IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v198y2022icp804-824.html
   My bibliography  Save this article

Impacts of surface model generation approaches on raytracing-based solar potential estimation in urban areas

Author

Listed:
  • Tian, B.
  • Loonen, R.C.G.M.
  • Bognár, Á.
  • Hensen, J.L.M.

Abstract

Raytracing-based methods are widely used for quantifying irradiation on building surfaces. Urban 3D surface models are necessary input for raytracing simulations, which can be generated from open-source point cloud data with the help of surface reconstruction algorithms. In research and engineering practice, various algorithms are being used for this purpose; each leading to different mesh topologies and corresponding performance. This paper compares the impacts of four different reconstruction algorithms by investigating their performance using DAYSIM raytracing simulations. The analysis is carried out for five configurations with various urban morphologies. Results show that the reconstructed models consistently underestimate the shading influence due to geometrical shrinkages that emerge from the various model generation procedures. The explicit algorithms, with Generic Delaunay a notable example, have better performance with less embedded error than the implicit algorithms in both daily and annual simulations. Results also show that diffuse irradiance is responsible for larger contributions to the overall error than direct components. This effect becomes more prominent when modeling reflected irradiation in urban environments. Additionally, the work shows that solar elevation and shading geometry types also affect the error magnitude. The paper concludes by providing reconstruction algorithm selection criteria for photovoltaic practitioners and urban energy planners.

Suggested Citation

  • Tian, B. & Loonen, R.C.G.M. & Bognár, Á. & Hensen, J.L.M., 2022. "Impacts of surface model generation approaches on raytracing-based solar potential estimation in urban areas," Renewable Energy, Elsevier, vol. 198(C), pages 804-824.
  • Handle: RePEc:eee:renene:v:198:y:2022:i:c:p:804-824
    DOI: 10.1016/j.renene.2022.08.095
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148122012708
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2022.08.095?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. 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. 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.
    3. Freitas, Sara & Santos, Teresa & Brito, Miguel C., 2018. "Impact of large scale PV deployment in the sizing of urban distribution transformers," Renewable Energy, Elsevier, vol. 119(C), pages 767-776.
    4. 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.
    5. Lingfors, D. & Bright, J.M. & Engerer, N.A. & Ahlberg, J. & Killinger, S. & Widén, J., 2017. "Comparing the capability of low- and high-resolution LiDAR data with application to solar resource assessment, roof type classification and shading analysis," Applied Energy, Elsevier, vol. 205(C), pages 1216-1230.
    6. Mohajeri, Nahid & Perera, A.T.D. & Coccolo, Silvia & Mosca, Lucas & Le Guen, Morgane & Scartezzini, Jean-Louis, 2019. "Integrating urban form and distributed energy systems: Assessment of sustainable development scenarios for a Swiss village to 2050," Renewable Energy, Elsevier, vol. 143(C), pages 810-826.
    7. Jakica, Nebojsa, 2018. "State-of-the-art review of solar design tools and methods for assessing daylighting and solar potential for building-integrated photovoltaics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1296-1328.
    8. Shi, Zhongming & Fonseca, Jimeno A. & Schlueter, Arno, 2021. "A parametric method using vernacular urban block typologies for investigating interactions between solar energy use and urban design," Renewable Energy, Elsevier, vol. 165(P1), pages 823-841.
    9. Gonçalves, Juliana E. & van Hooff, Twan & Saelens, Dirk, 2021. "Simulating building integrated photovoltaic facades: Comparison to experimental data and evaluation of modelling complexity," Applied Energy, Elsevier, vol. 281(C).
    10. Walker, Linus & Hofer, Johannes & Schlueter, Arno, 2019. "High-resolution, parametric BIPV and electrical systems modeling and design," Applied Energy, Elsevier, vol. 238(C), pages 164-179.
    11. Andreou, E., 2014. "The effect of urban layout, street geometry and orientation on shading conditions in urban canyons in the Mediterranean," Renewable Energy, Elsevier, vol. 63(C), pages 587-596.
    12. Baoyun Guo & Jiawen Wang & Xiaobin Jiang & Cailin Li & Benya Su & Zhiting Cui & Yankun Sun & ChangLei Yang, 2020. "A 3D Surface Reconstruction Method for Large-Scale Point Cloud Data," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-14, August.
    13. Mohamed, Mohamed A. & Zaki Diab, Ahmed A. & Rezk, Hegazy, 2019. "Partial shading mitigation of PV systems via different meta-heuristic techniques," Renewable Energy, Elsevier, vol. 130(C), pages 1159-1175.
    14. Oh, Myeongchan & Kim, Sung-Min & Park, Hyeong-Dong, 2020. "Estimation of photovoltaic potential of solar bus in an urban area: Case study in Gwanak, Seoul, Korea," Renewable Energy, Elsevier, vol. 160(C), pages 1335-1348.
    15. Rouani, Lahcene & Harkat, Mohamed Faouzi & Kouadri, Abdelmalek & Mekhilef, Saad, 2021. "Shading fault detection in a grid-connected PV system using vertices principal component analysis," Renewable Energy, Elsevier, vol. 164(C), pages 1527-1539.
    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. Žalik, Mitja & Mongus, Domen & Lukač, Niko, 2024. "High-resolution spatiotemporal assessment of solar potential from remote sensing data using deep learning," Renewable Energy, Elsevier, vol. 222(C).

