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Setting intelligent city tiling strategies for urban shading simulations
•Assessment of innovative computational strategies in an urban simulation platform.•Introduction of different tiling approaches for solar irradiance calculations.•Estimations of the Urban Shading Ratio for roofs and facades in large areas.•Analysis of two case studies with medium and high building d...
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Published in: | Solar energy 2017-11, Vol.157, p.880-894 |
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creator | Romero Rodríguez, Laura Nouvel, Romain Duminil, Eric Eicker, Ursula |
description | •Assessment of innovative computational strategies in an urban simulation platform.•Introduction of different tiling approaches for solar irradiance calculations.•Estimations of the Urban Shading Ratio for roofs and facades in large areas.•Analysis of two case studies with medium and high building densities.•Irradiance reductions up to 60% for facades and 25% for roofs in dense urban areas.
Assessing accurately the solar potential of all building surfaces in cities, including shading and multiple reflections between buildings, is essential for urban energy modelling. However, since the number of surface interactions and radiation exchanges increase exponentially with the scale of the district, innovative computational strategies are needed, some of which will be introduced in the present work. They should hold the best compromise between result accuracy and computational efficiency, i.e. computational time and memory requirements.
In this study, different approaches that may be used for the computation of urban solar irradiance in large areas are presented. Two concrete urban case studies of different densities have been used to compare and evaluate three different methods: the Perez Sky model, the Simplified Radiosity Algorithm and a new scene tiling method implemented in our urban simulation platform SimStadt, used for feasible estimations on a large scale. To quantify the influence of shading, the new concept of Urban Shading Ratio has been introduced and used for this evaluation process. In high density urban areas, this index may reach 60% for facades and 25% for roofs. Tiles of 500m width and 200m overlap are a minimum requirement in this case to compute solar irradiance with an acceptable accuracy. In medium density areas, tiles of 300m width and 100m overlap meet perfectly the accuracy requirements. In addition, the solar potential for various solar energy thresholds as well as the monthly variation of the Urban Shading Ratio have been quantified for both case studies, distinguishing between roofs and facades of different orientations. |
doi_str_mv | 10.1016/j.solener.2017.09.017 |
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Assessing accurately the solar potential of all building surfaces in cities, including shading and multiple reflections between buildings, is essential for urban energy modelling. However, since the number of surface interactions and radiation exchanges increase exponentially with the scale of the district, innovative computational strategies are needed, some of which will be introduced in the present work. They should hold the best compromise between result accuracy and computational efficiency, i.e. computational time and memory requirements.
In this study, different approaches that may be used for the computation of urban solar irradiance in large areas are presented. Two concrete urban case studies of different densities have been used to compare and evaluate three different methods: the Perez Sky model, the Simplified Radiosity Algorithm and a new scene tiling method implemented in our urban simulation platform SimStadt, used for feasible estimations on a large scale. To quantify the influence of shading, the new concept of Urban Shading Ratio has been introduced and used for this evaluation process. In high density urban areas, this index may reach 60% for facades and 25% for roofs. Tiles of 500m width and 200m overlap are a minimum requirement in this case to compute solar irradiance with an acceptable accuracy. In medium density areas, tiles of 300m width and 100m overlap meet perfectly the accuracy requirements. In addition, the solar potential for various solar energy thresholds as well as the monthly variation of the Urban Shading Ratio have been quantified for both case studies, distinguishing between roofs and facades of different orientations.</description><identifier>ISSN: 0038-092X</identifier><identifier>EISSN: 1471-1257</identifier><identifier>DOI: 10.1016/j.solener.2017.09.017</identifier><language>eng</language><publisher>New York: Elsevier Ltd</publisher><subject>Accuracy ; Case studies ; Cities ; Computer applications ; Computer memory ; Computer simulation ; Computing time ; Concrete ; Energy modeling ; Facades ; Irradiance ; Radiation ; Radiation models ; Radiosity ; Roofs ; Shading ; Solar energy ; Solar potential ; Tiles ; Tiling ; Tiling strategies ; Urban areas ; Urban shading ratio</subject><ispartof>Solar energy, 2017-11, Vol.157, p.880-894</ispartof><rights>2017 Elsevier Ltd</rights><rights>Copyright Pergamon Press Inc. Nov 15, 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c423t-527f686385d8c25de1464a9f51404bc10d1212e38b8d22b1b43953c5bf08b933</citedby><cites>FETCH-LOGICAL-c423t-527f686385d8c25de1464a9f51404bc10d1212e38b8d22b1b43953c5bf08b933</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Romero Rodríguez, Laura</creatorcontrib><creatorcontrib>Nouvel, Romain</creatorcontrib><creatorcontrib>Duminil, Eric</creatorcontrib><creatorcontrib>Eicker, Ursula</creatorcontrib><title>Setting intelligent city tiling strategies for urban shading simulations</title><title>Solar energy</title><description>•Assessment of innovative computational strategies in an urban simulation platform.•Introduction of different tiling approaches for solar irradiance calculations.•Estimations of the Urban Shading Ratio for roofs and facades in large areas.•Analysis of two case studies with medium and high building densities.•Irradiance reductions up to 60% for facades and 25% for roofs in dense urban areas.
