IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i5p1025-d1343716.html
   My bibliography  Save this article

An Estimation of the Available Spatial Intensity of Solar Energy in Urban Blocks in Wuhan, China

Author

Listed:
  • Hui Zhang

    (School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China
    Key Laboratory of Health Intelligent Perception and Ecological Restoration of River and Lake, Ministry of Education, Hubei University of Technology, Wuhan 430068, China
    ChinTiyan New Energy (Hubei) Co., Ltd., Wuhan 430223, China)

  • Xiaoxi Huang

    (School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China
    Key Laboratory of Health Intelligent Perception and Ecological Restoration of River and Lake, Ministry of Education, Hubei University of Technology, Wuhan 430068, China)

  • Zhengwei Wang

    (School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China
    Key Laboratory of Health Intelligent Perception and Ecological Restoration of River and Lake, Ministry of Education, Hubei University of Technology, Wuhan 430068, China)

  • Shiyu Jin

    (School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China)

  • Benlin Xiao

    (School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China)

  • Yanyan Huang

    (School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China
    Key Laboratory of Health Intelligent Perception and Ecological Restoration of River and Lake, Ministry of Education, Hubei University of Technology, Wuhan 430068, China)

  • Wei Zhong

    (ChinTiyan New Energy (Hubei) Co., Ltd., Wuhan 430223, China)

  • Aofei Meng

    (ChinTiyan New Energy (Hubei) Co., Ltd., Wuhan 430223, China)

Abstract

Urban form is an important factor affecting urban energy. However, the design of urban form and energy mostly belong to two separate disciplines and fields, and urban energy planning research rarely considers their mutual relationship. The available space intensity (ASI) of solar energy is formed on the basis of energy planning and urban design; the objective of this research is to evaluate the impact of urban form on the ASI of solar energy and to propose strategies for planning of the space that is available for solar energy so as to improve the efficiency of urban energy utilization and achieve sustainable urban development. Methodologically, this study firstly proposes a model to quantify the ASI of solar energy using three indicators: solar radiation intensity (SRI), solar installation intensity (SII), and solar generation intensity (SEGI). Then, we quantitatively calculate the solar ASI of nine types of typical urban blocks in a sub-center of Wuhan City, Nanhu. Correlation analysis and multiple linear regression analysis are then used to analyze the correlation between the form indicators and solar ASI, as well as the degree of influence. The results show that the differences in SRI, SII, and SEGI amongst the nine types of city blocks were as high as 114.61%, 162.50%, and 61.01%. The solar ASI was mainly affected by three form indicators: the building coverage ratio, the average building height, and the volume-to-area ratio. Reducing the building coverage ratio and increasing vertical development at the same time can effectively improve the ASI of solar energy. The results of this study and the established method provide an important reference and rapid calculation tool for urban energy planning and design, reducing the data and time usually required for solar analysis at the block scale.

