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Article: Benchmarking the building energy consumption and solar energy trade-offs of residential neighborhoods on Chongming Eco-Island, China

TitleBenchmarking the building energy consumption and solar energy trade-offs of residential neighborhoods on Chongming Eco-Island, China
Authors
KeywordsResidential neighborhood types
Optimization
Photovoltaic energy
Energy trade-off
Issue Date2016
Citation
Applied Energy, 2016, v. 180, p. 792-799 How to Cite?
AbstractThis paper explores the effects of residential neighborhood types on building energy consumption and solar energy trade-offs with the goal of developing an operational methodology to achieve the best conditions towards a zero nonrenewable energy neighborhood. Six typical Chongming neighborhood types are identified, termed the Farmhouse, Linear-village, Nucleated-village, Townhouse, Slab and High-rise types with the effects of increased installation of solar energy panels estimated by Monte Carlo simulation. To achieve a more comprehensive view of cost-effective opportunities to improve the performance of buildings at the neighborhood scale, we use actual energy use data obtained from both the survey and electricity bills’ analysis to show that considerable variations exist due to hitherto unrecorded socioeconomic factors relating to the type of occupants involved. By concluding that the associated variables are interdependent, the paper continues with an empirical study in which the solar energy potential of each neighborhood is quantified to show that, in the case of Chongming, the Nucleated-village and Slab neighborhood types have the greatest retrofitting potential. These investigations into energy trade-offs with existing retrofitting and construction technologies therefore provide a metric for other eco-cities to use as a tool for future policy guidance.
Persistent Identifierhttp://hdl.handle.net/10722/301801
ISSN
2020 Impact Factor: 9.746
2020 SCImago Journal Rankings: 3.035

 

DC FieldValueLanguage
dc.contributor.authorYang, Tianren-
dc.contributor.authorZhang, Xiaoling-
dc.date.accessioned2021-08-19T02:20:46Z-
dc.date.available2021-08-19T02:20:46Z-
dc.date.issued2016-
dc.identifier.citationApplied Energy, 2016, v. 180, p. 792-799-
dc.identifier.issn0306-2619-
dc.identifier.urihttp://hdl.handle.net/10722/301801-
dc.description.abstractThis paper explores the effects of residential neighborhood types on building energy consumption and solar energy trade-offs with the goal of developing an operational methodology to achieve the best conditions towards a zero nonrenewable energy neighborhood. Six typical Chongming neighborhood types are identified, termed the Farmhouse, Linear-village, Nucleated-village, Townhouse, Slab and High-rise types with the effects of increased installation of solar energy panels estimated by Monte Carlo simulation. To achieve a more comprehensive view of cost-effective opportunities to improve the performance of buildings at the neighborhood scale, we use actual energy use data obtained from both the survey and electricity bills’ analysis to show that considerable variations exist due to hitherto unrecorded socioeconomic factors relating to the type of occupants involved. By concluding that the associated variables are interdependent, the paper continues with an empirical study in which the solar energy potential of each neighborhood is quantified to show that, in the case of Chongming, the Nucleated-village and Slab neighborhood types have the greatest retrofitting potential. These investigations into energy trade-offs with existing retrofitting and construction technologies therefore provide a metric for other eco-cities to use as a tool for future policy guidance.-
dc.languageeng-
dc.relation.ispartofApplied Energy-
dc.subjectResidential neighborhood types-
dc.subjectOptimization-
dc.subjectPhotovoltaic energy-
dc.subjectEnergy trade-off-
dc.titleBenchmarking the building energy consumption and solar energy trade-offs of residential neighborhoods on Chongming Eco-Island, China-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.apenergy.2016.08.039-
dc.identifier.scopuseid_2-s2.0-84981503291-
dc.identifier.volume180-
dc.identifier.spage792-
dc.identifier.epage799-

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