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Economic and environmental assessment of rooftops regarding suitability for photovoltaic systems installation based on remote sensing data

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  • Lukač, Niko
  • Seme, Sebastijan
  • Dežan, Katarina
  • Žalik, Borut
  • Štumberger, Gorazd

Abstract

Within the last few years, the increase of the world's energy consumption has substantially impacted the environment. Solar energy initiative is more than ever involved to tackle this issue, especially when deploying PV (photovoltaic) systems over large-scale residential areas. However, not all surfaces in these areas are economically suitable, while some surfaces have low CO2 mitigation. With the availability of high-resolution remote sensing data, the estimation of suitable rooftops for PV systems installation can be performed automatically by estimating the PV potential. This paper presents a novel method for estimating NPV (net present value) of the potential PV systems installed on rooftops by using LiDAR (Light Detection And Ranging) data and PV systems' nonlinear efficiency characteristics. More importantly, the environmental impact is estimated for each rooftop through EPBT (energy payback time) and GGER (greenhouse gas emission rate), based on the life-cycle of a specific PV system. This is combined with NPV in order to find rooftops that are both economically and environmentally viable candidates for PV systems deployment. Results demonstrate a case study LiDAR data for predicting each building's economical and environmental impact, as well as providing an overall view of resulting cumulative CO2 mitigation over large residential area.

Suggested Citation

  • Lukač, Niko & Seme, Sebastijan & Dežan, Katarina & Žalik, Borut & Štumberger, Gorazd, 2016. "Economic and environmental assessment of rooftops regarding suitability for photovoltaic systems installation based on remote sensing data," Energy, Elsevier, vol. 107(C), pages 854-865.
    • Handle: RePEc:eee:energy:v:107:y:2016:i:c:p:854-865
    DOI: 10.1016/j.energy.2016.04.089
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    5. 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.
    6. Seme, Sebastijan & Sredenšek, Klemen & Praunseis, Zdravko & Štumberger, Bojan & Hadžiselimović, Miralem, 2018. "Optimal price of electricity of solar power plants and small hydro power plants – Technical and economical part of investments," Energy, Elsevier, vol. 157(C), pages 87-95.
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    8. Saad Odeh & Tri Hieu Nguyen, 2021. "Assessment Method to Identify the Potential of Rooftop PV Systems in the Residential Districts," Energies, MDPI, vol. 14(14), pages 1-11, July.
    9. Sameh Monna & Ramez Abdallah & Adel Juaidi & Aiman Albatayneh & Antonio Jesús Zapata-Sierra & Francisco Manzano-Agugliaro, 2022. "Potential Electricity Production by Installing Photovoltaic Systems on the Rooftops of Residential Buildings in Jordan: An Approach to Climate Change Mitigation," Energies, MDPI, vol. 15(2), pages 1-15, January.
    10. Coppitters, Diederik & De Paepe, Ward & Contino, Francesco, 2020. "Robust design optimization and stochastic performance analysis of a grid-connected photovoltaic system with battery storage and hydrogen storage," Energy, Elsevier, vol. 213(C).
    11. 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.
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