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Rooftop photovoltaic potential in Istanbul: Calculations based on LiDAR data, measurements and verifications

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  • Yildirim, Deniz
  • Büyüksalih, Gürcan
  • Şahin, Ahmet Duran

Abstract

Usage of solar energy is increasing steadily especially in the rooftop installations of buildings in large cities. This study contains calculations of electrical energy produced by photovoltaic panels placed on roofs of buildings for city of Istanbul using building data and verify calculated results by a mobile measurement system. Three dimensional city model utilizes light detection and ranging data that covers an area of 5400 km2 for the whole city. The main object classes such as ground, building, vegetation were derived, buildings are vectorized and a digital elevation model are used for the generation of a second level of detail. Using the geometric data of the buildings in Istanbul as input to the developed software, the electricity production of panels is calculated on the suitable roofs of the buildings considering the observed climatic conditions and solar radiation for the city. A photovoltaic weather mobile vehicle measurement system was designed and applied for verification of developed model in eight different areas of Istanbul for stationing 50 days at each location. Results of difference between measurements and calculations of solar irradiation and electrical energy production are 2.44% and 14.70%, respectively. Batch processing was performed on 39 districts of Istanbul with 1.3 million buildings and annual electrical energy production from the roofs of all buildings is calculated to be 30.8 TWh at the point of common coupling to the utility. Total rooftop electricity production of Istanbul has a potential to meet 67% of the total electricity consumption for the year 2019.

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  • Yildirim, Deniz & Büyüksalih, Gürcan & Şahin, Ahmet Duran, 2021. "Rooftop photovoltaic potential in Istanbul: Calculations based on LiDAR data, measurements and verifications," Applied Energy, Elsevier, vol. 304(C).
    • Handle: RePEc:eee:appene:v:304:y:2021:i:c:s0306261921010898
    DOI: 10.1016/j.apenergy.2021.117743
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    References listed on IDEAS

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    2. Özdemir, Samed & Yavuzdoğan, Ahmet & Bilgilioğlu, Burhan Baha & Akbulut, Zeynep, 2023. "SPAN: An open-source plugin for photovoltaic potential estimation of individual roof segments using point cloud data," Renewable Energy, Elsevier, vol. 216(C).
    3. Jingtao Li & Zhixin Li & Yao Wang & Hong Zhang, 2023. "Energy Utilization and Carbon Reduction Potential of Solar Energy in Residential Blocks: A Case Study on a Tropical High-Density City in China," Sustainability, MDPI, vol. 15(17), pages 1-25, August.
    4. Salim, Daniel Henrique Carneiro & de Sousa Mello, Caio César & Franco, Guilherme Gandra & de Albuquerque Nóbrega, Rodrigo Affonso & de Paula, Eduardo Coutinho & Fonseca, Bráulio Magalhães & Nero, Marc, 2023. "Unveiling Fernando de Noronha Island's photovoltaic potential with unmanned aerial survey and irradiation modeling," Applied Energy, Elsevier, vol. 337(C).
    5. Sun, Tao & Shan, Ming & Rong, Xing & Yang, Xudong, 2022. "Estimating the spatial distribution of solar photovoltaic power generation potential on different types of rural rooftops using a deep learning network applied to satellite images," Applied Energy, Elsevier, vol. 315(C).

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