基于气候的采暖空调耗能及室外计算参数研究
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摘要
气候与能源的关系是当今世界各国政府和学者关注的热点问题之一。一方面能源的开发利用影响气候变化,另一方面气候变化也影响到能源的消耗。目前我国的建筑能耗已约占全社会总耗能的30%,其中主要是采暖和空调能耗,而采暖、空调能耗是与气候变化直接相关的。在全球变暖的大背景下,近年来的气候变化形势更加剧烈复杂,研究气候变化对采暖空调耗能的影响具有重要的现实意义。
本文在国家863计划(2006AA05Z221)和国家自然基金项目(50778144)的资助下,从国家气象中心获取了194个台站的近40年(1961年-2000年)原始气象资料,选择全国主要省会城市,根据《民用建筑热工设计规范》的分区,对严寒、寒冷、夏热冬冷、夏热冬暖和温和区这五个建筑热工分区分别采用度日法分析研究了近年来我国的气候变化情况及其对冬季采暖和夏季空调耗能的影响。在分析气候学的一般规律基础上,利用概率论和数理统计的方法,用耿贝尔分布对极端温度建立了统计模型。进行了不同保证率下采暖、空调室外计算温度参数的研究以及极端温度情况下的能耗分析。主要内容及成果如下:
(1)通过对全国主要城市1961-2000年气温变化的统计分析,得到并分析了我国五个热工分区40年来平均温度、采暖度日HDD和空调度日CDD的变化趋势规律以及平均温度变化与采暖、空调度日变化的相关关系。根据统计得到的度日数变化趋势方程可对度日数进行预测。
(2)采用度日分析法研究了我国典型城市和各热工分区气温变化对冬季采暖耗能的影响。主要工作和结论有:①采暖度日与冬季气温之间具有良好的线性相关关系。采暖度日变率与冬季各月的平均气温均呈现出高度显著的线性相关性,2月份的相关性较12月和1月密切。线性回归是显著的。②通过对所建立的各热工分区采暖耗能评估模型分析发现,温度变化相同时各热工分区的采暖耗能降低幅度是不同的,严寒地区、寒冷地区、夏热冬冷地区、温和和夏热冬暖地区呈依次增加趋势。③以北京市冬季单位面积采暖销售量为例,对采暖度日与采暖耗能的关系进行了研究,两者线性相关显著。④暖冬对采暖耗能的影响明显。
(3)采用度日分析法研究了我国典型城市和各热工分区气温变化对夏季空调耗能的影响。主要工作和结论有:①空调度日与夏季气温之间相关关系显著。空调度日变率与夏季的平均气温距平线性相关性最为密切,线性回归是显著的。②通过对所建立的各热工分区空调耗能评估模型分析发现,温度变化相同时各热工分区的空调耗能变化幅值随夏热冬冷地区、夏热冬暖地区、寒冷地区、严寒地区及温和地区呈依次增加趋势。③以上海市用电量为例,对室外平均温度和电力耗能关系进行了相关研究。④以西安某建筑为例分析了室外平均温度变化对建筑物空调能耗的影响,计算表明气候变暖对夏季空调能耗影响已经成为空调设计和节能计算所需考虑的重要因素。
(4)运用气候学、概率论及数理统计学原理及方法,以我国典型城市的原始气象数据为基础,引入频率分析法,采用耿贝尔分布建立了我国极端气温统计模型,得到了极端温度频率的计算公式及概率分布曲线图,曲线与实测数据吻合良好且通过显著水平α=0.05的x~2检验,结果表明,使用耿贝尔分布函数对极端温度的频率分布进行模拟是合理和准确的。
(5)对全国五个热工分区建立了基于极端温度统计模型的室外计算温度正态分布简化计算模型,得到各热工分区室外计算温度保证率和极端温度重现期的相关性方程。通过编程对不同温度重现期下建筑能耗的变化进行了计算和分析。主要工作和结论有:①对所选取城市近年来的极端温度进行统计计算,得到各个城市不同重现率的极端温度值统计值。②根据极端温度统计模型建立了采暖、空调室外计算温度的正态简化模型并进行了实例验证。结果表明模型是合理和准确的。③得到了冬季采暖室外计算温度、夏季空调室外计算干球温度和夏季空调室外计算日平均温度的现行规范统计值在不同温度重现期下的保证率。分析比较了各热工分区采暖空调室外计算参数在不同温度重现期下的保证率变化趋势和规律,给出了量化的经验计算公式。④以北京市某建筑物为例,编程对不同温度重现期下建筑能耗的变化进行了计算。结果表明,在进行空调设计和计算时应该考虑极端气候条件对空调能耗的影响。
通过本文的研究,初步揭示了我国气候变化规律及气候变化对采暖和空调耗能变化的影响。对这一问题的研究,有助于明确气候变化对能源消耗影响的具体情况,不但可以了解气候正常情况下能源需求的变化规律,还可以预测气候异常变化特别是异常寒冬或炎热发生时能源需求的变化情况,为决策部门应对气候变化带来的能源需求调整提供了参考,为采暖空调系统在保证安全性的前提下进行节能优化设计提供了依据,同时也为相关问题的深入研究打下了基础。
The relation between climate and energy is one of the hot issues which government and scholar all around the current world pay close attention to.On one hand the development and utilization of energy influences climate,on the other hand climate change influences the consumption of energy too.Undoubtedly,it is the most urgent environmental problem that we face that the global climate becomes warm.Therefore, it is necessary to study on the influence of climate change on heating and cooling energy consumption.
This dissertation has obtained the original meteorological data in the past 40 years (1961-2000) that stand of 194 weather stations from the National Meteorological Center.According to the district of "thermal design specification of civil building", use the techniques of degree-day method to analyze the China's climate change of recent decades and impact of climate change on winter heating and summer cooling energy consumption.On the basis of analyzing the general rules the climate change, based on the theory of probability and mathematical statistical methods,established a statistical model of extreme temperature with Gumbel distribution.Carried out the study on heating,air-conditioning outdoor design parameters under different guaranteed rates,calculated energy consumption under the extreme temperature.The innovative work and main conclusions are listed as follows:
