An Improved Method for Generating Typical Meteorological Years Used in Building Energy Simulation in China

The present study proposes an improved method for generating better typical meteorological years( TMYs) used in building energy simulation in China. Modifications are made to the commonly used Sandia method,by optimizing the weightings of indices and thus giving more emphasis to dry bulb temperature and relative humidity and less to wind velocity. After analyzing the solar heat gain on the vertical envelop,an index of diffuse radiation rather than direct normal radiation is added for solar radiation. Using the improved method proposed,TMYs for 5 representative cities of 5 major climate zones in China are generated from the meteorological data recorded during the period 1981—2010. The results show that,compared with previous studies,the monthly diffuse solar radiation of typical meteorological months generated by the improved method are the"closest"to the 30-year average,and the comparison between annual diffuse radiation for the TMY and the 30-year annual average is improved,while little adverse effect is produced on global horizontal radiation comparisons,indicating that the improved method is more suitable to generate the TMY data than previous studies.

The Generation of Typical Meteorological Year and Climatic Database of Turkey for the Energy Analysis of Buildings

For sustainable development, a reduction in energy demand is essential. This could be achieved through improving energy efficiency, effective energy conservation and management. The weather conditions of a given region are the most important consideration for the proper design of space AC （Air Conditioning） systems. In this study, the typical meteorological year and climatic database of Turkey for the energy analysis of buildings were generated by SQL （Structured Query Language） database programmimg language. The Finkelstein-Schafer statistical method was applied to analyze the hourly measured weather data of a 23-year period （1989-2012） and select representative TMMs （Typical Meteorological Months）. The selection criteria were based on 13 meteorological parameters. These parameters are the daily mean, maximum and minimum values and ranges of temperature, dew-point and wind velocity and the daily values of global solar radiation. According to results of TMY （Typical Meteorological Year）, climatic database of Turkey including daily or hourly climate variables was created in SQL data tables.

基于气候资源禀赋的TMY权重因子调整方法研究

提出一种基于气候资源禀赋的典型气象年(TMY)权重因子调整方法。在参数间相关分析的基础上,遴选干球温度、相对湿度、日照时数与气温日较差作为分区指标,采用K-均值聚类算法对中国地域气候进行分区,依据台站所处地域的太阳能、风能等资源动态调整TMY权重因子。结果显示,调整后的权重因子构建的TMY更加精准,更能体现地域的气候特征。

A global typical meteorological year(TMY)database on ERA5 dataset

The outdoor climate condition is one of the deterministic factors influencing building energy consumption.Building performance simulation(BPS)tools usually adopt typical meteorological year(TMY)as the outdoor climate input.Despite that many scholars and institutes have developed TMY datasets,these datasets are usually based on distinct data sources and methods.Considering the increase of international cooperation construction projects,compatible TMY dataset for different countries is in urgent need.This paper presents a global typical meteorological year(TMY)database covering 38,947 stations worldwide based on the fifth-generation atmospheric reanalysis product released by the European Center(ERA5).The data is created with Chinese Standard Weather Database(CSWD)method to reflect the average level of historical weather.The dataset is saved in a 55 GB database of compressed CSV files and a website is established where users can download their required TMY data for certain cities according to the longitude and latitude information.A systematic validation is conducted to confirm the feasibility of ERA5 as data source and validity of generated TMY data.This TMY-ERA5 dataset is fundamental and essential in building system designs of international construction projects,building performance simulation,especially for some countries lacking ground meteorological stations or missing meteorological year data in the building sector.It can be used as references for other meteorological climate studies.

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

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.

Effect of typical meteorological year selection on integrated daylight modeling and building energy simulation

