j.apenergy.2024.123567
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924009504
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2024.123567?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Brown, Marilyn A., 2001. "Market failures and barriers as a basis for clean energy policies," Energy Policy, Elsevier, vol. 29(14), pages 1197-1207, November.
    2. Freitas, S. & Catita, C. & Redweik, P. & Brito, M.C., 2015. "Modelling solar potential in the urban environment: State-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 915-931.
    3. Siddharth Joshi & Shivika Mittal & Paul Holloway & Priyadarshi Ramprasad Shukla & Brian Ó Gallachóir & James Glynn, 2021. "High resolution global spatiotemporal assessment of rooftop solar photovoltaics potential for renewable electricity generation," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    4. Camilo Mora & Daniele Spirandelli & Erik C. Franklin & John Lynham & Michael B. Kantar & Wendy Miles & Charlotte Z. Smith & Kelle Freel & Jade Moy & Leo V. Louis & Evan W. Barba & Keith Bettinger & Ab, 2018. "Broad threat to humanity from cumulative climate hazards intensified by greenhouse gas emissions," Nature Climate Change, Nature, vol. 8(12), pages 1062-1071, December.
    5. Lin Dong & Jiazi Li & Yingjun Xu & Youtian Yang & Xuemin Li & Hua Zhang, 2021. "Study on the Spatial Classification of Construction Land Types in Chinese Cities: A Case Study in Zhejiang Province," Land, MDPI, vol. 10(5), pages 1-14, May.
    6. Brito, M.C. & Freitas, S. & Guimarães, S. & Catita, C. & Redweik, P., 2017. "The importance of facades for the solar PV potential of a Mediterranean city using LiDAR data," Renewable Energy, Elsevier, vol. 111(C), pages 85-94.
    7. Mohajeri, Nahid & Assouline, Dan & Guiboud, Berenice & Bill, Andreas & Gudmundsson, Agust & Scartezzini, Jean-Louis, 2018. "A city-scale roof shape classification using machine learning for solar energy applications," Renewable Energy, Elsevier, vol. 121(C), pages 81-93.
    8. Lin, Yu-Hao & Tsai, Kang-Ting & Lin, Min-Der & Yang, Ming-Der, 2016. "Design optimization of office building envelope configurations for energy conservation," Applied Energy, Elsevier, vol. 171(C), pages 336-346.
    9. Zhang, Yuhu & Ren, Jing & Pu, Yanru & Wang, Peng, 2020. "Solar energy potential assessment: A framework to integrate geographic, technological, and economic indices for a potential analysis," Renewable Energy, Elsevier, vol. 149(C), pages 577-586.
    10. Sidek, M.H.M. & Azis, N. & Hasan, W.Z.W. & Ab Kadir, M.Z.A. & Shafie, S. & Radzi, M.A.M., 2017. "Automated positioning dual-axis solar tracking system with precision elevation and azimuth angle control," Energy, Elsevier, vol. 124(C), pages 160-170.
    11. Yang, Qing & Huang, Tianyue & Wang, Saige & Li, Jiashuo & Dai, Shaoqing & Wright, Sebastian & Wang, Yuxuan & Peng, Huaiwu, 2019. "A GIS-based high spatial resolution assessment of large-scale PV generation potential in China," Applied Energy, Elsevier, vol. 247(C), pages 254-269.
    12. Steven Chu & Arun Majumdar, 2012. "Opportunities and challenges for a sustainable energy future," Nature, Nature, vol. 488(7411), pages 294-303, August.
    13. Colak, H. Ebru & Memisoglu, Tugba & Gercek, Yasin, 2020. "Optimal site selection for solar photovoltaic (PV) power plants using GIS and AHP: A case study of Malatya Province, Turkey," Renewable Energy, Elsevier, vol. 149(C), pages 565-576.
    14. Shubbak, Mahmood H., 2019. "Advances in solar photovoltaics: Technology review and patent trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    15. Hofierka, Jaroslav & Kaňuk, Ján, 2009. "Assessment of photovoltaic potential in urban areas using open-source solar radiation tools," Renewable Energy, Elsevier, vol. 34(10), pages 2206-2214.
    16. Peng, Jinqing & Lu, Lin, 2013. "Investigation on the development potential of rooftop PV system in Hong Kong and its environmental benefits," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 149-162.
    17. Lukač, Niko & Seme, Sebastijan & Žlaus, Danijel & Štumberger, Gorazd & Žalik, Borut, 2014. "Buildings roofs photovoltaic potential assessment based on LiDAR (Light Detection And Ranging) data," Energy, Elsevier, vol. 66(C), pages 598-609.