(1) Through the statistical analysis of temperature changes of the major cities in 1961-2000,obtained the tendency law of average temperature,heating degree days HDD,air conditioning degree days CDD and the relevant correlation between the average temperature change and HDD and CDD change.According to the statistics trend equation obtained,the number of degree days in future can be predicted.
(2) Adopting the techniques of degree-day method,studied the impact of temperature change of typical cities and each zone on winter heating energy consumption.The main coverage and conclusions are as follows.1) There are closely correlations between heating degree-day and winter average temperature.The change rate of heating degree-day and each month of winter(December,January,February) were shown a good linear correlation.2) Through analyzing the established heating energy assessment model of each thermal zone,found that the impact of temperature change on the heating demand of each thermal zone are different.When the temperature change 1℃,the change rate of energy consumption of hot summer and warm winter zone and mild zone are larger than that of cold zones and hot summer and cold winter zone.3) Take Beijing as an example,carried on research of relation of unit area heating sales volume and that heating degree-day.Found that the linear correlation of the two is prominent.4) Warm winter had significant impact on heating energy consumption.
(3) Adopting the techniques of degree-day method,studied the impact of temperature change of typical cities and each zone on summer cooling energy consumption.The main coverage and conclusions are as follows.1) There are closely correlations between cooling degree-day and summer average temperature.The change rate of cooling degree-day and summer average temperature were shown a significant linear relationship.2) Through analyzing the established cooling energy assessment model of each thermal zone,found that the impact of temperature change on the cooling demand of each thermal zone are different.When the temperature anomaly changes 0.1℃,the increasing degree of cooling energy consumption of each thermal zone is different.3) Take the electricity consumption in Shanghai for example.The relation between outdoor average temperature and the electricity consumption was studied.The results showed that the average outdoor temperature and power consumption has a good linear correlation and the linear regression is highly significant.4) Taking a certain construction of Xi'an as an example,analyzed the relation between the air conditioning energy consumption and outdoor temperature. The results showed that the heat loss of the build envelop was increased by an average of about 22%when the outdoor average temperature of air-conditioning raise 1℃.
