IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i19p7018-d923969.html
   My bibliography  Save this article

A Point-Cloud Solar Radiation Tool

Author

Listed:
  • Filip Pružinec

    (Department of Theoretical Geodesy and Geoinformatics, Faculty of Civil Engineering, Slovak University of Technology in Bratislava, 810 05 Bratislava, Slovakia)

  • Renata Ďuračiová

    (Department of Theoretical Geodesy and Geoinformatics, Faculty of Civil Engineering, Slovak University of Technology in Bratislava, 810 05 Bratislava, Slovakia)

Abstract

Current software solutions for solar-radiation modeling in 3D focus on the urban environment. Most of the published tools do not implement methods to consider complex objects, such as urban greenery in their models or they expect a rather complex 3D mesh to represent such objects. Their use in an environment that is difficult to represent geometrically, such as vegetation-covered areas, is rather limited. In this paper, we present a newly developed solar-radiation tool focused on solar-radiation modeling in areas with complex objects, such as vegetation. The tool uses voxel representations of space based on point-cloud data to calculate the illumination and ESRA solar-radiation model to estimate the direct, diffuse, and global irradiation in a specified time range. We demonstrate the capabilities of this tool on a forested mountain area of Suchá valley in the Hight Tatra mountains (Slovakia) and also in the urban environment of Castle Hill in Bratislava (Slovakia) with urban greenery. We compare the tool with the r.sun module of GRASS GIS and the Area Solar Radiation tool of ArcGIS using point-cloud data generated from the digital-terrain model of Kamenistá valley in High Tatra mountains in Slovakia. The results suggest a higher detail of the model in rugged terrain and comparable results on smooth surfaces when considering its purpose as a 3D modeling tool. The performance is tested using different hardware and input data. The processing times are less than 8 min, and 8 GB of memory is used with 4 to 16 core processors and point clouds larger than 100,000 points. The tool is, therefore, easily usable on common computers.

Suggested Citation

  • Filip Pružinec & Renata Ďuračiová, 2022. "A Point-Cloud Solar Radiation Tool," Energies, MDPI, vol. 15(19), pages 1-15, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:19:p:7018-:d:923969
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/19/7018/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/19/7018/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Garg, H.P. & Datta, Gouri, 1993. "Fundamentals and characteristics of solar radiation," Renewable Energy, Elsevier, vol. 3(4), pages 305-319.
    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)

    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. 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.
    2. 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.
    3. 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).
    4. Zhong, Qing & Tong, Daoqin, 2020. "Spatial layout optimization for solar photovoltaic (PV) panel installation," Renewable Energy, Elsevier, vol. 150(C), pages 1-11.
    5. 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).
    6. 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.
    7. Panagiotis G. Kosmopoulos & Marios T. Mechilis & Panagiota Kaoura, 2022. "Solar Energy Production Planning in Antikythera: Adequacy Scenarios and the Effect of the Atmospheric Parameters," Energies, MDPI, vol. 15(24), pages 1-19, December.
    8. Tian, Shuai & Yang, Guoqiang & Du, Sihong & Zhuang, Dian & Zhu, Ke & Zhou, Xin & Jin, Xing & Ye, Yu & Li, Peixian & Shi, Xing, 2024. "An innovative method for evaluating the urban roof photovoltaic potential based on open-source satellite images," Renewable Energy, Elsevier, vol. 224(C).
    9. Tomáš Hubinský & Roman Hajtmanek & Andrea Šeligová & Ján Legény & Robert Špaček, 2023. "Potentials and Limits of Photovoltaic Systems Integration in Historic Urban Structures: The Case Study of Monument Reserve in Bratislava, Slovakia," Sustainability, MDPI, vol. 15(3), pages 1-27, January.
    10. D’Adamo, Idiano & Falcone, Pasquale Marcello & Gastaldi, Massimo & Morone, Piergiuseppe, 2020. "The economic viability of photovoltaic systems in public buildings: Evidence from Italy," Energy, Elsevier, vol. 207(C).
    11. Hwangbo, Soonho & Heo, SungKu & Yoo, ChangKyoo, 2022. "Development of deterministic-stochastic model to integrate variable renewable energy-driven electricity and large-scale utility networks: Towards decarbonization petrochemical industry," Energy, Elsevier, vol. 238(PC).
    12. 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.
    13. Aleksandra Besser & Jan K. Kazak & Małgorzata Świąder & Szymon Szewrański, 2019. "A Customized Decision Support System for Renewable Energy Application by Housing Association," Sustainability, MDPI, vol. 11(16), pages 1-16, August.
    14. Bocca, Alberto & Chiavazzo, Eliodoro & Macii, Alberto & Asinari, Pietro, 2015. "Solar energy potential assessment: An overview and a fast modeling approach with application to Italy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 291-296.
    15. Vardimon, Ran, 2011. "Assessment of the potential for distributed photovoltaic electricity production in Israel," Renewable Energy, Elsevier, vol. 36(2), pages 591-594.
    16. Abbes, Dhaker & Martinez, André & Champenois, Gérard, 2014. "Life cycle cost, embodied energy and loss of power supply probability for the optimal design of hybrid power systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 98(C), pages 46-62.
    17. Rehman, Naveed ur & Katebi, Milad & Shaikh, Faraz & Al Karim, Miftah, 2020. "Solar resource assessment of modern parking machines in an urban environment," Renewable Energy, Elsevier, vol. 149(C), pages 1406-1413.
    18. Bosch, J.L. & Batlles, F.J. & Zarzalejo, L.F. & López, G., 2010. "Solar resources estimation combining digital terrain models and satellite images techniques," Renewable Energy, Elsevier, vol. 35(12), pages 2853-2861.
    19. ur Rehman, Naveed & Hijazi, Mohamad & Uzair, Muhammad, 2020. "Solar potential assessment of public bus routes for solar buses," Renewable Energy, Elsevier, vol. 156(C), pages 193-200.
    20. Almorox, Javier & Voyant, Cyril & Bailek, Nadjem & Kuriqi, Alban & Arnaldo, J.A., 2021. "Total solar irradiance's effect on the performance of empirical models for estimating global solar radiation: An empirical-based review," Energy, Elsevier, vol. 236(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:15:y:2022:i:19:p:7018-:d:923969. 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.