IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v298y2021ics0306261921006905.html
   My bibliography  Save this article

Unsupervised azimuth estimation of solar arrays in low-resolution satellite imagery through semantic segmentation and Hough transform

Author

Listed:
  • Edun, Ayobami S.
  • Perry, Kirsten
  • Harley, Joel B.
  • Deline, Chris

Abstract

This paper explains the use of a convolutional neural network (CNN) to segment solar panels in a satellite image containing solar arrays, and extract associated metadata from the arrays. A novel unsupervised technique is introduced to estimate the azimuth of each individual solar panel from the predicted mask of the convolutional neural network. This pipeline was developed with the aim of extracting necessary metadata for a solar installation, using only a set of latitude–longitude coordinates. Azimuth prediction results for 669 individual solar installations associated with 387 sites located across the United States are provided. A mean average error and median average error of 21.65 degrees and 1.0 degrees were obtained, respectively, when predicting the azimuth of the solar fleet data set, with about 80% of the results within an error of zero degrees of the ground truth azimuth value and about 85% within an error of 25 degrees. The predicted azimuth was then used to estimate the energy conversion of the solar arrays. Results show a 90.9 and 90.6 R-squared value for estimating alternating current (AC) and direct current (DC) energy, respectively, and a mean absolute percentage error (MAPE) of 1.70% in estimating the alternating current (AC) energy using the fully automated algorithm.

