...
首页> 外文期刊>Building Simulation >A method of determining typical meteorological year for evaluating overheating performance of passive buildings
【24h】

A method of determining typical meteorological year for evaluating overheating performance of passive buildings

机译:一种确定被动式建筑过热性能的典型气象年份的方法

获取原文
获取原文并翻译 | 示例
           

摘要

In the simulation of building overheating risks, the use of typical meteorological years (TMY) can greatly reduce the simulation workload and accurately reflect the distribution of simulation results according to the weather conditions over a given period. However, all meteorological parameters in most current TMY methods use a uniform weighting factor which may make the simulation results against the actual simulation results of the period and negatively affect the accuracy of the evaluation results. In addition to differences in climate characteristics between climate zones, the sensitivity of different simulation results to external parameters will also be different. Therefore, a TMY method based on the Finkelstein-Schafer statistical method is proposed, which considers the climatic characteristics of different regions and the correlation with the output parameters of indoor simulation to select the typical month. The proposed method is demonstrated in the three future scenarios for the three cities in different climate zones in China. The results show that the traditional TMY method has an overestimated weight of solar radiation and wind speed and an undervalued weight of dry bulb temperature when indoor temperature-related indicators are the output target. Compared with the traditional TMY method, the TMY generated by the improved method is closer to the distribution characteristics of the long-term outdoor weather data. Furthermore, when using the improved TMY data to evaluate the overheating performance of the passive residential buildings, the difference of the results of the unmet degree hours, indoor overheating degree, and the overheating escalation factor between the long-term projected data and the TMY data can be reduced by 63-67 compared with the traditional TMY data.
机译:在建筑过热风险模拟中,采用典型气象年(TMY)可以大大减少模拟工作量,并根据给定时期的天气情况准确反映模拟结果的分布情况。然而,目前大多数TMY方法中的所有气象参数都使用统一的加权因子,这可能会使模拟结果与该时期的实际模拟结果相悖,并对评估结果的准确性产生负面影响。除了气候带间气候特征的差异外,不同模拟结果对外部参数的敏感性也会有所不同。因此,该文提出一种基于Finkelstein-Schafer统计方法的TMY方法,该方法考虑了不同区域的气候特征以及与室内模拟输出参数的相关性来选择典型月份。该方法在中国不同气候区3个城市的3种未来情景中得到了证明。结果表明:以室内温度相关指标为输出目标时,传统TMY方法高估了太阳辐射和风速的权重,低估了干球温度的权重;与传统的TMY方法相比,改进方法生成的TMY更接近长期室外天气数据的分布特征。此外,当使用改进的TMY数据评估被动式住宅建筑的过热性能时,与传统的TMY数据相比,长期预测数据与TMY数据之间的未满足度小时数、室内过热度和过热升级系数的结果差异可以降低63%-67%。

著录项

相似文献

  • 外文文献
  • 中文文献
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号