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Evaluating the potential of coupling the sunlight beam index with lumped parameter modelling in low energy building design

Evaluating the potential of coupling the sunlight beam index with lumped parameter modelling in low energy building design
评估低能耗建筑设计中阳光光束指数与集总参数建模耦合的潜力
批准号:
1809400
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2016
资助国家:
英国
项目状态:
已结题
起止时间:
2016 至 --

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中文摘要
翻译
建筑部门占总能耗的30%以上(Perez等人,2008年)。玻璃窗和相关的太阳热增益极大地影响建筑物的能量消耗,特别是在由于气候变化的影响而导致的较温暖的气候条件下(Berger等人,2014; Hopfe和McLeod,2015)。特别是在低能耗建筑设计概念(例如被动式住宅)中,窗户在确保热舒适性方面发挥着重要作用(Hopfe和McLeod,2015)。一般来说,通过玻璃围护结构进入的太阳辐射是决定总冷负荷和居住者热舒适度的主要因素。然而,由于其瞬态和动态性质,不容易准确地估计这种效应(Evola等人,2015年)。目的本研究的目的是探讨目前稳态和动态方法计算日照的准确性。此外,通过将SBI与集总参数建模相结合,研究将评估SBI在准确表示空间中的太阳能增益方面的贡献,并提出可纳入当前方法的更详细程序(例如被动式住宅)和未来的欧盟/CEN准则和立法。ObjectivesThe研究项目的目标是:分析当前稳态和动态建筑性能模拟方法中使用的建模和估计太阳照射的方法。生成模型,以评估使用上述模拟方法计算阳光可达性的准确性。使用集总参数建模方法,以便在使用SBI方法计算的阳光照射与太阳热增益之间建立联系。调查SBI与集总参数建模方法相结合的有效性和准确性。检查SBI方法的整体性能和有效性,并建立一个模板,该模板可以集成到当前/未来的立法中,关于玻璃窗对低能耗建筑设计的影响。参考资料Berger T.,阿曼·C福尔迈尔·H Korjenic A.,波斯皮查尔B.,Neururer C.,斯穆特尼河,2014.城市位置和气候变化对奥地利维也纳办公楼能源需求的影响,建筑与环境81(2014),258- 269 Evola G.玛莱塔湖,2015.太阳能响应系数用于计算太阳能增益引起的冷负荷。应用能源160,2015,431- 441. Hopfe,CJ.,McLeod,RS,2015.被动式住宅设计师手册,凯文·J·克尔彻,张凯麦克斯2015年RC网络建模中集总电容近似精度的研究。能源与建筑108,2015,454- 462. Mardaljevic J.,罗伊·N 2016.阳光指数。Lighting Res. Technol. Vol. 48,2016,55-69.Perez-Lombard L.,奥尔蒂斯·J Pout C. 2008.建筑能耗信息综述,能源建设。40(2008),394-398.
英文摘要
The building sector is responsible for more than 30% of the total energy consumption (Perez et al., 2008). Glazing and the associated solar heat gains greatly affect a building's energy consumption, particularly under the warmer climatic conditions due to the effects of climate change (Berger et al., 2014; Hopfe and McLeod, 2015). Particularly in low energy building design concepts (e.g Passivhaus), the windows play a major role in ensuring thermal comfort (Hopfe and McLeod, 2015). The solar radiation admitted through the glazed envelope is a major factor in determining the total cooling load and thermal comfort of the occupants in general. However, it is not easy to estimate accurately this effect due to its transient and dynamic nature (Evola et al.,2015). AimsThe aim of the research project is to explore the accuracy of calculating sunlight exposure in current steady-state and dynamic methodologies. Furthermore, with the combination of the SBI and lumped parameter modelling, the research study is going to assess the contribution of the SBI in representing accurately the solar gains in a space and propose a more detailed procedure that could be incorporated into current methodologies (e.g. Passivhaus) and future EU/CEN guidelines and legislations.ObjectivesThe objectives of the research project are:Analysis of the methodology of modelling and estimating the solar exposure used in current steady-state and dynamic building performance simulation methods.Generation of a model in order to assess the accuracy of calculating sunlight accessibility using the aforementioned simulation methods. Use of the lumped parameter modelling methodology in order to establish a link between sunlight exposure, calculated using the SBI method, and solar heat gains. Investigation of the effectiveness and accuracy of coupling the SBI with the lumped parameter modelling methodology.Examination of the overall performance and effectiveness of the SBI methodology and establishment of a template that could be integrated into current/future legislations, regarding the effect of glazing on low energy building design.ReferencesBerger T., Amann C., Formayer H., Korjenic A., Pospichal B., Neururer C., Smutny R., 2014. Impacts of urban location and climate change upon energy demand of office buildings in Vienna, Austria, Building and Environment 81 (2014), 258-269Evola G. Marletta L., 2015. The Solar Response Factor to calculate the cooling load induced by solar gains. Applied Energy 160, 2015, 431-441.Hopfe, CJ., McLeod, RS, 2015. The Passivhaus Designers Manual, RoutledeKircher Kevin J., Zhang K. Max, 2015. On the lumped capacitance approximation accuracy in RC network building models. Energy and Buildings 108, 2015, 454-462.Mardaljevic J., Roy N., 2016. The sunlight beam index. Lighting Res. Technol. Vol. 48, 2016, 55-69.Perez-Lombard L., Ortiz J., Pout C., 2008. A review on buildings energy consumption information, Energy Build. 40 (2008), 394-398.
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