Assessing accurately the solar potential of all building surfaces in cities, including shading and multiple reflections between buildings, is essential for urban energy modelling. However, since the number of surface interactions and radiation exchanges increase exponentially with the scale of the district, innovative computational strategies are needed, some of which will be introduced in the present work. They should hold the best compromise between result accuracy and computational efficiency, i.e. computational time and memory requirements.
In this study, different approaches that may be used for the computation of urban solar irradiance in large areas are presented. Two concrete urban case studies of different densities have been used to compare and evaluate three different methods: the Perez Sky model, the Simplified Radiosity Algorithm and a new scene tiling method implemented in our urban simulation platform SimStadt, used for feasible estimations on a large scale. To quantify the influence of shading, the new concept of Urban Shading Ratio has been introduced and used for this evaluation process. In high density urban areas, this index may reach 60% for facades and 25% for roofs. Tiles of 500m width and 200m overlap are a minimum requirement in this case to compute solar irradiance with an acceptable accuracy. In medium density areas, tiles of 300m width and 100m overlap meet perfectly the accuracy requirements. In addition, the solar potential for various solar energy thresholds as well as the monthly variation of the Urban Shading Ratio have been quantified for both case studies, distinguishing between roofs and facades of different orientations.</description><subject>Accuracy</subject><subject>Case studies</subject><subject>Cities</subject><subject>Computer applications</subject><subject>Computer memory</subject><subject>Computer simulation</subject><subject>Computing time</subject><subject>Concrete</subject><subject>Energy modeling</subject><subject>Facades</subject><subject>Irradiance</subject><subject>Radiation</subject><subject>Radiation models</subject><subject>Radiosity</subject><subject>Roofs</subject><subject>Shading</subject><subject>Solar energy</subject><subject>Solar potential</subject><subject>Tiles</subject><subject>Tiling</subject><subject>Tiling strategies</subject><subject>Urban areas</subject><subject>Urban shading ratio</subject><issn>0038-092X</issn><issn>1471-1257</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNqFUMtKxDAUDaLgOPoJQsF1a24ebboSGdQRBlw4C3ehTW_HlE46Jqkwf2_ruHd14J7H5RxCboFmQCG_77Iw9OjQZ4xCkdEym-CMLEAUkAKTxTlZUMpVSkv2cUmuQujopABVLMj6HWO0bpdYF7Hv7Q5dTIyNxyTafr6H6KuIO4shaQefjL6uXBI-q-aXtPuxr6IdXLgmF23VB7z5wyXZPj9tV-t08_byunrcpEYwHlPJijZXOVeyUYbJBkHkoipbCYKK2gBtgAFDrmrVMFZDLXgpuZF1S1Vdcr4kd6fYgx--RgxRd8Po3fRRQ6lEkQMUs0qeVMYPIXhs9cHbfeWPGqieN9Od_ttMz5tpWuoJJt_DyYdTg287scFYdAYb69FE3Qz2n4Qfjgl4Bw</recordid><startdate>20171115</startdate><enddate>20171115</enddate><creator>Romero Rodríguez, Laura</creator><creator>Nouvel, Romain</creator><creator>Duminil, Eric</creator><creator>Eicker, Ursula</creator><general>Elsevier Ltd</general><general>Pergamon Press Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7ST</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>KR7</scope><scope>L7M</scope><scope>SOI</scope></search><sort><creationdate>20171115</creationdate><title>Setting intelligent city tiling strategies for urban shading simulations</title><author>Romero Rodríguez, Laura ; Nouvel, Romain ; Duminil, Eric ; Eicker, Ursula</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c423t-527f686385d8c25de1464a9f51404bc10d1212e38b8d22b1b43953c5bf08b933</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Accuracy</topic><topic>Case studies</topic><topic>Cities</topic><topic>Computer applications</topic><topic>Computer memory</topic><topic>Computer simulation</topic><topic>Computing time</topic><topic>Concrete</topic><topic>Energy