IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i24p8364-d700441.html
   My bibliography  Save this article

Comparing 2D and 3D Solar Radiation Modeling in Urban Areas

Author

Listed:
  • Štefan Kolečanský

    (Institute of Geography, Faculty of Science, Pavol Jozef Šafárik University in Košice, Šrobárova 2, 04154 Košice, Slovakia)

  • Jaroslav Hofierka

    (Institute of Geography, Faculty of Science, Pavol Jozef Šafárik University in Košice, Šrobárova 2, 04154 Košice, Slovakia)

  • Jozef Bogľarský

    (Institute of Geography, Faculty of Science, Pavol Jozef Šafárik University in Košice, Šrobárova 2, 04154 Košice, Slovakia)

  • Jozef Šupinský

    (Institute of Geography, Faculty of Science, Pavol Jozef Šafárik University in Košice, Šrobárova 2, 04154 Košice, Slovakia)

Abstract

The use of solar radiation in the urban environment is becoming increasingly important for the sustainable development of cities and human societies. Several factors influence the distribution of solar radiation in urban areas, including urban morphology and the physical properties of urban materials. Most of these factors can be modeled with a relatively high accuracy using 2D and 3D solar radiation models. In this paper, the r.sun and v.sun solar radiation models are used to calculate solar radiation for the city of Košice in Eastern Slovakia to assess the accuracy of both approaches for vertical surfaces frequently found in urban areas. The results were validated by pyranometer measurements. The results showed relatively good estimates by the 3D v.sun model and poor estimates by the 2D r.sun model. This can be attributed to an improper representation of vertical surfaces by a digital surface model, which has a strong impact on solar resource assessments. We found that 3D city models prepared in level of detail 2 (LoD2) are not always adequate in case of complex buildings with morphological structures, such as terraces. These cast shadows on facades especially when solar altitude is high and, thus, assessments, even by a 3D model, are inaccurate.

Suggested Citation

  • Štefan Kolečanský & Jaroslav Hofierka & Jozef Bogľarský & Jozef Šupinský, 2021. "Comparing 2D and 3D Solar Radiation Modeling in Urban Areas," Energies, MDPI, vol. 14(24), pages 1-15, December.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:24:p:8364-:d:700441
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/24/8364/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/24/8364/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Mingxing Chen & Hua Zhang & Weidong Liu & Wenzhong Zhang, 2014. "The Global Pattern of Urbanization and Economic Growth: Evidence from the Last Three Decades," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-15, August.
    4. 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)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Filip Pružinec & Renata Ďuračiová, 2022. "A Point-Cloud Solar Radiation Tool," Energies, MDPI, vol. 15(19), pages 1-15, September.

    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. Finn, Thomas & McKenzie, Paul, 2020. "A high-resolution suitability index for solar farm location in complex landscapes," Renewable Energy, Elsevier, vol. 158(C), pages 520-533.
    2. 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.
    3. 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.
    4. Thai, Clinton & Brouwer, Jack, 2021. "Challenges estimating distributed solar potential with utilization factors: California universities case study," Applied Energy, Elsevier, vol. 282(PB).
    5. Sarmiento, Nilsa & Belmonte, Silvina & Dellicompagni, Pablo & Franco, Judith & Escalante, Karina & Sarmiento, Joaquín, 2019. "A solar irradiation GIS as decision support tool for the Province of Salta, Argentina," Renewable Energy, Elsevier, vol. 132(C), pages 68-80.
    6. 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.
    7. 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).
    8. Kurdi, Yumna & Alkhatatbeh, Baraa J. & Asadi, Somayeh & Jebelli, Houtan, 2022. "A decision-making design framework for the integration of PV systems in the urban energy planning process," Renewable Energy, Elsevier, vol. 197(C), pages 288-304.
    9. Filip Pružinec & Renata Ďuračiová, 2022. "A Point-Cloud Solar Radiation Tool," Energies, MDPI, vol. 15(19), pages 1-15, September.
    10. Oh, Myeongchan & Park, Hyeong-Dong, 2018. "A new algorithm using a pyramid dataset for calculating shadowing in solar potential mapping," Renewable Energy, Elsevier, vol. 126(C), pages 465-474.
    11. Vrînceanu, Alexandra & Dumitrașcu, Monica & Kucsicsa, Gheorghe, 2022. "Site suitability for photovoltaic farms and current investment in Romania," Renewable Energy, Elsevier, vol. 187(C), pages 320-330.
    12. Formolli, M. & Kleiven, T. & Lobaccaro, G., 2023. "Assessing solar energy accessibility at high latitudes: A systematic review of urban spatial domains, metrics, and parameters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 177(C).
    13. Zhong, Qing & Tong, Daoqin, 2020. "Spatial layout optimization for solar photovoltaic (PV) panel installation," Renewable Energy, Elsevier, vol. 150(C), pages 1-11.
    14. Zhixin Zhang & Min Chen & Teng Zhong & Rui Zhu & Zhen Qian & Fan Zhang & Yue Yang & Kai Zhang & Paolo Santi & Kaicun Wang & Yingxia Pu & Lixin Tian & Guonian Lü & Jinyue Yan, 2023. "Carbon mitigation potential afforded by rooftop photovoltaic in China," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    15. Zhen Yang & Jun Lei & Jian-Gang Li, 2019. "Identifying the Determinants of Urbanization in Prefecture-Level Cities in China: A Quantitative Analysis Based on Spatial Production Theory," Sustainability, MDPI, vol. 11(4), pages 1-18, February.
    16. Zhao, Qin & Zhang, Houcheng & Hu, Ziyang & Hou, Shujin, 2021. "Performance evaluation of a new hybrid system consisting of a photovoltaic module and an absorption heat transformer for electricity production and heat upgrading," Energy, Elsevier, vol. 216(C).
    17. George Kyriakarakos & Athanasios T. Balafoutis & Dionysis Bochtis, 2020. "Proposing a Paradigm Shift in Rural Electrification Investments in Sub-Saharan Africa through Agriculture," Sustainability, MDPI, vol. 12(8), pages 1-19, April.
    18. Jamil, Basharat & Akhtar, Naiem, 2017. "Comparison of empirical models to estimate monthly mean diffuse solar radiation from measured data: Case study for humid-subtropical climatic region of India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1326-1342.
    19. Fuster-Palop, Enrique & Prades-Gil, Carlos & Masip, X. & Viana-Fons, Joan D. & Payá, Jorge, 2021. "Innovative regression-based methodology to assess the techno-economic performance of photovoltaic installations in urban areas," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    20. Hussain, C.M. Iftekhar & Norton, Brian & Duffy, Aidan, 2017. "Technological assessment of different solar-biomass systems for hybrid power generation in Europe," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P2), pages 1115-1129.

    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:14:y:2021:i:24:p:8364-:d:700441. 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.