The complete description of outdoor luminous and thermal environment is the basis for daylight utilization design with simulation tools.Nevertheless,Typical Meteorological Year(TMY)and generation method specifically developed for the energy simulation of daylight-utilized buildings is still unavailable currently.Luminous environment parameters have not been taken into consideration in existing TMY generation methods.In this study,the feasibility of existing TMY generation process has been examined.A generic office model implementing sided window daylighting is established.Historical meteorological data of Hong Kong region from 1979 to 2007 have been collected and three existing weighting schemes are applied during the Typical Meteorological Month(TMM)selection procedures.Three TMY files for Hong Kong are generated and used to conduct integrated Climate-Based Daylight Modeling and building energy simulation.The result demonstrates that,on annual basis,the energy consumption results obtained from the generated TMY files are in good agreements with the long-term mean annual value.The maximum deviation of annual energy consumptions for the generated TMY files is only 1.8%.However,further analysis on monthly basis shows that all the three generated TMY files fail to fully represent the long-term monthly mean level.The maximum deviation of monthly energy consumptions for the generated TMY files can reach up to 11%.As the energy performance daylight utilization is subject to weather change,analysis on daily and monthly energy level is important,especially during design stage.The deficiency of existing TMM selection process and TMY generation method indicates the necessity to develop a corresponding typical weather data input with finer resolution for the energy simulation of daylight-related buildings.

高层建筑典型气象年数据竖直修正方法研究

进行建筑能耗评估应考虑气象数据在竖直方向上的变化,目前的典型气象年(TMY)数据是基于地面观测数据获得的,无法很好地满足高层建筑的设计需求。本文基于上海宝山站的探空气象数据,提出了不同高度处TMY数据的修正方法,比较了修正后的TMY数据与实际气象数据的负荷模拟结果。结果表明:修正后的TMY数据的模拟结果与真实数据模拟结果的差异为3.65%~13.42%,且变化趋势一致;相较于地面观测处TMY数据的模拟结果,冷负荷准确度提高了2.37%,热负荷准确度提高了4.06%。

光热电站太阳能典型气象年的气象要素权重取值分析

影响光热电站(CSP)性能的各气象要素主要有水平面总辐射(GHI)、法向直接辐射(DNI)、温度及风速,各气象要素的权重因子赋值不同会导致典型气象年(TMY)结果的差异。本文以西北某地区多年实测辐射数据以及长系列卫星辐射数据为研究基础数据,分别采用Sandia、SolarGIS及CSWD的分析方法,采用随机赋值法,得出我国西北某地区光热电站典型年太阳能资源分析DNI、GHI、风速、温度的权重取值如下:采用Sandia方法时,分别为0.6、0.2、0.1及0.1;采用SolarGIS方法时,分别为0.7、0.1、0.1及0.1;采用CSWD方法时,分别为0.6、0.1、0.2及0.1。本文的研究结果将为太阳能光热电站的高效利用及推广提供一定的借鉴。

基于典型气象年的游泳馆过渡季室外空气含湿量取值方法

游泳馆建筑室内湿负荷大,通风问题备受关注.过渡季室外空气含湿量是通风量计算的基本设计参数,含湿量的取值直接影响了建筑设计的合理性.我国目前使用最广泛的确定过渡季室外计算含湿量的方法是通风曲线法(Ventilation-Curve Method,V-C Method).然而,使用该方法确定的过渡季室外空气含湿量值无法反映不保证小时数,其取值合理性难以评估.提出了一个新的游泳馆过渡季室外空气含湿量取值方法,即典型过渡季法(Typical Transition Season Method,TTS Method).TTS法基于典型气象年(Typical Meteorological Year,TMY)数据挑选过渡季,并以多种不保证小时数计算出室外空气含湿量值,可以很好地表征当地常年气候特征,且能够清楚地反映不保证小时数.研究中选取中国6个典型代表城市,通过计算通风量和换气次数对所选含湿量进行了评估,验证了新方法的合理性.结果表明,TTS法得到的含湿量计算出的通风量更符合设计要求.

辐射数据缺失时TMY与逐时值生成方法分析

为解决太阳辐射数据缺失导致无法准确地进行建筑能耗模拟、建筑节能等相关分析,以西安市为例,研究太阳辐射数据缺失时典型气象年(TMY)挑选与逐时辐射预测。首先,通过相关性分析得出容易获取的日照时数与太阳辐射相关性最高,因此在传统Sandia方法的基础上采用日照时数替代辐射的方法挑选TMY,并对挑选结果进行参数对比分析,验证了新参数挑选出TMY的准确性。其次,通过主要太阳辐射影响参数对比,选择合理的预测输入参数,选用处理泛化问题能力较强的神经网络及其优化算法进行逐时辐射预测研究,并将得到的结果与统计模型和观测数据进行对比分析。最后,参照中国建筑节能设计标准建立办公建筑模型,并利用本研究提出的方法得出的气象数据进行建筑能耗模拟验证,分别分析了建筑采暖与制冷能耗的变化情况。结果表明,提出的TMY挑选方法可以很好地解决辐射数据缺失地区挑选TMY的难题,神经网络算法可以对逐时辐射数据进行较精准的预测,为辐射数据缺失研究建筑节能提供新思路。

