The Urban Rooftop Photovoltaic Potential Determination
Urban areas can be considered high-potential energy producers alongside their notable portion of energy consumption. Solar energy is the most promising sustainable energy in which urban environments can produce electricity by using rooftop-mounted photovoltaic systems. While the precise knowledge of...
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doaj-1d2e865422d2472c9a80c0d79db16f282021-07-15T15:47:49ZengMDPI AGSustainability2071-10502021-07-01137447744710.3390/su13137447The Urban Rooftop Photovoltaic Potential DeterminationElham Fakhraian0Marc Alier1Francesc Valls Dalmau2Alireza Nameni3Maria José Casañ Guerrero4Institute of Sustainability, Universitat Politècnica de Catalunya, 08034 Barcelona, SpainDepartment of Services and Information Systems Engineering (ESSI), Universitat Politècnica de Catalunya, 08034 Barcelona, SpainDepartment of Architectural Representation, Universitat Politècnica de Catalunya, 08028 Barcelona, SpainInstitute of Sustainability, Universitat Politècnica de Catalunya, 08034 Barcelona, SpainDepartment of Services and Information Systems Engineering (ESSI), Universitat Politècnica de Catalunya, 08034 Barcelona, SpainUrban areas can be considered high-potential energy producers alongside their notable portion of energy consumption. Solar energy is the most promising sustainable energy in which urban environments can produce electricity by using rooftop-mounted photovoltaic systems. While the precise knowledge of electricity production from solar energy resources as well as the needed parameters to define the optimal locations require an adequate study, effective guidelines for optimal installation of solar photovoltaics remain a challenge. This paper aims to make a complete systematic review and states the vital steps with their data resources to find the urban rooftop PV potential. Organizing the methodologies is another novelty of this paper to create a complete global basis for future studies and improve a more detailed degree in this particular field.https://www.mdpi.com/2071-1050/13/13/7447rooftop photovoltaic potentialsolar photovoltaicsurban solar potentialLIDARGISmachine learning |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Elham Fakhraian Marc Alier Francesc Valls Dalmau Alireza Nameni Maria José Casañ Guerrero |
spellingShingle |
Elham Fakhraian Marc Alier Francesc Valls Dalmau Alireza Nameni Maria José Casañ Guerrero The Urban Rooftop Photovoltaic Potential Determination Sustainability rooftop photovoltaic potential solar photovoltaics urban solar potential LIDAR GIS machine learning |
author_facet |
Elham Fakhraian Marc Alier Francesc Valls Dalmau Alireza Nameni Maria José Casañ Guerrero |
author_sort |
Elham Fakhraian |
title |
The Urban Rooftop Photovoltaic Potential Determination |
title_short |
The Urban Rooftop Photovoltaic Potential Determination |
title_full |
The Urban Rooftop Photovoltaic Potential Determination |
title_fullStr |
The Urban Rooftop Photovoltaic Potential Determination |
title_full_unstemmed |
The Urban Rooftop Photovoltaic Potential Determination |
title_sort |
urban rooftop photovoltaic potential determination |
publisher |
MDPI AG |
series |
Sustainability |
issn |
2071-1050 |
publishDate |
2021-07-01 |
description |
Urban areas can be considered high-potential energy producers alongside their notable portion of energy consumption. Solar energy is the most promising sustainable energy in which urban environments can produce electricity by using rooftop-mounted photovoltaic systems. While the precise knowledge of electricity production from solar energy resources as well as the needed parameters to define the optimal locations require an adequate study, effective guidelines for optimal installation of solar photovoltaics remain a challenge. This paper aims to make a complete systematic review and states the vital steps with their data resources to find the urban rooftop PV potential. Organizing the methodologies is another novelty of this paper to create a complete global basis for future studies and improve a more detailed degree in this particular field. |
topic |
rooftop photovoltaic potential solar photovoltaics urban solar potential LIDAR GIS machine learning |
url |
https://www.mdpi.com/2071-1050/13/13/7447 |
work_keys_str_mv |
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