Rooftop photovoltaic potential analysis based on UAV-derived 3D-data and open source software

Detalhes bibliográficos
Autor(a) principal: Khan, Muhammad Gulraiz
Data de Publicação: 2020
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/94401
Resumo: Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial Technologies
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spelling Rooftop photovoltaic potential analysis based on UAV-derived 3D-data and open source softwareElectric energyEconomic growthNatural resourcesRural populationRenewable Energy SourcesDissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesElectric energy is one of the driving forces for economic growth. Energy supply to rural areas is a big challenge for many countries, especially for those with less income and sparse settlements where main grid supply is not feasible. Solar energy is the most abundant, clean and readily available natural energy source. Open source technology and low cost UAV data can be used to assess solar potential on rooftops so that main grid supply will not be required for small settlements. This research aimed to develop procedures and workflows to address this problem. A test site in Muenster WWU (Leonardo campus) was used to test the model because both UAV and highly accurate laser scanning data are readily available. Solar global irradiance data was also available for Germany. After pre-processing of raw UAV images, rooftop extraction model was designed to extract rooftops using RGB images and 3D data. Solar energy calculation model was used to compute the potential for each raster pixel for extracted rooftops. Open Drone Map, Docker and QGIS were all open source software used to run this workflow. This model can be implemented on different regions under some constraints. Accuracy assessment gave insight of the accuracy of this GIS model, so that future improvements can be made.Prinz, TorstenKnoth, ChristianCabral, Pedro da Costa BritoRUNKhan, Muhammad Gulraiz2020-03-17T14:31:33Z2020-01-312020-01-31T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/94401TID:202458148enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:42:22Zoai:run.unl.pt:10362/94401Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:37:56.817231Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Rooftop photovoltaic potential analysis based on UAV-derived 3D-data and open source software
title Rooftop photovoltaic potential analysis based on UAV-derived 3D-data and open source software
spellingShingle Rooftop photovoltaic potential analysis based on UAV-derived 3D-data and open source software
Khan, Muhammad Gulraiz
Electric energy
Economic growth
Natural resources
Rural population
Renewable Energy Sources
title_short Rooftop photovoltaic potential analysis based on UAV-derived 3D-data and open source software
title_full Rooftop photovoltaic potential analysis based on UAV-derived 3D-data and open source software
title_fullStr Rooftop photovoltaic potential analysis based on UAV-derived 3D-data and open source software
title_full_unstemmed Rooftop photovoltaic potential analysis based on UAV-derived 3D-data and open source software
title_sort Rooftop photovoltaic potential analysis based on UAV-derived 3D-data and open source software
author Khan, Muhammad Gulraiz
author_facet Khan, Muhammad Gulraiz
author_role author
dc.contributor.none.fl_str_mv Prinz, Torsten
Knoth, Christian
Cabral, Pedro da Costa Brito
RUN
dc.contributor.author.fl_str_mv Khan, Muhammad Gulraiz
dc.subject.por.fl_str_mv Electric energy
Economic growth
Natural resources
Rural population
Renewable Energy Sources
topic Electric energy
Economic growth
Natural resources
Rural population
Renewable Energy Sources
description Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial Technologies
publishDate 2020
dc.date.none.fl_str_mv 2020-03-17T14:31:33Z
2020-01-31
2020-01-31T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/94401
TID:202458148
url http://hdl.handle.net/10362/94401
identifier_str_mv TID:202458148
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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