太阳能辐射资源计算分析与特性模拟方法

采用太阳辐射理论计算及TRANSYS气象系统进行辐射资源计算和特性模拟。由每月典型日的辐射量推算出地外、水平面、倾斜面的辐射量以及总、直射辐射的月、年总辐射量;分析不同日照百分率下的总辐射量和直射辐射量;利用TRANSYS模拟地外、水平面、倾斜面的总辐射量和直射辐射量的变化情况。计算分析表明:对于鄂尔多斯达拉特旗地区而言,其年总太阳辐射量达9916 MJ/m^(2),倾斜面年总太阳辐射量可达7675 MJ/m^(2)。水平面与倾斜面辐射情况大有差异。该文的计算模拟方法也适用于任何地区的太阳能辐射量计算。

不同能源系统的典型气象年生成方法研究

基于Sandia方法,对北京地区的3种不同能源系统(全空调建筑和2个可再生能源系统),采用随机森林提取特征重要性的方法替代专家判断,定量地分配权重因子,生成适用于不同能源系统的典型气象年(TMY),并利用EnergyPlus进行模拟分析。结果显示:该方法可定量地生成适用于不同能源系统的权重因子集,用于生成相应的TMY。根据不同能源系统的特性,对时间段进行划分并提取对应的权重因子集,可进一步提高TMY的代表性。

建筑极端能耗气象年的建构方法

气候变化日益加剧导致全球变暖、极端事件的频繁发生,极大地影响了建筑能耗.目前,在建筑设计前期,用于建筑能耗模拟的气象参数主要是代表平均状况的典型气象年,无法体现极端天气状况下的建筑耗能情况,因此,生成用于模拟极端天气下建筑能耗的气象年十分必要.对比了几种已有的反映极端天气气象年的优缺点,提出了一种新的用于建筑极端能耗模拟的气象年生成方法,该方法不仅考虑了多种气象参数对建筑耗能的影响,而且使用动态阈值计算多参数的极端强度和出现时长,综合评价各参数超过阈值的时长和强度的得分,生成建筑极端能耗气象年.通过对比不同气象年的建筑能耗模拟结果来验证新方法的优越性.结果显示:采用建筑极端能耗气象年作为室外气象计算参数,对极端天气状况下建筑极值能耗模拟的准确性优于极端气象年、典型冷年及典型热年数据,能够很好模拟出极端天气状况下的建筑能耗.同时,验证了通过组合使用典型气象年和建筑极端能耗气象年数据,可模拟出建筑的平均能耗以及极端天气状况下的极值能耗,组合数据集在不损失模拟结果全面性的前提下减少了模拟次数.

基于典型气象年和制氧可时移负荷的独立微电网容量优化配置

微电网电源容量的优化配置是微电网规划和建设初期的关键步骤。这需要根据建设地点的气象数据、地理位置和负荷需求,在满足经济性和可靠性的前提下,合理地配置微电网的电源容量。本文以高原地区的某独立微电网为研究对象,提出了一种基于典型气象年和制氧可时移负荷的独立微电网电源容量配置优化方法。算法综合考虑了可再生能源装机容量比、供电可靠性和供氧可靠性等多种约束条件,以微电网全寿命周期内年平均成本最小为目标函数,并采用遗传算法求解这个优化配置模型。本文对不同方案下的配置结果进行了分析,验证了所提方法的可行性。该研究为独立微电网的规划和建设提供了参考,有助于实现能源的高效利用和经济性,同时也提高了供电和供氧的可靠性。

住宅建筑南向墙遮阳板尺寸设计及节能潜力分析

在建筑的供暖和空调系统设计中,太阳辐射对供暖和空调负荷有重要的影响.合理遮阳是暖通空调领域节能的一个途径.根据天津地区典型气象年的气象资料,对该地区住宅建筑南向墙遮阳板的构造进行建模分析,并对其节能前景进行预测.在保证冬季日照的前提下,对于天津地区南向墙遮阳板宽度宜取0.5～0.9m,距窗户上沿距离0.5～0.8m.安装遮阳板后,南向窗每个夏季可减少太阳辐射得热80～110MJ/m2.