    18. Assouline, Dan & Mohajeri, Nahid & Scartezzini, Jean-Louis, 2018. "Large-scale rooftop solar photovoltaic technical potential estimation using Random Forests," Applied Energy, Elsevier, vol. 217(C), pages 189-211.
    19. Ko, Li & Wang, Jen-Chun & Chen, Chia-Yon & Tsai, Hsing-Yeh, 2015. "Evaluation of the development potential of rooftop solar photovoltaic in Taiwan," Renewable Energy, Elsevier, vol. 76(C), pages 582-595.
    20. Hong, Taehoon & Lee, Minhyun & Koo, Choongwan & Jeong, Kwangbok & Kim, Jimin, 2017. "Development of a method for estimating the rooftop solar photovoltaic (PV) potential by analyzing the available rooftop area using Hillshade analysis," Applied Energy, Elsevier, vol. 194(C), pages 320-332.
    21. Sredenšek, Klemen & Štumberger, Bojan & Hadžiselimović, Miralem & Mavsar, Primož & Seme, Sebastijan, 2022. "Physical, geographical, technical, and economic potential for the optimal configuration of photovoltaic systems using a digital surface model and optimization method," Energy, Elsevier, vol. 242(C).
    22. Shahsavari, Amir & Akbari, Morteza, 2018. "Potential of solar energy in developing countries for reducing energy-related emissions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 275-291.
    23. Elkadeem, Mohamed R. & Younes, Ali & Mazzeo, Domenico & Jurasz, Jakub & Elia Campana, Pietro & Sharshir, Swellam W. & Alaam, Mohamed A., 2022. "Geospatial-assisted multi-criterion analysis of solar and wind power geographical-technical-economic potential assessment," Applied Energy, Elsevier, vol. 322(C).
    24. Kaygusuz, K., 2011. "Energy services and energy poverty for sustainable rural development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(2), pages 936-947, February.
    25. Erkan Aydin & Esma Ugur & Bumin K. Yildirim & Thomas G. Allen & Pia Dally & Arsalan Razzaq & Fangfang Cao & Lujia Xu & Badri Vishal & Aren Yazmaciyan & Ahmed A. Said & Shynggys Zhumagali & Randi Azmi , 2023. "Enhanced optoelectronic coupling for perovskite/silicon tandem solar cells," Nature, Nature, vol. 623(7988), pages 732-738, November.
    26. Gassar, Abdo Abdullah Ahmed & Cha, Seung Hyun, 2021. "Review of geographic information systems-based rooftop solar photovoltaic potential estimation approaches at urban scales," Applied Energy, Elsevier, vol. 291(C).
    27. Cheng, Liang & Zhang, Fangli & Li, Shuyi & Mao, Junya & Xu, Hao & Ju, Weimin & Liu, Xiaoqiang & Wu, Jie & Min, Kaifu & Zhang, Xuedong & Li, Manchun, 2020. "Solar energy potential of urban buildings in 10 cities of China," Energy, Elsevier, vol. 196(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gassar, Abdo Abdullah Ahmed & Cha, Seung Hyun, 2021. "Review of geographic information systems-based rooftop solar photovoltaic potential estimation approaches at urban scales," Applied Energy, Elsevier, vol. 291(C).
    2. Zhong, Teng & Zhang, Zhixin & Chen, Min & Zhang, Kai & Zhou, Zixuan & Zhu, Rui & Wang, Yijie & Lü, Guonian & Yan, Jinyue, 2021. "A city-scale estimation of rooftop solar photovoltaic potential based on deep learning," Applied Energy, Elsevier, vol. 298(C).
    3. Liu, Jiang & Wu, Qifeng & Lin, Zhipeng & Shi, Huijie & Wen, Shaoyang & Wu, Qiaoyu & Zhang, Junxue & Peng, Changhai, 2023. "A novel approach for assessing rooftop-and-facade solar photovoltaic potential in rural areas using three-dimensional (3D) building models constructed with GIS," Energy, Elsevier, vol. 282(C).
    4. Sredenšek, Klemen & Štumberger, Bojan & Hadžiselimović, Miralem & Mavsar, Primož & Seme, Sebastijan, 2022. "Physical, geographical, technical, and economic potential for the optimal configuration of photovoltaic systems using a digital surface model and optimization method," Energy, Elsevier, vol. 242(C).