Suggested Citation

  • Edun, Ayobami S. & Perry, Kirsten & Harley, Joel B. & Deline, Chris, 2021. "Unsupervised azimuth estimation of solar arrays in low-resolution satellite imagery through semantic segmentation and Hough transform," Applied Energy, Elsevier, vol. 298(C).
    • Handle: RePEc:eee:appene:v:298:y:2021:i:c:s0306261921006905
    DOI: 10.1016/j.apenergy.2021.117273
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921006905
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2021.117273?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. Zhang, Chen & Li, Zhixin & Jiang, Haihua & Luo, Yongqiang & Xu, Shen, 2021. "Deep learning method for evaluating photovoltaic potential of urban land-use: A case study of Wuhan, China," Applied Energy, Elsevier, vol. 283(C).
    2. Le Roux, W.G., 2016. "Optimum tilt and azimuth angles for fixed solar collectors in South Africa using measured data," Renewable Energy, Elsevier, vol. 96(PA), pages 603-612.
    3. Rowlands, Ian H. & Kemery, Briana Paige & Beausoleil-Morrison, Ian, 2011. "Optimal solar-PV tilt angle and azimuth: An Ontario (Canada) case-study," Energy Policy, Elsevier, vol. 39(3), pages 1397-1409, March.
    4. Mohammadi, Kasra & Khorasanizadeh, Hossein, 2015. "A review of solar radiation on vertically mounted solar surfaces and proper azimuth angles in six Iranian major cities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 504-518.
    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. Haghdadi, Navid & Copper, Jessie & Bruce, Anna & MacGill, Iain, 2017. "A method to estimate the location and orientation of distributed photovoltaic systems from their generation output data," Renewable Energy, Elsevier, vol. 108(C), pages 390-400.
    7. Malof, Jordan M. & Bradbury, Kyle & Collins, Leslie M. & Newell, Richard G., 2016. "Automatic detection of solar photovoltaic arrays in high resolution aerial imagery," Applied Energy, Elsevier, vol. 183(C), pages 229-240.
    8. Streltsov, Artem & Malof, Jordan M. & Huang, Bohao & Bradbury, Kyle, 2020. "Estimating residential building energy consumption using overhead imagery," Applied Energy, Elsevier, vol. 280(C).
    9. Oladiran, M. T., 1995. "Mean global radiation captured by inclined collectors at various surface azimuth angles in Nigeria," Applied Energy, Elsevier, vol. 52(4), pages 317-330.
    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. Chen, Qi & Li, Xinyuan & Zhang, Zhengjia & Zhou, Chao & Guo, Zhiling & Liu, Zhengguang & Zhang, Haoran, 2023. "Remote sensing of photovoltaic scenarios: Techniques, applications and future directions," Applied Energy, Elsevier, vol. 333(C).
    2. Mayer, Kevin & Rausch, Benjamin & Arlt, Marie-Louise & Gust, Gunther & Wang, Zhecheng & Neumann, Dirk & Rajagopal, Ram, 2022. "3D-PV-Locator: Large-scale detection of rooftop-mounted photovoltaic systems in 3D," Applied Energy, Elsevier, vol. 310(C).
    3. Mao, Hongzhi & Chen, Xie & Luo, Yongqiang & Deng, Jie & Tian, Zhiyong & Yu, Jinghua & Xiao, Yimin & Fan, Jianhua, 2023. "Advances and prospects on estimating solar photovoltaic installation capacity and potential based on satellite and aerial images," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(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. Mao, Hongzhi & Chen, Xie & Luo, Yongqiang & Deng, Jie & Tian, Zhiyong & Yu, Jinghua & Xiao, Yimin & Fan, Jianhua, 2023. "Advances and prospects on estimating solar photovoltaic installation capacity and potential based on satellite and aerial images," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(C).
    2. Dey, Sumon & Lakshmanan, Madan Kumar & Pesala, Bala, 2018. "Optimal solar tree design for increased flexibility in seasonal energy extraction," Renewable Energy, Elsevier, vol. 125(C), pages 1038-1048.
    3. Mayer, Kevin & Rausch, Benjamin & Arlt, Marie-Louise & Gust, Gunther & Wang, Zhecheng & Neumann, Dirk & Rajagopal, Ram, 2022. "3D-PV-Locator: Large-scale detection of rooftop-mounted photovoltaic systems in 3D," Applied Energy, Elsevier, vol. 310(C).
    4. 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.
    5. Yagli, Gokhan Mert & Yang, Dazhi & Gandhi, Oktoviano & Srinivasan, Dipti, 2020. "Can we justify producing univariate machine-learning forecasts with satellite-derived solar irradiance?," Applied Energy, Elsevier, vol. 259(C).
    6. Chinchilla, Monica & Santos-Martín, David & Carpintero-Rentería, Miguel & Lemon, Scott, 2021. "Worldwide annual optimum tilt angle model for solar collectors and photovoltaic systems in the absence of site meteorological data," Applied Energy, Elsevier, vol. 281(C).
    7. Al Garni, Hassan Z. & Awasthi, Anjali & Wright, David, 2019. "Optimal orientation angles for maximizing energy yield for solar PV in Saudi Arabia," Renewable Energy, Elsevier, vol. 133(C), pages 538-550.
    8. Chen, Qi & Li, Xinyuan & Zhang, Zhengjia & Zhou, Chao & Guo, Zhiling & Liu, Zhengguang & Zhang, Haoran, 2023. "Remote sensing of photovoltaic scenarios: Techniques, applications and future directions," Applied Energy, Elsevier, vol. 333(C).
    9. Yadav, Somil & Panda, S.K. & Hachem-Vermette, Caroline, 2020. "Optimum azimuth and inclination angle of BIPV panel owing to different factors influencing the shadow of adjacent building," Renewable Energy, Elsevier, vol. 162(C), pages 381-396.
    10. Zhong, Qing & Tong, Daoqin, 2020. "Spatial layout optimization for solar photovoltaic (PV) panel installation," Renewable Energy, Elsevier, vol. 150(C), pages 1-11.
    11. Essa Alhamer & Addison Grigsby & Rydge Mulford, 2022. "The Influence of Seasonal Cloud Cover, Ambient Temperature and Seasonal Variations in Daylight Hours on the Optimal PV Panel Tilt Angle in the United States," Energies, MDPI, vol. 15(20), pages 1-14, October.
    12. Salah Beni Hamed & Mouna Ben Hamed & Lassaad Sbita, 2022. "Robust Voltage Control of a Buck DC-DC Converter: A Sliding Mode Approach," Energies, MDPI, vol. 15(17), pages 1-21, August.
    13. Mondol, Jayanta Deb & Yohanis, Yigzaw G. & Norton, Brian, 2007. "The impact of array inclination and orientation on the performance of a grid-connected photovoltaic system," Renewable Energy, Elsevier, vol. 32(1), pages 118-140.
    14. Gönül, Ömer & Yazar, Fatih & Duman, A. Can & Güler, Önder, 2022. "A comparative techno-economic assessment of manually adjustable tilt mechanisms and automatic solar trackers for behind-the-meter PV applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    15. Giwa, Adewale & Alabi, Adetunji & Yusuf, Ahmed & Olukan, Tuza, 2017. "A comprehensive review on biomass and solar energy for sustainable energy generation in Nigeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 620-641.
    16. Marcin Bukowski & Janusz Majewski & Agnieszka Sobolewska, 2020. "Macroeconomic Electric Energy Production Efficiency of Photovoltaic Panels in Single-Family Homes in Poland," Energies, MDPI, vol. 14(1), pages 1-21, December.
    17. Mohammadi, Kasra & Khorasanizadeh, Hossein, 2015. "A review of solar radiation on vertically mounted solar surfaces and proper azimuth angles in six Iranian major cities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 504-518.
    18. Konstantinos Ioannou & Dimitrios Myronidis, 2021. "Automatic Detection of Photovoltaic Farms Using Satellite Imagery and Convolutional Neural Networks," Sustainability, MDPI, vol. 13(9), pages 1-15, May.
    19. Mohammad K. Najjar & Eduardo Linhares Qualharini & Ahmed W. A. Hammad & Dieter Boer & Assed Haddad, 2019. "Framework for a Systematic Parametric Analysis to Maximize Energy Output of PV Modules Using an Experimental Design," Sustainability, MDPI, vol. 11(10), pages 1-24, May.
    20. Rajput, Usman Jamil & Alhadrami, Hani & Al-Hazmi, Faten & Guo, Quiquan & Yang, Jun, 2017. "Initial investigations of a combined photo-assisted water cleaner and thermal collector," Renewable Energy, Elsevier, vol. 113(C), pages 235-247.

    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:298:y:2021:i:c:s0306261921006905. 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.