建筑能耗模拟典型年中气象参数权重的确定

发布时间：2018-06-16 16:31

本文选题：典型气象年 + 权重因子　；参考：《土木建筑与环境工程》2015年01期

【摘要】：在建筑能耗模拟用典型年的生成中,传统的Finkelstein-Schafer统计方法对气象参数赋予了固定的权重因子,但有关研究表明,由于地域间气象资源不同,气象参数权重因子的固化有待商榷。针对挑选典型年时气象参数权重因子统一与否对典型年挑选结果和建筑能耗模拟准确性的影响问题,选同一建筑热工分区中寒冷地区的代表城市北京和拉萨,分别使用FS方法和主成分法进行了典型年的挑选,并对典型公共建筑建模进行了能耗模拟分析。结果表明:FS统计方法适于表征单独气象参数的长期相似性,但存在对太阳辐射参数权重赋予过大的问题,适用于太阳能丰富地区;而主成分法适合寻求当地气象资源的本质特征,使用主成分法时对气象参数的选择尤为重要。
[Abstract]:The traditional Finkelstein-Schafer statistical method has given a fixed weight factor to meteorological parameters in the generation of typical years for building energy consumption simulation. However, the relevant studies show that the solidification of meteorological parameters weight factors remains to be discussed due to the difference of meteorological resources between regions. Aiming at the influence of the unity of meteorological parameter weight factor on the result of typical year selection and the accuracy of building energy consumption simulation, the representative cities of Beijing and Lhasa in the cold area of the same building thermal zone are selected. FS method and principal component method are used to select typical years, and the energy consumption simulation analysis of typical public buildings is carried out. The results show that the ratio FS statistical method is suitable to characterize the long-term similarity of individual meteorological parameters, but there is a problem that the weight of solar radiation parameters is too large, which is suitable for solar energy rich areas. The principal component method is suitable for seeking the essential characteristics of the local meteorological resources, and the selection of meteorological parameters is particularly important when using the principal component method.
【作者单位】：西安建筑科技大学信息与控制工程学院;西安建筑科技大学建筑学院;
【基金】：陕西省重点科技创新团队项目(2012KCT-11) 国家自然科学基金(51108366)~~
【分类号】：TU111.195

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