基于GPD的夏季空调室外计算温度确定方法

发布时间：2018-03-23 04:39

  本文选题：空调室外计算温度　切入点：广义帕累托分布　出处：《天津大学学报(自然科学与工程技术版)》2017年07期 　论文类型：期刊论文

【摘要】：为以概率方式确定空调室外计算温度,提出用广义帕累托分布(GPD)描述室外空气湿球和干球极端高温数据概率分布的方法.以天津市30年气象数据为基础,建立了极端高温数据的GPD模型,以此确定了历年平均不保证50,h的空调室外计算温度.从数据采集频率、气候变化和地域气候类型适用性3个角度验证了GPD方法的适用性.结果表明:GPD密度曲线与经验分布曲线吻合度较高,对天津市而言,GPD法确定的空调室外计算温度与"规范法"差值不大于0.1,℃;GPD法对气象数据采集频率不敏感,分别以逐时和定时数据为统计基础确定的室外计算温度相差最大的是干球温度,差值为0.1,℃;此外,GPD法可以准确反映气候变暖带来的室外计算温度变化,并且对不同地区不同特征的气候也具有良好的适应性.综上,GPD法可以用于空调室外计算温度的统计确定.
[Abstract]:In order to determine the outdoor calculated temperature of air conditioning by probability method, a method of describing the extreme high temperature data of outdoor air wet bulb and dry ball by generalized Pareto distribution (GPDD) is proposed. Based on the 30 years meteorological data of Tianjin, The GPD model of extreme high temperature data is established to determine the outdoor calculation temperature of air conditioning, which is not guaranteed for 50 h on average, and the frequency of data acquisition is obtained from the data collection frequency. The applicability of the GPD method is verified from three aspects of climate change and applicability of regional climate types. The results show that the density curve of GPD is in good agreement with the empirical distribution curve. For Tianjin City, the difference between the outdoor calculation temperature determined by the GPD method and the "Standard method" is not greater than 0.1, and the temperature GPD method is not sensitive to the frequency of meteorological data collection. The difference between the calculated outdoor temperatures based on hourly and timing data is 0.1 鈩，

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