气候变化条件下中国典型城市未来天气参数与建筑能源需求预测

20世纪以来,全球气候变暖趋势已得到证实,对生态系统和人居环境造成的影响备受瞩目,气候变化无疑将对建筑能源需求产生重大影响。基于IPCC最新预测结果,选择我国3个典型气候区代表城市——北京、上海和广州,采用统计降尺度方法 -Mor-phing,在现有典型气象年的基础上,结合地球气候模式(GCM)在气候变化中间稳定路径(RCP4.5)和高端路径(RCP8.5)下的大尺度预测结果,进行未来天气参数预测。针对每个城市、每个气候变化路径各生成5个未来时间段(2000年～2017年、2018年～2035年、2036年～2053年、2054年～2071年和2072年～2089年)的TMY逐时天气参数文件,用于典型建筑模型进行全年能耗模拟,预估典型城市建筑能源需求在未来100年里的变化趋势。

寒冷地区直膨式太阳能热泵热水器性能分析

基于直膨式太阳能热泵热水器的数学模型编制系统仿真程序,分别选取兰州地区典型气象年、辐射极低年和辐射极高年3种气象参数,计算得出3种不同气象参数下系统全年性能参数。分别选取1月2日和7月16日作为冬季和夏季典型日,输入典型气象年气象参数,计算得出典型日系统性能参数。模拟计算结果表明:将水从20℃加热到50℃,系统全年运行COP在3.500以上,在7月份达到最大值5.630,热水加热时间均在140min以内,在7月份达到最小值91min;系统性能具有明显的季节差异,在冬季典型日和夏季典型日系统平均COP分别为3.768和5.869;系统的运行时段对系统性能具有很大影响,中午时段的运行性能一般要优于其他时段。由系统全年和典型日性能分析结果可知,兰州地区的气象条件可以保证系统具有较好的全年运行性能。

空冷机组设计中典型气象年的选取

以府谷清水川电厂为例,对空冷机组典型气象年(typical meteorological year,TMY)的选取进行探讨,根据影响空冷机组设计及运行的气象因素,确定平均温度、最高温度、最低温度、平均风速和最大风速等5个气象参数作为因子,利用Finkelstein-Schafer(FS)统计方法选取TMY,并与传统的典型代表年(typical reference year,TRY)进行设计气温、满发气温等几方面的对比分析。结果表明,TMY较TRY更能反映建设项目所在地气温变化的长期规律,适应机组夏季满发的"多发电量"性质要求,且TMY所选设计气温更有利于机组经济运行,因此可以得出FS方法选择TMY是切实可行的,且明显优于TRY,对空冷系统的设计更具应用价值,同时总结典型年选取的步骤,首先确定资料统计时段,然后选取典型月(typical meteorological month,TMM)组成一个"虚拟"气象年。

建筑能耗模拟用典型气象年产生方法的研究

室外气候条件的准确描述是建筑能耗模拟评估正确与否的基础,用于表征室外气候条件的典型年TMY(Typical Meteorological Year)由8 760 h的逐时气象参数组成.TMY的产生需要长期的气象参数记录和科学的处理方法.本文梳理了国内外现有的TMY的产生方法和进行建筑能耗动态模拟用逐时气象参数的处理方法,以及气候变化下未来TMY的产生方法.典型年气象数据的正确处理是进行建筑节能和建筑设计的基础工作.

典型气象年和典型代表年的选择及其对建筑能耗的影响

介绍了典型气象年和典型代表年的选择原理和几种常见的选择方法。不同的方法考虑了不同气象参数的加权因子和气象数据的连续性。介绍了将太阳辐射总量分为太阳直射辐射量与太阳散射辐射量的应用模型 ,并依据香港的气象数据 ,分别计算选出了香港的典型气象年与典型代表年。为了验证不同方法计算出的典型气象年与典型代表年对研究对象、系统的影响 ,作了一个实例建筑物能耗动态模拟。结果表明 ,不同典型气象年对模拟结果的影响偏差较小 ,而典型代表年的影响较大 ;