Suggested Citation

  • Hui Zhang & Xiaoxi Huang & Zhengwei Wang & Shiyu Jin & Benlin Xiao & Yanyan Huang & Wei Zhong & Aofei Meng, 2024. "An Estimation of the Available Spatial Intensity of Solar Energy in Urban Blocks in Wuhan, China," Energies, MDPI, vol. 17(5), pages 1-26, February.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:5:p:1025-:d:1343716
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/5/1025/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/5/1025/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sun, Liangliang & Lu, Lin & Yang, Hongxing, 2012. "Optimum design of shading-type building-integrated photovoltaic claddings with different surface azimuth angles," Applied Energy, Elsevier, vol. 90(1), pages 233-240.
    2. Joeri Rogelj & Michel den Elzen & Niklas Höhne & Taryn Fransen & Hanna Fekete & Harald Winkler & Roberto Schaeffer & Fu Sha & Keywan Riahi & Malte Meinshausen, 2016. "Paris Agreement climate proposals need a boost to keep warming well below 2 °C," Nature, Nature, vol. 534(7609), pages 631-639, June.
    3. Saber, Esmail M. & Lee, Siew Eang & Manthapuri, Sumanth & Yi, Wang & Deb, Chirag, 2014. "PV (photovoltaics) performance evaluation and simulation-based energy yield prediction for tropical buildings," Energy, Elsevier, vol. 71(C), pages 588-595.
    4. Strzalka, Aneta & Alam, Nazmul & Duminil, Eric & Coors, Volker & Eicker, Ursula, 2012. "Large scale integration of photovoltaics in cities," Applied Energy, Elsevier, vol. 93(C), pages 413-421.
    5. Buffat, René & Grassi, Stefano & Raubal, Martin, 2018. "A scalable method for estimating rooftop solar irradiation potential over large regions," Applied Energy, Elsevier, vol. 216(C), pages 389-401.
    6. Guo, Xiaopeng & Dong, Yining & Ren, Dongfang, 2023. "CO2 emission reduction effect of photovoltaic industry through 2060 in China," Energy, Elsevier, vol. 269(C).
    7. Zhong, Qing & Nelson, Jake R. & Tong, Daoqin & Grubesic, Tony H., 2022. "A spatial optimization approach to increase the accuracy of rooftop solar energy assessments," Applied Energy, Elsevier, vol. 316(C).
    8. 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.
    9. 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).
    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. 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).
    2. 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).
    3. 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.
    4. 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).
    5. Gomez-Exposito, Antonio & Arcos-Vargas, Angel & Gutierrez-Garcia, Francisco, 2020. "On the potential contribution of rooftop PV to a sustainable electricity mix: The case of Spain," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    6. Walch, Alina & Castello, Roberto & Mohajeri, Nahid & Scartezzini, Jean-Louis, 2020. "Big data mining for the estimation of hourly rooftop photovoltaic potential and its uncertainty," Applied Energy, Elsevier, vol. 262(C).
    7. Taveres-Cachat, Ellika & Lobaccaro, Gabriele & Goia, Francesco & Chaudhary, Gaurav, 2019. "A methodology to improve the performance of PV integrated shading devices using multi-objective optimization," Applied Energy, Elsevier, vol. 247(C), pages 731-744.
    8. Özdemir, Samed & Yavuzdoğan, Ahmet & Bilgilioğlu, Burhan Baha & Akbulut, Zeynep, 2023. "SPAN: An open-source plugin for photovoltaic potential estimation of individual roof segments using point cloud data," Renewable Energy, Elsevier, vol. 216(C).
    9. Tripathy, M. & Yadav, S. & Sadhu, P.K. & Panda, S.K., 2017. "Determination of optimum tilt angle and accurate insolation of BIPV panel influenced by adverse effect of shadow," Renewable Energy, Elsevier, vol. 104(C), pages 211-223.
    10. 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.
    11. Yang, Ying & Campana, Pietro Elia & Stridh, Bengt & Yan, Jinyue, 2020. "Potential analysis of roof-mounted solar photovoltaics in Sweden," Applied Energy, Elsevier, vol. 279(C).
    12. 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.
    13. Ren, Haoshan & Xu, Chengliang & Ma, Zhenjun & Sun, Yongjun, 2022. "A novel 3D-geographic information system and deep learning integrated approach for high-accuracy building rooftop solar energy potential characterization of high-density cities," Applied Energy, Elsevier, vol. 306(PA).
    14. Jiang, Hou & Zhang, Xiaotong & Yao, Ling & Lu, Ning & Qin, Jun & Liu, Tang & Zhou, Chenghu, 2023. "High-resolution analysis of rooftop photovoltaic potential based on hourly generation simulations and load profiles," Applied Energy, Elsevier, vol. 348(C).
    15. 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).
    16. 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.
    17. Enrique Fuster-Palop & Carlos Prades-Gil & Ximo Masip & J. D. Viana-Fons & Jorge Payá, 2023. "Techno-Economic Potential of Urban Photovoltaics: Comparison of Net Billing and Net Metering in a Mediterranean Municipality," Energies, MDPI, vol. 16(8), pages 1-32, April.
    18. Suntiti Yoomak & Theerasak Patcharoen & Atthapol Ngaopitakkul, 2019. "Performance and Economic Evaluation of Solar Rooftop Systems in Different Regions of Thailand," Sustainability, MDPI, vol. 11(23), pages 1-20, November.
    19. Gupta, Rahul & Sossan, Fabrizio & Paolone, Mario, 2021. "Countrywide PV hosting capacity and energy storage requirements for distribution networks: The case of Switzerland," Applied Energy, Elsevier, vol. 281(C).
    20. Li, Yue & Luo, Hao & Cai, Hua, 2023. "Photovoltaic-battery powered bike share stations are not necessarily energy self-sufficient," Applied Energy, Elsevier, vol. 348(C).

    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:gam:jeners:v:17:y:2024:i:5:p:1025-:d:1343716. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.