Modelling the effect of BIPV window in the built environment: Uncertainty and sensitivity
BIPV (building-integrated photovoltaic) window has been proven as a promising technology to increase renewable energy and reduce environmental effects of the building. The effect of BIPV window in the built environment could change significantly with the window configuration, building materials, and...
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description | BIPV (building-integrated photovoltaic) window has been proven as a promising technology to increase renewable energy and reduce environmental effects of the building. The effect of BIPV window in the built environment could change significantly with the window configuration, building materials, and urban landscape, which have a large variability within cities. In this study, we adopted a newly developed building energy model coupled with a single-layer urban canopy model (BEM-SLUCM) to characterize the uncertainties of BIPV window effect at the neighbourhood scale in a hot desert climate city, Phoenix, USA. Using an advanced Markov chain Monte Carlo algorithm, extensive simulations were conducted to quantify the sensitivity of extreme outdoor microclimate, building cooling load and renewable energy generation to various input parameters. Results show that the canyon aspect ratio, window coverage, and power generation efficiency are pivotal to maximize the electricity generation by BIPV window. Canyon air temperature and building cooling load are highly sensitive to momentum roughness length above canyon, thickness of building envelope, air conditioning setpoint temperature, and canyon aspect ratio. This indicates a strong dynamic interaction between building's indoor space and the surrounding canyon environment. In contrast, thermal and optical properties of BIPV window have negligible effects on the urban thermal environment. Findings in this study reveal key mechanisms that regulate the urban microclimate and building energy consumption, provide guidance for BIPV applications in the built environment, and shed new lights on the sustainable design of urban neighbourhoods.
•Uncertainty of the BIPV window effect is investigated through extensive simulations.•Large BIPV window coverage helps mitigate nocturnal urban heat island.•Optical and thermal properties of BIPV window have negligible influences.•Canyon heat dissipation is the key process for regulating extreme thermal condition. |
doi_str_mv | 10.1016/j.buildenv.2021.108605 |
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•Uncertainty of the BIPV window effect is investigated through extensive simulations.•Large BIPV window coverage helps mitigate nocturnal urban heat island.•Optical and thermal properties of BIPV window have negligible influences.•Canyon heat dissipation is the key process for regulating extreme thermal condition.</description><identifier>ISSN: 0360-1323</identifier><identifier>EISSN: 1873-684X</identifier><identifier>DOI: 10.1016/j.buildenv.2021.108605</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Air conditioning ; Air temperature ; Algorithms ; Arid climates ; Aspect ratio ; BIPV window ; Building energy efficiency ; Building envelopes ; Building materials ; Built environment ; Canyons ; Construction materials ; Cooling ; Cooling loads ; Cooling systems ; Electrical loads ; Energy consumption ; Environmental effects ; Indoor environments ; Markov chains ; Microclimate ; Optical properties ; Photovoltaic cells ; Photovoltaics ; Power generation ; Renewable energy ; Renewable resources ; Sensitivity ; Sustainable design ; Thermal environments ; Uncertainty ; Urban environments ; Urban heat island</subject><ispartof>Building and environment, 2022-01, Vol.208, p.108605, Article 108605</ispartof><rights>2021 Elsevier Ltd</rights><rights>Copyright Elsevier BV Jan 15, 2022</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c340t-a5899d1c70d07fdb35389c3bd6443418aa7c3966e79461e3f3d5a446a99eb7573</citedby><cites>FETCH-LOGICAL-c340t-a5899d1c70d07fdb35389c3bd6443418aa7c3966e79461e3f3d5a446a99eb7573</cites><orcidid>0000-0002-3890-5628 ; 0000-0002-0057-2637</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.buildenv.2021.108605$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>315,781,785,3551,27929,27930,46000</link.rule.ids></links><search><creatorcontrib>Chen, Liutao</creatorcontrib><creatorcontrib>Yang, Jiachuan</creatorcontrib><creatorcontrib>Li, Peiyuan</creatorcontrib><title>Modelling the effect of BIPV window in the built environment: Uncertainty and sensitivity</title><title>Building and environment</title><description>BIPV (building-integrated photovoltaic) window has been proven as a promising technology to increase renewable energy and reduce environmental effects of the building. The effect of BIPV window in the built environment could change significantly with the window configuration, building materials, and urban landscape, which have a large variability within cities. In this study, we adopted a newly developed building energy model coupled with a single-layer urban canopy model (BEM-SLUCM) to characterize the uncertainties of BIPV window effect at the neighbourhood scale in a hot desert climate city, Phoenix, USA. Using an advanced Markov chain Monte Carlo algorithm, extensive simulations were conducted to quantify the sensitivity of extreme outdoor microclimate, building cooling load and renewable energy generation to various input parameters. Results show that the canyon aspect ratio, window coverage, and power generation efficiency are pivotal to maximize the electricity generation by BIPV window. Canyon air temperature and building cooling load are highly sensitive to momentum roughness length above canyon, thickness of building envelope, air conditioning setpoint temperature, and canyon aspect ratio. This indicates a strong dynamic interaction between building's indoor space and the surrounding canyon environment. In contrast, thermal and optical properties of BIPV window have negligible effects on the urban thermal environment. Findings in this study reveal key mechanisms that regulate the urban microclimate and building energy consumption, provide guidance for BIPV applications in the built environment, and shed new lights on the sustainable design of urban neighbourhoods.