modeling</topic><topic>Facades</topic><topic>Irradiance</topic><topic>Radiation</topic><topic>Radiation models</topic><topic>Radiosity</topic><topic>Roofs</topic><topic>Shading</topic><topic>Solar energy</topic><topic>Solar potential</topic><topic>Tiles</topic><topic>Tiling</topic><topic>Tiling strategies</topic><topic>Urban areas</topic><topic>Urban shading ratio</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Romero Rodríguez, Laura</creatorcontrib><creatorcontrib>Nouvel, Romain</creatorcontrib><creatorcontrib>Duminil, Eric</creatorcontrib><creatorcontrib>Eicker, Ursula</creatorcontrib><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Environment Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Environment Abstracts</collection><jtitle>Solar energy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Romero Rodríguez, Laura</au><au>Nouvel, Romain</au><au>Duminil, Eric</au><au>Eicker, Ursula</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Setting intelligent city tiling strategies for urban shading simulations</atitle><jtitle>Solar energy</jtitle><date>2017-11-15</date><risdate>2017</risdate><volume>157</volume><spage>880</spage><epage>894</epage><pages>880-894</pages><issn>0038-092X</issn><eissn>1471-1257</eissn><abstract>•Assessment of innovative computational strategies in an urban simulation platform.•Introduction of different tiling approaches for solar irradiance calculations.•Estimations of the Urban Shading Ratio for roofs and facades in large areas.•Analysis of two case studies with medium and high building densities.•Irradiance reductions up to 60% for facades and 25% for roofs in dense urban areas.
Assessing accurately the solar potential of all building surfaces in cities, including shading and multiple reflections between buildings, is essential for urban energy modelling. However, since the number of surface interactions and radiation exchanges increase exponentially with the scale of the district, innovative computational strategies are needed, some of which will be introduced in the present work. They should hold the best compromise between result accuracy and computational efficiency, i.e. computational time and memory requirements.
In this study, different approaches that may be used for the computation of urban solar irradiance in large areas are presented. Two concrete urban case studies of different densities have been used to compare and evaluate three different methods: the Perez Sky model, the Simplified Radiosity Algorithm and a new scene tiling method implemented in our urban simulation platform SimStadt, used for feasible estimations on a large scale. To quantify the influence of shading, the new concept of Urban Shading Ratio has been introduced and used for this evaluation process. In high density urban areas, this index may reach 60% for facades and 25% for roofs. Tiles of 500m width and 200m overlap are a minimum requirement in this case to compute solar irradiance with an acceptable accuracy. In medium density areas, tiles of 300m width and 100m overlap meet perfectly the accuracy requirements. In addition, the solar potential for various solar energy thresholds as well as the monthly variation of the Urban Shading Ratio have been quantified for both case studies, distinguishing between roofs and facades of different orientations.</abstract><cop>New York</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.solener.2017.09.017</doi><tpages>15</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy Case studies Cities Computer applications Computer memory Computer simulation Computing time Concrete Energy modeling Facades Irradiance Radiation Radiation models Radiosity Roofs Shading Solar energy Solar potential Tiles Tiling Tiling strategies Urban areas Urban shading ratio |
title | Setting intelligent city tiling strategies for urban shading simulations |
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