(4)Using climatology,probability theory and mathematical statistical methods, on the basis of the original meteorological data of China typical cities,introducing the frequency analysis method,establish the extreme temperature statistical model by using Gumbel distribution.Achieved the calculating formula of the frequency of extreme temperature and the probability distribution curve.The curve was in good agreement with the measured data and passed through the testing,of a significant level of 0.05.The testing result showed that adopting the Gumbel distribution to match the extreme temperature is reasonable.
(5)Basing on statistical models of extreme temperature,built the simplified normal distribution model of outdoor temperature for each thermal zone.Obtained the relevance of the equation of the ensure ratio and the return period of outdoor temperature.The main work and conclusions are as follows.1)Through calculating the temperature value of summer daily average extreme temperature,winter daily average extreme daily,summer extreme temperature and winter extreme temperature, obtained the statistical value of extreme temperature of different return period.2) According to the extreme temperature statistical model,established normal simplified model of heating,air-conditioning outside temperature.The results showed that the simplified model for calculating normal value has a good match with the existing norms of HVAC statistical method.3) Analyzed the trends and changes in the law of guarantee rate of heating and air-conditioning outdoor temperature at different return period.Given the quantitative formula of experience.4) Took a building in Beijing for example.Wrote program to calculate the building energy consumption changes at the temperature of different return periods.The results showed that,with the temperature increase from the normal value to once in hundred years,the heat loss of building envelop also increased rapidly.Therefore,during the design of air-conditioning the extreme weather conditions should be considered.
Through the work of this dissertation,reveals the climate change laws and the impact of climate change on heating and cooling energy changes.The study of this problem is helpful to determine the concrete condition of the impact of climate change on energy consumption.Not only can master the energy demand change law under normal climate condition,but also can forecast the energy demand under abnormal climate condition.It can offer the reference to the administrator and offer the theory basis of optical and energy efficiency design of heating and air conditioning design.Besides,it will be a guide for the relevant research.
本文在国家863计划(2006AA05Z221)和国家自然基金项目(50778144)的资助下,从国家气象中心获取了194个台站的近40年(1961年-2000年)原始气象资料,选择全国主要省会城市,根据《民用建筑热工设计规范》的分区,对严寒、寒冷、夏热冬冷、夏热冬暖和温和区这五个建筑热工分区分别采用度日法分析研究了近年来我国的气候变化情况及其对冬季采暖和夏季空调耗能的影响。在分析气候学的一般规律基础上,利用概率论和数理统计的方法,用耿贝尔分布对极端温度建立了统计模型。进行了不同保证率下采暖、空调室外计算温度参数的研究以及极端温度情况下的能耗分析。主要内容及成果如下:
(1)通过对全国主要城市1961-2000年气温变化的统计分析,得到并分析了我国五个热工分区40年来平均温度、采暖度日HDD和空调度日CDD的变化趋势规律以及平均温度变化与采暖、空调度日变化的相关关系。根据统计得到的度日数变化趋势方程可对度日数进行预测。