    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. Agnieszka Bieda & Agnieszka Cienciała, 2021. "Towards a Renewable Energy Source Cadastre—A Review of Examples from around the World," Energies, MDPI, vol. 14(23), pages 1-34, December.
    2. Bushra, Nayab, 2022. "A comprehensive analysis of parametric design approaches for solar integration with buildings: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    3. 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.
    4. Freitas, Jader de Sousa & Cronemberger, Joára & Soares, Raí Mariano & Amorim, Cláudia Naves David, 2020. "Modeling and assessing BIPV envelopes using parametric Rhinoceros plugins Grasshopper and Ladybug," Renewable Energy, Elsevier, vol. 160(C), pages 1468-1479.
    5. Gonçalves, Juliana E. & Montazeri, Hamid & van Hooff, Twan & Saelens, Dirk, 2021. "Performance of building integrated photovoltaic facades: Impact of exterior convective heat transfer," Applied Energy, Elsevier, vol. 287(C).
    6. 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).
    7. Lobaccaro, G. & Croce, S. & Lindkvist, C. & Munari Probst, M.C. & Scognamiglio, A. & Dahlberg, J. & Lundgren, M. & Wall, M., 2019. "A cross-country perspective on solar energy in urban planning: Lessons learned from international case studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 209-237.
    8. Sairam, Seshapalli & Seshadhri, Subathra & Marafioti, Giancarlo & Srinivasan, Seshadhri & Mathisen, Geir & Bekiroglu, Korkut, 2022. "Edge-based Explainable Fault Detection Systems for photovoltaic panels on edge nodes," Renewable Energy, Elsevier, vol. 185(C), pages 1425-1440.
    9. Arias-Rosales, Andrés & LeDuc, Philip R., 2022. "Shadow modeling in urban environments for solar harvesting devices with freely defined positions and orientations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 164(C).
    10. 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).
    11. Arias-Rosales, Andrés & LeDuc, Philip R., 2020. "Comparing View Factor modeling frameworks for the estimation of incident solar energy," Applied Energy, Elsevier, vol. 277(C).
    12. Shirazi, Ali Mohammad & Zomorodian, Zahra S. & Tahsildoost, Mohammad, 2019. "Techno-economic BIPV evaluation method in urban areas," Renewable Energy, Elsevier, vol. 143(C), pages 1235-1246.
    13. 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.
    14. Bushra, Nayab & Hartmann, Timo, 2024. "A method for design optimization of roof-integrated two-stage solar concentrators (TSSCs)," Applied Energy, Elsevier, vol. 353(PA).
    15. Freitas, S. & Brito, M.C., 2019. "Non-cumulative only solar photovoltaics for electricity load-matching," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 271-283.
    16. 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.
    17. Chen, Haoqian & Sui, Yi & Shang, Wen-long & Sun, Rencheng & Chen, Zhiheng & Wang, Changying & Han, Chunjia & Zhang, Yuqian & Zhang, Haoran, 2022. "Towards renewable public transport: Mining the performance of electric buses using solar-radiation as an auxiliary power source," Applied Energy, Elsevier, vol. 325(C).
    18. Arias-Rosales, Andrés & LeDuc, Philip R., 2023. "Urban solar harvesting: The importance of diffuse shadows in complex environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
    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. Sánchez-Aparicio, M. & Martín-Jiménez, J. & Del Pozo, S. & González-González, E. & Lagüela, S., 2021. "Ener3DMap-SolarWeb roofs: A geospatial web-based platform to compute photovoltaic potential," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(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:eee:renene:v:198:y:2022:i:c:p:804-824. 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.journals.elsevier.com/renewable-energy .

    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.