基于整体能量需求的方案阶段建筑节能设计方法研究
|
摘要
目前我国建筑节能设计领域仍然存在一些不足与缺憾。首先,过于关注空调采暖负荷而忽视建筑整体能量需求;其次,轻视“源头”控制而强调“下游”操作,结果可能在方案设计阶段就偏离了节能设计的方向;最后,缺乏系统而完善的节能设计导则,特别是方案阶段的设计导则,无法为设计者明确建筑节能设计方向。基于此,本论文重点研究基于整体能量需求的建筑方案阶段节能设计方法,具体开展以下工作。
首先,总结和评价了现有的建筑方案阶段节能设计方法及节能设计导则的形式,并在此基础上,确立了以“建立能量需求简化预测模型——基于最优化方法的节能建筑设计——方案阶段节能设计导则”的研究路线。
其次,在稳态公式、模拟拟合等方法基础上建立建筑整体能量需求预测模型(简称AEDPM)。包括围护结构负荷贡献量、暖通空调(HVAC)负荷、HVAC系统综合效率、照明能耗等多个预测模型。其中的围护结构负荷贡献量及HVAC负荷预测模型在前人研究基础上,引入了对间歇空调、夜间通风辐射等多项修正,并与建筑能耗与热环境模拟软件DeST进行了比较验证。HVAC系统综合效率模型通过总结实际系统能耗调研数据和常见系统形式的特点建立。照明能耗预测模型通过采光节能计算软件Daysim模拟拟合成经验公式后建立。
第三,基于遗传算法和AEDPM,建立了能自动生成满足建筑方案基本要求的最节能方案生成程序(简称MEESG),并利用详细模拟软件验证了不同气象条件下的最优节能方案。然后,利用MEESG研究了照明能耗对建筑节能方案的影响,分析了不同气象条件、不同建筑类型条件下最节能方案的设计措施。
最后,研究方案阶段节能设计导则的制定方法,提出利用“基于最优方案的敏感性分析”建立节能设计导则。导则主要向设计者提供两点信息,一是各设计因素的优化趋势类别,用于指导优化设计的方向,二是各设计因素的设计特征量——区间弹性,用于明确优化设计的收益。
本研究建立了一套建筑方案阶段节能设计方法体系,探讨了方案阶段节能设计导则的形式,有助于推动建筑节能技术在建筑方案设计阶段中的应用。
At present, there are still some deficiencies in the field of energy-saving building design. First, HVAC load is overemphasized, hence embodied building energy demand is neglected. Second, the consideration of energy saving in early design stages is often ignored, and the aided design tools cannot be well introduced into scheme design stage. Third, there is a lack of systematic energy-saving building design guidelines, especially the ones for scheme design stage. Based on it, this paper mainly focuses on energy saving design method considering embodied energy demand in the scheme design stage. The following research is carried out.
First, existing research of building energy-saving method in scheme design stage is summarized and evaluated. And a research route of“establish simplified energy demand predication model—develop optimization-method-based scheme design approach—study on the form of design guidelines”is determined.
Second, a building embodied energy demand predication model“AEDPM”is established, which includes some sub-models of building envelope load, HVAC load, HVAC system integrated efficiencies and lighting energy consumption, etc. Of them, the building envelope load model is developed by introducing some corrections for intermittent air-conditioning, nighttime ventilation/radiation conditions, etc, into the existing models established by former researchers, and is validated by dynamic building thermal simulation software DeST. The HVAC system efficiency predication model is built by summarizing practical system energy consumption data and common system types’characteristics. And lighting energy consumption predication model is built by empirical formulas curve-fitted from daylighting energy-saving simulation by Daysim.
Third, based on genetic algorithm, a program (named MEESG), which can automatically generate most energy-efficient building scheme under scheme’s fundermental demands and restrictions, is developed and validated. Then, the influence on optimal building scheme with the introduction of lighting energy demand is studied using MEESG, and several case studies for different climate zone and building type are carried out to explain the application of MEESG.
Finally, establishing method and manifestation of the energy-saving building design guidelines for scheme design stage is studied. The guidelines are established by“sensitivity analysis basing on the optimal building scheme”. It provides designers two types of information, one is the“optimazing trend type”of each design factor, which illustrates the design direction of the factor, the other is the characteristic value of each design factor—interval elasticity, which illustrates the benefit of each design factor’s optimazing design.
To summarize, this paper establishes an energy-saving building design method system for scheme design stage, and studied the methodology and manifestation of energy saving design guidelines for this stage. The research may help promote the application of energy-saving technologies in building’s design process, especially the scheme design process.
