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Determining roof surfaces suitable for the installation of PV (photovoltaic) systems, based on LiDAR (Light Detection And Ranging) data, pyranometer measurements, and distribution network configuration

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  • Srećković, Nevena
  • Lukač, Niko
  • Žalik, Borut
  • Štumberger, Gorazd

Abstract

Proliferation of distributed generation units, integrated within the distribution network requires increased attention to their proper placements. In urban areas, buildings' rooftops are expected to have greater involvement in the deployment of PV (photovoltaic) systems. This paper proposes a novel procedure for determining roof surfaces suitable for their installation. The PV potential of roof surfaces is assessed based on Light Detection And Ranging (LiDAR) data and pyranometer measurements. Then, the time-dependent PV generation profiles, electricity distribution network configuration, and time-dependent loading profiles are used together over time-steps for selecting those roof surfaces with the highest PV potential, which would lead to the highest reduction of network losses per year. The presented procedure was implemented within a real urban area distribution network. The results obtained confirmed that PV potential assessment could be an insufficient criterion when selecting those roof surfaces suitable for the installation of PV systems. In order to obtain relevant results, network configuration and time-dependent loading and generation profiles must be considered as well.

Suggested Citation

  • Srećković, Nevena & Lukač, Niko & Žalik, Borut & Štumberger, Gorazd, 2016. "Determining roof surfaces suitable for the installation of PV (photovoltaic) systems, based on LiDAR (Light Detection And Ranging) data, pyranometer measurements, and distribution network configuratio," Energy, Elsevier, vol. 96(C), pages 404-414.
    • Handle: RePEc:eee:energy:v:96:y:2016:i:c:p:404-414
    DOI: 10.1016/j.energy.2015.12.078
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    Cited by:

    1. Liu, Zhengguang & Guo, Zhiling & Chen, Qi & Song, Chenchen & Shang, Wenlong & Yuan, Meng & Zhang, Haoran, 2023. "A review of data-driven smart building-integrated photovoltaic systems: Challenges and objectives," Energy, Elsevier, vol. 263(PE).
    2. Joshua M. Pearce & Emily Prehoda, 2019. "Could 79 People Solarize the U.S. Electric Grid?," Societies, MDPI, vol. 9(1), pages 1-27, March.
    3. Seme, Sebastijan & Lukač, Niko & Štumberger, Bojan & Hadžiselimović, Miralem, 2017. "Power quality experimental analysis of grid-connected photovoltaic systems in urban distribution networks," Energy, Elsevier, vol. 139(C), pages 1261-1266.
    4. 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).
    5. 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).

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