(2)采用度日分析法研究了我国典型城市和各热工分区气温变化对冬季采暖耗能的影响。主要工作和结论有:①采暖度日与冬季气温之间具有良好的线性相关关系。采暖度日变率与冬季各月的平均气温均呈现出高度显著的线性相关性,2月份的相关性较12月和1月密切。线性回归是显著的。②通过对所建立的各热工分区采暖耗能评估模型分析发现,温度变化相同时各热工分区的采暖耗能降低幅度是不同的,严寒地区、寒冷地区、夏热冬冷地区、温和和夏热冬暖地区呈依次增加趋势。③以北京市冬季单位面积采暖销售量为例,对采暖度日与采暖耗能的关系进行了研究,两者线性相关显著。④暖冬对采暖耗能的影响明显。
(3)采用度日分析法研究了我国典型城市和各热工分区气温变化对夏季空调耗能的影响。主要工作和结论有:①空调度日与夏季气温之间相关关系显著。空调度日变率与夏季的平均气温距平线性相关性最为密切,线性回归是显著的。②通过对所建立的各热工分区空调耗能评估模型分析发现,温度变化相同时各热工分区的空调耗能变化幅值随夏热冬冷地区、夏热冬暖地区、寒冷地区、严寒地区及温和地区呈依次增加趋势。③以上海市用电量为例,对室外平均温度和电力耗能关系进行了相关研究。④以西安某建筑为例分析了室外平均温度变化对建筑物空调能耗的影响,计算表明气候变暖对夏季空调能耗影响已经成为空调设计和节能计算所需考虑的重要因素。
(4)运用气候学、概率论及数理统计学原理及方法,以我国典型城市的原始气象数据为基础,引入频率分析法,采用耿贝尔分布建立了我国极端气温统计模型,得到了极端温度频率的计算公式及概率分布曲线图,曲线与实测数据吻合良好且通过显著水平α=0.05的x~2检验,结果表明,使用耿贝尔分布函数对极端温度的频率分布进行模拟是合理和准确的。
(5)对全国五个热工分区建立了基于极端温度统计模型的室外计算温度正态分布简化计算模型,得到各热工分区室外计算温度保证率和极端温度重现期的相关性方程。通过编程对不同温度重现期下建筑能耗的变化进行了计算和分析。主要工作和结论有:①对所选取城市近年来的极端温度进行统计计算,得到各个城市不同重现率的极端温度值统计值。②根据极端温度统计模型建立了采暖、空调室外计算温度的正态简化模型并进行了实例验证。结果表明模型是合理和准确的。③得到了冬季采暖室外计算温度、夏季空调室外计算干球温度和夏季空调室外计算日平均温度的现行规范统计值在不同温度重现期下的保证率。分析比较了各热工分区采暖空调室外计算参数在不同温度重现期下的保证率变化趋势和规律,给出了量化的经验计算公式。④以北京市某建筑物为例,编程对不同温度重现期下建筑能耗的变化进行了计算。结果表明,在进行空调设计和计算时应该考虑极端气候条件对空调能耗的影响。
通过本文的研究,初步揭示了我国气候变化规律及气候变化对采暖和空调耗能变化的影响。对这一问题的研究,有助于明确气候变化对能源消耗影响的具体情况,不但可以了解气候正常情况下能源需求的变化规律,还可以预测气候异常变化特别是异常寒冬或炎热发生时能源需求的变化情况,为决策部门应对气候变化带来的能源需求调整提供了参考,为采暖空调系统在保证安全性的前提下进行节能优化设计提供了依据,同时也为相关问题的深入研究打下了基础。
The relation between climate and energy is one of the hot issues which government and scholar all around the current world pay close attention to.On one hand the development and utilization of energy influences climate,on the other hand climate change influences the consumption of energy too.Undoubtedly,it is the most urgent environmental problem that we face that the global climate becomes warm.Therefore, it is necessary to study on the influence of climate change on heating and cooling energy consumption.
This dissertation has obtained the original meteorological data in the past 40 years (1961-2000) that stand of 194 weather stations from the National Meteorological Center.According to the district of "thermal design specification of civil building", use the techniques of degree-day method to analyze the China's climate change of recent decades and impact of climate change on winter heating and summer cooling energy consumption.On the basis of analyzing the general rules the climate change, based on the theory of probability and mathematical statistical methods,established a statistical model of extreme temperature with Gumbel distribution.Carried out the study on heating,air-conditioning outdoor design parameters under different guaranteed rates,calculated energy consumption under the extreme temperature.The innovative work and main conclusions are listed as follows:
(1) Through the statistical analysis of temperature changes of the major cities in 1961-2000,obtained the tendency law of average temperature,heating degree days HDD,air conditioning degree days CDD and the relevant correlation between the average temperature change and HDD and CDD change.According to the statistics trend equation obtained,the number of degree days in future can be predicted.