首先,总结和评价了现有的建筑方案阶段节能设计方法及节能设计导则的形式,并在此基础上,确立了以“建立能量需求简化预测模型——基于最优化方法的节能建筑设计——方案阶段节能设计导则”的研究路线。
其次,在稳态公式、模拟拟合等方法基础上建立建筑整体能量需求预测模型(简称AEDPM)。包括围护结构负荷贡献量、暖通空调(HVAC)负荷、HVAC系统综合效率、照明能耗等多个预测模型。其中的围护结构负荷贡献量及HVAC负荷预测模型在前人研究基础上,引入了对间歇空调、夜间通风辐射等多项修正,并与建筑能耗与热环境模拟软件DeST进行了比较验证。HVAC系统综合效率模型通过总结实际系统能耗调研数据和常见系统形式的特点建立。照明能耗预测模型通过采光节能计算软件Daysim模拟拟合成经验公式后建立。
第三,基于遗传算法和AEDPM,建立了能自动生成满足建筑方案基本要求的最节能方案生成程序(简称MEESG),并利用详细模拟软件验证了不同气象条件下的最优节能方案。然后,利用MEESG研究了照明能耗对建筑节能方案的影响,分析了不同气象条件、不同建筑类型条件下最节能方案的设计措施。
最后,研究方案阶段节能设计导则的制定方法,提出利用“基于最优方案的敏感性分析”建立节能设计导则。导则主要向设计者提供两点信息,一是各设计因素的优化趋势类别,用于指导优化设计的方向,二是各设计因素的设计特征量——区间弹性,用于明确优化设计的收益。
本研究建立了一套建筑方案阶段节能设计方法体系,探讨了方案阶段节能设计导则的形式,有助于推动建筑节能技术在建筑方案设计阶段中的应用。
At present, there are still some deficiencies in the field of energy-saving building design. First, HVAC load is overemphasized, hence embodied building energy demand is neglected. Second, the consideration of energy saving in early design stages is often ignored, and the aided design tools cannot be well introduced into scheme design stage. Third, there is a lack of systematic energy-saving building design guidelines, especially the ones for scheme design stage. Based on it, this paper mainly focuses on energy saving design method considering embodied energy demand in the scheme design stage. The following research is carried out.
First, existing research of building energy-saving method in scheme design stage is summarized and evaluated. And a research route of“establish simplified energy demand predication model—develop optimization-method-based scheme design approach—study on the form of design guidelines”is determined.
Second, a building embodied energy demand predication model“AEDPM”is established, which includes some sub-models of building envelope load, HVAC load, HVAC system integrated efficiencies and lighting energy consumption, etc. Of them, the building envelope load model is developed by introducing some corrections for intermittent air-conditioning, nighttime ventilation/radiation conditions, etc, into the existing models established by former researchers, and is validated by dynamic building thermal simulation software DeST. The HVAC system efficiency predication model is built by summarizing practical system energy consumption data and common system types’characteristics. And lighting energy consumption predication model is built by empirical formulas curve-fitted from daylighting energy-saving simulation by Daysim.
Third, based on genetic algorithm, a program (named MEESG), which can automatically generate most energy-efficient building scheme under scheme’s fundermental demands and restrictions, is developed and validated. Then, the influence on optimal building scheme with the introduction of lighting energy demand is studied using MEESG, and several case studies for different climate zone and building type are carried out to explain the application of MEESG.
Finally, establishing method and manifestation of the energy-saving building design guidelines for scheme design stage is studied. The guidelines are established by“sensitivity analysis basing on the optimal building scheme”. It provides designers two types of information, one is the“optimazing trend type”of each design factor, which illustrates the design direction of the factor, the other is the characteristic value of each design factor—interval elasticity, which illustrates the benefit of each design factor’s optimazing design.
To summarize, this paper establishes an energy-saving building design method system for scheme design stage, and studied the methodology and manifestation of energy saving design guidelines for this stage. The research may help promote the application of energy-saving technologies in building’s design process, especially the scheme design process.
引文
[1]清华大学建筑节能研究中心.中国建筑节能年度发展研究报(2009).北京:中国建筑工业出版社, 2009.
[2]中华人民共和国建设部. GB50189-2005.公共建筑节能标准.北京:中国建筑工业出版社, 2005
[3]薛志峰.大型公共建筑节能研究[博士学位论文].北京:清华大学, 2005.
[4] Energy Information Administration. International Energy outlook 2008.USA: EIA Publication, 2008.
[5]杨旭东.建筑节能的基础科学问题.“国家重点基础研究发展规划”申报演示文稿[R].北京:清华大学, 2007.
[6]张伶伶,李存东.建筑创作思维的过程与表达[M].北京:中国建筑工业出版社. 2001.
[7] Warren P. IEA-BCS ANNEX 30 final report: Bring simulation into application [R/OL]. [2008-05-22]. http://www.ecbcs.org/docs/annex_30_tsr_web.pdf.