•Uncertainty of the BIPV window effect is investigated through extensive simulations.•Large BIPV window coverage helps mitigate nocturnal urban heat island.•Optical and thermal properties of BIPV window have negligible influences.•Canyon heat dissipation is the key process for regulating extreme thermal condition.</description><subject>Air conditioning</subject><subject>Air temperature</subject><subject>Algorithms</subject><subject>Arid climates</subject><subject>Aspect ratio</subject><subject>BIPV window</subject><subject>Building energy efficiency</subject><subject>Building envelopes</subject><subject>Building materials</subject><subject>Built environment</subject><subject>Canyons</subject><subject>Construction materials</subject><subject>Cooling</subject><subject>Cooling loads</subject><subject>Cooling systems</subject><subject>Electrical loads</subject><subject>Energy consumption</subject><subject>Environmental effects</subject><subject>Indoor environments</subject><subject>Markov chains</subject><subject>Microclimate</subject><subject>Optical properties</subject><subject>Photovoltaic cells</subject><subject>Photovoltaics</subject><subject>Power generation</subject><subject>Renewable energy</subject><subject>Renewable resources</subject><subject>Sensitivity</subject><subject>Sustainable design</subject><subject>Thermal environments</subject><subject>Uncertainty</subject><subject>Urban environments</subject><subject>Urban heat island</subject><issn>0360-1323</issn><issn>1873-684X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNqFkEtPwzAQhC0EEqXwF5Alzil27DgxJx7iUakIDhTByXLjDThKnWK7rfrvcSmcOa20O7Oj-RA6pWRECRXn7Wi2tJ0BtxrlJKdpWQlS7KEBrUqWiYq_7aMBYYJklOXsEB2F0JJklIwP0Ptjb6DrrPvA8RMwNA3UEfcNvh4_v-K1daZfY-t-jtuYiFOO9b2bg4sXeOpq8FFbFzdYO4MDuGCjXdm4OUYHje4CnPzOIZre3b7cPGSTp_vxzdUkqxknMdNFJaWhdUkMKRszYwWrZM1mRnDOOK20LmsmhYBSckGBNcwUmnOhpYRZWZRsiM52fxe-_1pCiKrtl96lSJULVuUyJ5Illdipat-H4KFRC2_n2m8UJWqLUbXqD6PaYlQ7jMl4uTNC6rCy4FWoLaTaxvqESpne_vfiGx7Yfs4</recordid><startdate>20220115</startdate><enddate>20220115</enddate><creator>Chen, Liutao</creator><creator>Yang, Jiachuan</creator><creator>Li, Peiyuan</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>KR7</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0002-3890-5628</orcidid><orcidid>https://orcid.org/0000-0002-0057-2637</orcidid></search><sort><creationdate>20220115</creationdate><title>Modelling the effect of BIPV window in the built environment: Uncertainty and sensitivity</title><author>Chen, Liutao ; Yang, Jiachuan ; Li, Peiyuan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c340t-a5899d1c70d07fdb35389c3bd6443418aa7c3966e79461e3f3d5a446a99eb7573</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Air conditioning</topic><topic>Air temperature</topic><topic>Algorithms</topic><topic>Arid climates</topic><topic>Aspect ratio</topic><topic>BIPV window</topic><topic>Building energy efficiency</topic><topic>Building envelopes</topic><topic>Building materials</topic><topic>Built environment</topic><topic>Canyons</topic><topic>Construction materials</topic><topic>Cooling</topic><topic>Cooling loads</topic><topic>Cooling systems</topic><topic>Electrical loads</topic><topic>Energy consumption</topic><topic>Environmental effects</topic><topic>Indoor environments</topic><topic>Markov chains</topic><topic>Microclimate</topic><topic>Optical properties</topic><topic>Photovoltaic cells</topic><topic>Photovoltaics</topic><topic>Power generation</topic><topic>Renewable energy</topic><topic>Renewable resources</topic><topic>Sensitivity</topic><topic>Sustainable design</topic><topic>Thermal environments</topic><topic>Uncertainty</topic><topic>Urban environments</topic><topic>Urban heat