(2) Adopting the techniques of degree-day method,studied the impact of temperature change of typical cities and each zone on winter heating energy consumption.The main coverage and conclusions are as follows.1) There are closely correlations between heating degree-day and winter average temperature.The change rate of heating degree-day and each month of winter(December,January,February) were shown a good linear correlation.2) Through analyzing the established heating energy assessment model of each thermal zone,found that the impact of temperature change on the heating demand of each thermal zone are different.When the temperature change 1℃,the change rate of energy consumption of hot summer and warm winter zone and mild zone are larger than that of cold zones and hot summer and cold winter zone.3) Take Beijing as an example,carried on research of relation of unit area heating sales volume and that heating degree-day.Found that the linear correlation of the two is prominent.4) Warm winter had significant impact on heating energy consumption.
(3) Adopting the techniques of degree-day method,studied the impact of temperature change of typical cities and each zone on summer cooling energy consumption.The main coverage and conclusions are as follows.1) There are closely correlations between cooling degree-day and summer average temperature.The change rate of cooling degree-day and summer average temperature were shown a significant linear relationship.2) Through analyzing the established cooling energy assessment model of each thermal zone,found that the impact of temperature change on the cooling demand of each thermal zone are different.When the temperature anomaly changes 0.1℃,the increasing degree of cooling energy consumption of each thermal zone is different.3) Take the electricity consumption in Shanghai for example.The relation between outdoor average temperature and the electricity consumption was studied.The results showed that the average outdoor temperature and power consumption has a good linear correlation and the linear regression is highly significant.4) Taking a certain construction of Xi'an as an example,analyzed the relation between the air conditioning energy consumption and outdoor temperature. The results showed that the heat loss of the build envelop was increased by an average of about 22%when the outdoor average temperature of air-conditioning raise 1℃.
(4)Using climatology,probability theory and mathematical statistical methods, on the basis of the original meteorological data of China typical cities,introducing the frequency analysis method,establish the extreme temperature statistical model by using Gumbel distribution.Achieved the calculating formula of the frequency of extreme temperature and the probability distribution curve.The curve was in good agreement with the measured data and passed through the testing,of a significant level of 0.05.The testing result showed that adopting the Gumbel distribution to match the extreme temperature is reasonable.
(5)Basing on statistical models of extreme temperature,built the simplified normal distribution model of outdoor temperature for each thermal zone.Obtained the relevance of the equation of the ensure ratio and the return period of outdoor temperature.The main work and conclusions are as follows.1)Through calculating the temperature value of summer daily average extreme temperature,winter daily average extreme daily,summer extreme temperature and winter extreme temperature, obtained the statistical value of extreme temperature of different return period.2) According to the extreme temperature statistical model,established normal simplified model of heating,air-conditioning outside temperature.The results showed that the simplified model for calculating normal value has a good match with the existing norms of HVAC statistical method.3) Analyzed the trends and changes in the law of guarantee rate of heating and air-conditioning outdoor temperature at different return period.Given the quantitative formula of experience.4) Took a building in Beijing for example.Wrote program to calculate the building energy consumption changes at the temperature of different return periods.The results showed that,with the temperature increase from the normal value to once in hundred years,the heat loss of building envelop also increased rapidly.Therefore,during the design of air-conditioning the extreme weather conditions should be considered.
Through the work of this dissertation,reveals the climate change laws and the impact of climate change on heating and cooling energy changes.The study of this problem is helpful to determine the concrete condition of the impact of climate change on energy consumption.Not only can master the energy demand change law under normal climate condition,but also can forecast the energy demand under abnormal climate condition.It can offer the reference to the administrator and offer the theory basis of optical and energy efficiency design of heating and air conditioning design.Besides,it will be a guide for the relevant research.
引文
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