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A methodology to estimate the photovoltaic potential on parking spaces and water deposits. The case of the Canary Islands

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  • Julieta, Schallenberg-Rodriguez
  • José-Julio, Rodrigo-Bello
  • Pablo, Yanez-Rosales

Abstract

In regions where the land available is scarce it is of special interest to deploy solar photovoltaic energy without occupying additional land. Besides solar roofs, which have already been extensively studied, there are other type of constructions that could be used for the deployment of solar photovoltaic such as car parking spaces and big water deposits. No much attention has been given so far to these type of elements that could potentially been used to deploy solar photovoltaic energy. So the aim of this research is to establish how relevant can these type of surfaces be in terms of solar energy production. For this purpose a methodology has been developed to identify the surfaces corresponding to uncovered parking spaces and water deposit at regional level using cartographic information, first, and, secondly, to estimate how much of these areas could be used to deploy solar photovoltaic energy. This methodology has been applied to one insular region, the Canary Islands, and the results are surprising in terms of the potentiality of these type of elements for the deployment of solar photovoltaic energy which could cover around 9% of the whole regional electricity demand.

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  • Julieta, Schallenberg-Rodriguez & José-Julio, Rodrigo-Bello & Pablo, Yanez-Rosales, 2022. "A methodology to estimate the photovoltaic potential on parking spaces and water deposits. The case of the Canary Islands," Renewable Energy, Elsevier, vol. 189(C), pages 1046-1062.
    • Handle: RePEc:eee:renene:v:189:y:2022:i:c:p:1046-1062
    DOI: 10.1016/j.renene.2022.02.103
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    References listed on IDEAS

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    1. Meskiana Boulahia & Kahina Amal Djiar & Miguel Amado, 2021. "Combined Engineering—Statistical Method for Assessing Solar Photovoltaic Potential on Residential Rooftops: Case of Laghouat in Central Southern Algeria," Energies, MDPI, vol. 14(6), pages 1-16, March.
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    3. Lukač, Niko & Seme, Sebastijan & Žlaus, Danijel & Štumberger, Gorazd & Žalik, Borut, 2014. "Buildings roofs photovoltaic potential assessment based on LiDAR (Light Detection And Ranging) data," Energy, Elsevier, vol. 66(C), pages 598-609.
    4. Hong, Taehoon & Lee, Minhyun & Koo, Choongwan & Jeong, Kwangbok & Kim, Jimin, 2017. "Development of a method for estimating the rooftop solar photovoltaic (PV) potential by analyzing the available rooftop area using Hillshade analysis," Applied Energy, Elsevier, vol. 194(C), pages 320-332.
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    1. Maier, Rachel & Lütz, Luna & Risch, Stanley & Kullmann, Felix & Weinand, Jann & Stolten, Detlef, 2024. "Potential of floating, parking, and agri photovoltaics in Germany," Renewable and Sustainable Energy Reviews, Elsevier, vol. 200(C).
    2. 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).

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