island</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Liutao</creatorcontrib><creatorcontrib>Yang, Jiachuan</creatorcontrib><creatorcontrib>Li, Peiyuan</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Environment Abstracts</collection><jtitle>Building and environment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Liutao</au><au>Yang, Jiachuan</au><au>Li, Peiyuan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modelling the effect of BIPV window in the built environment: Uncertainty and sensitivity</atitle><jtitle>Building and environment</jtitle><date>2022-01-15</date><risdate>2022</risdate><volume>208</volume><spage>108605</spage><pages>108605-</pages><artnum>108605</artnum><issn>0360-1323</issn><eissn>1873-684X</eissn><abstract>BIPV (building-integrated photovoltaic) window has been proven as a promising technology to increase renewable energy and reduce environmental effects of the building. The effect of BIPV window in the built environment could change significantly with the window configuration, building materials, and urban landscape, which have a large variability within cities. In this study, we adopted a newly developed building energy model coupled with a single-layer urban canopy model (BEM-SLUCM) to characterize the uncertainties of BIPV window effect at the neighbourhood scale in a hot desert climate city, Phoenix, USA. Using an advanced Markov chain Monte Carlo algorithm, extensive simulations were conducted to quantify the sensitivity of extreme outdoor microclimate, building cooling load and renewable energy generation to various input parameters. Results show that the canyon aspect ratio, window coverage, and power generation efficiency are pivotal to maximize the electricity generation by BIPV window. Canyon air temperature and building cooling load are highly sensitive to momentum roughness length above canyon, thickness of building envelope, air conditioning setpoint temperature, and canyon aspect ratio. This indicates a strong dynamic interaction between building's indoor space and the surrounding canyon environment. In contrast, thermal and optical properties of BIPV window have negligible effects on the urban thermal environment. Findings in this study reveal key mechanisms that regulate the urban microclimate and building energy consumption, provide guidance for BIPV applications in the built environment, and shed new lights on the sustainable design of urban neighbourhoods.
•Uncertainty of the BIPV window effect is investigated through extensive simulations.•Large BIPV window coverage helps mitigate nocturnal urban heat island.•Optical and thermal properties of BIPV window have negligible influences.•Canyon heat dissipation is the key process for regulating extreme thermal condition.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.buildenv.2021.108605</doi><orcidid>https://orcid.org/0000-0002-3890-5628</orcidid><orcidid>https://orcid.org/0000-0002-0057-2637</orcidid></addata></record> |
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subjects | Air conditioning Air temperature Algorithms Arid climates Aspect ratio BIPV window Building energy efficiency Building envelopes Building materials Built environment Canyons Construction materials Cooling Cooling loads Cooling systems Electrical loads Energy consumption Environmental effects Indoor environments Markov chains Microclimate Optical properties Photovoltaic cells Photovoltaics Power generation Renewable energy Renewable resources Sensitivity Sustainable design Thermal environments Uncertainty Urban environments Urban heat island |
title | Modelling the effect of BIPV window in the built environment: Uncertainty and sensitivity |
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