    5. Chen, Zhe & Yang, Bisheng & Zhu, Rui & Dong, Zhen, 2024. "City-scale solar PV potential estimation on 3D buildings using multi-source RS data: A case study in Wuhan, China," Applied Energy, Elsevier, vol. 359(C).
    6. Liao, Xuan & Zhu, Rui & Wong, Man Sing & Heo, Joon & Chan, P.W. & Kwok, Coco Yin Tung, 2023. "Fast and accurate estimation of solar irradiation on building rooftops in Hong Kong: A machine learning-based parameterization approach," Renewable Energy, Elsevier, vol. 216(C).
    7. Sun, Tao & Shan, Ming & Rong, Xing & Yang, Xudong, 2022. "Estimating the spatial distribution of solar photovoltaic power generation potential on different types of rural rooftops using a deep learning network applied to satellite images," Applied Energy, Elsevier, vol. 315(C).
    8. Sebastian Krapf & Nils Kemmerzell & Syed Khawaja Haseeb Uddin & Manuel Hack Vázquez & Fabian Netzler & Markus Lienkamp, 2021. "Towards Scalable Economic Photovoltaic Potential Analysis Using Aerial Images and Deep Learning," Energies, MDPI, vol. 14(13), pages 1-22, June.
    9. Elham Fakhraian & Marc Alier & Francesc Valls Dalmau & Alireza Nameni & Maria José Casañ Guerrero, 2021. "The Urban Rooftop Photovoltaic Potential Determination," Sustainability, MDPI, vol. 13(13), pages 1-18, July.
    10. Lee, Minhyun & Hong, Taehoon & Jeong, Kwangbok & Kim, Jimin, 2018. "A bottom-up approach for estimating the economic potential of the rooftop solar photovoltaic system considering the spatial and temporal diversity," Applied Energy, Elsevier, vol. 232(C), pages 640-656.
    11. Hong, Taehoon & Lee, Minhyun & Koo, Choongwan & Jeong, Kwangbok & Kim, Jimin, 2017. "Development of a method for estimating the rooftop solar photovoltaic (PV) potential by analyzing the available rooftop area using Hillshade analysis," Applied Energy, Elsevier, vol. 194(C), pages 320-332.
    12. Job Taminiau & John Byrne & Jongkyu Kim & Min‐Hwi Kim & Jeongseok Seo, 2022. "Inferential‐ and measurement‐based methods to estimate rooftop “solar city” potential in megacity Seoul, South Korea," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 11(5), September.
    13. Primož Mavsar & Klemen Sredenšek & Bojan Štumberger & Miralem Hadžiselimović & Sebastijan Seme, 2019. "Simplified Method for Analyzing the Availability of Rooftop Photovoltaic Potential," Energies, MDPI, vol. 12(22), pages 1-17, November.
    14. Diana Bernasconi & Giorgio Guariso, 2021. "Rooftop PV: Potential and Impacts in a Complex Territory," Energies, MDPI, vol. 14(12), pages 1-17, June.
    15. Lukač, Niko & Mongus, Domen & Žalik, Borut & Štumberger, Gorazd & Bizjak, Marko, 2024. "Novel GPU-accelerated high-resolution solar potential estimation in urban areas by using a modified diffuse irradiance model," Applied Energy, Elsevier, vol. 353(PA).
    16. Aslani, Mohammad & Seipel, Stefan, 2022. "Automatic identification of utilizable rooftop areas in digital surface models for photovoltaics potential assessment," Applied Energy, Elsevier, vol. 306(PA).
    17. Carlos Beltran-Velamazan & Marta Monzón-Chavarrías & Belinda López-Mesa, 2021. "A Method for the Automated Construction of 3D Models of Cities and Neighborhoods from Official Cadaster Data for Solar Analysis," Sustainability, MDPI, vol. 13(11), pages 1-19, May.
    18. Assouline, Dan & Mohajeri, Nahid & Scartezzini, Jean-Louis, 2018. "Large-scale rooftop solar photovoltaic technical potential estimation using Random Forests," Applied Energy, Elsevier, vol. 217(C), pages 189-211.
    19. Thai, Clinton & Brouwer, Jack, 2021. "Challenges estimating distributed solar potential with utilization factors: California universities case study," Applied Energy, Elsevier, vol. 282(PB).
    20. Bódis, Katalin & Kougias, Ioannis & Jäger-Waldau, Arnulf & Taylor, Nigel & Szabó, Sándor, 2019. "A high-resolution geospatial assessment of the rooftop solar photovoltaic potential in the European Union," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:369:y:2024:i:c:s0306261924009504. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.