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A method to account for the urban microclimate on the creation of 'typical weather year' datasets for building energy simulation, using stochastically generated data

机译:一种使用随机生成的数据在创建“典型天气年”数据集以进行建筑能耗模拟时考虑城市小气候的方法

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摘要

Predicting buildings' heating and cooling needs through dynamic simulation methods requires the input of hourly weather data, so as to represent the typical meteorological characteristics of a specific location. Hence, the so called 'typical weather years' (TWY), mainly deduced from multi-year records of meteorological stations outside the urban centres, cannot account of the complex interactions between solar radiation, wind speed and high urban densities which lead to the formation of the urban heat island effect and to higher ambient air temperatures. As the assumption that climatic parameters at a reference location of a meteo station are similar for a densely built up area can lead to miscalculations of the heating and cooling needs, the aim of this study is to present a computational method for assessing the urban climate's effect during the generation of typical weather data for dynamic energy calculations. In this vein, a typical 'urban specific weather dataset' (USWD), reflecting the microclimatic conditions in front of a building unit inside an urban district in the city of Thessaloniki, Greece is created based on microclimate simulations with the Envi-met model; it is then compared with a typical reference weather dataset (RWD), representing climatic conditions at a reference location of a meteo station. The results indicate that the proposed method can capture microclimate characteristics; higher dry bulb temperatures were reported during the year inside the urban canyon, compared to the corresponding values at the reference location, with indicative mean daily deviations up to 1.0 degrees C and 0.75 degrees C in February and July respectively. Wind speed, near the building facade is generally found lower than the corresponding values at the reference location, due to wind sheltering by neighbouring constructions. Given that climatic parameters strongly influence the output of energy simulations the proposed computational method provide a contribution for higher accuracy of building energy simulation in the urban context. Future work will involve energy performance simulations of a typical building unit with the generated USWD file so as to evaluate the urban climate's influence on energy needs. (C) 2018 Elsevier B.V. All rights reserved.
机译:通过动态模拟方法预测建筑物的供暖和制冷需求需要输入每小时的天气数据,以表示特定位置的典型气象特征。因此,所谓的“典型天气年”(TWY)主要是由城市中心以外的气象站的多年记录得出的,不能解释太阳辐射,风速和高城市密度之间的复杂相互作用,从而导致形成城市热岛效应和更高的环境空气温度的影响。假设在一个人口稠密的地区,气象站的参考位置的气候参数相似,可能会导致对供热和制冷需求的计算错误,因此本研究的目的是提出一种评估城市气候影响的计算方法在生成用于动态能量计算的典型天气数据期间。在这种情况下,基于Envi-met模型的微气候模拟,创建了一个典型的“城市特定天气数据集”(USWD),该数据反映了希腊塞萨洛尼基市区内建筑单元前方的微气候条件。然后将其与代表气象站参考地点的气候条件的典型参考天气数据集(RWD)进行比较。结果表明,该方法可以捕获微气候特征。与参考位置的相应值相比,一年中城市峡谷内的干球温度更高,2月和7月的指示平均日偏差分别高达1.0摄氏度和0.75摄氏度。通常会发现建筑物立面附近的风速低于参考位置的相应值,这是由于相邻建筑物遮挡了风。考虑到气候参数强烈影响能源模拟的输出,所提出的计算方法为城市环境下建筑能源模拟的更高准确性做出了贡献。未来的工作将包括使用生成的USWD文件对典型建筑单元进行能源性能模拟,以评估城市气候对能源需求的影响。 (C)2018 Elsevier B.V.保留所有权利。

著录项

  • 来源
    《Energy and Buildings》 |2018年第4期|270-283|共14页
  • 作者单位

    Aristotle Univ Thessaloniki, Fac Civil Engn, Lab Bldg Construct & Bldg Phys, Thessaloniki, Greece;

    Aristotle Univ Thessaloniki, Sch Geol, Dept Meteorol & Climatol, Thessaloniki, Greece;

    Aristotle Univ Thessaloniki, Fac Civil Engn, Lab Bldg Construct & Bldg Phys, Thessaloniki, Greece;

    Aristotle Univ Thessaloniki, Fac Civil Engn, Lab Bldg Construct & Bldg Phys, Thessaloniki, Greece;

    Aristotle Univ Thessaloniki, Fac Civil Engn, Lab Bldg Construct & Bldg Phys, Thessaloniki, Greece;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Typical weather years; Representative days; Microclimate simulation; Envi-met;

    机译:典型天气年;代表天;微气候模拟;环境;

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