[8]夏春海.面向建筑方案的节能设计方法研究[博士学位论文].北京:清华大学, 2008.
[9]夏伟.基于被动式设计策略的气候分区研究[博士学位论文].北京:清华大学, 2008.
[10] Square One research Ltd. Ecotect 5.5[CP]. http://www.squ1.com.
[11]云鹏. ECOTECT建筑环境设计教程.北京:中国建筑工业出版社, 2007
[12]清华大学DeST开发组.建筑环境系统模拟分析方法—DeST.北京:中国建筑工业出版社, 2006.
[13] United States Department of Energy (USDOE). EnergyPlus software [CP]. http://www.eere.energy.gov/buildings/energyplus/.
[14] United States Department of Energy (USDOE). eQuest software [CP]. http://www.doe2.com/equest/.
[15] Thermal Energy System Specialists, LLC (T.E.S.S.). Trnsys software [CP]. http://www.trnsys.com/.
[16] Integrated Environmental Solutions (IES) Ltd. Virtual Environment software [CP]. http://www.iesve.com/content/default.asp?page=.
[17] Clarke J A, McLean D. ESP-A building and plant energy simulation system. Strathclyde: Energy Simulation Research Unit, University of Strathclyede, 1988.
[18]清华大学建筑节能研究中心.中国建筑节能年度发展研究报(2007).北京:中国建筑工业出版社, 2007.
[19] Yik F W H, Wan K S Y. An evaluation of the appropriateness of using overall thermal transfer value (OTTV) to regulate envelope energy performance of air-conditioned buildings. Energy, 2005, 30:41-71.
[20] Krarti M, Erickson P M, Hillman T C. A simplified method to estimate energy savings of artificial lighting. Building and Environment, 2005, 40:747-754.
[21]王刚,邵伟,毕晓云,宋晓鹏.体育馆天窗采光影响因素模拟分析.低温建筑技术. 2008, 3: 128-130.
[22] Aizlewood M. The daylighting of atria: a critical review ASHRAE Transaction, 1995,101: 841-857.
[23]林波荣,余琼,周潇儒,朱颖心.办公建筑中庭形体参数对自然采光影响评价.城市化进程中的建筑与城市物理环境(第十届全国建筑物理学术会议论文集).广州:华南理工大学出版社,2008.
[24]陈超,渡边俊行,谢光亚,于航.日本的建筑节能概念与政策.暖通空调2002, 32(6): 40-43.
[25]建设部标准定额研究. JGJ75-2003.夏热冬暖地区居住建筑节能设计标准.北京:中国建筑工业出版社, 2003.
[26] ASHRAE. ASHRAE/IESNA Standard 90.1-2001, Energy Standard for Buildings Except Low-Rise Residential Buildings. Atlanta: American Society of Heating, Refrigerating, and Air-Conditioning Engineers, Inc., 2001.
[27] Yohanis Y G, Norton B. Including embodied energy considerations at the conceptual stage of building design. Proceedings of the Institution of Mechanical Engineers. 2006, 220(3): 271-288.
[28] Lam J C, Hui S C M. Sensitivity analysis of energy performance of office buildings. Building and Environment, 1996, 31(1): 27-39.
[29]周潇儒. (演示文稿)基于模拟软件的建筑立案方案辅助评价[R].清华大学, 2006.
[30]林波荣,周潇儒. (演示文稿)Design with Simulation-Metro Valley SED Project [R].清华大学建筑技术系, 2008.
[31] Kassab M, Lee T. The development of integrated based-simulation design support system. Proceedings of Building Simulation 2007, 2007, 3: 1734-1739.
[32] US Department of Energy. Desktop Radiance [CP]. http://radsite.lbl.gov/radiance.
[33] Aksoy U T, Inalli M. Impacts of some building passive design parameters on heating demand for a cold region. Building and Environment, 2006, 41:1742-1754.
[34] Transsolar Energietechnik GmbH (www.transsolar.com).深圳-大梅沙万科中心纲要设计报告[R]. 2006.
[35]古军,周潇儒. 2007年招商地产绿色建筑设计大赛获奖作品,设计结合技术[R]. 2007.
[36] Mehta D P, Dynamic thermal response of buildings and systems [Ph.D. thesis]. USA: Iowa State University, 1980.
[37] Case K E, Fair R C. Principles of Economics [M]. USA: Prentice-Hall, 1989. 114-126.
[38] Cordon G C. Input-output sensitivity of building energy simulations. ASHRAE Transaction dS, 1992, Part I: 618-626.
[39] United States Department of Energy (USDOE). DOE-2 softerware [CP]. http://doe2.com/DOE2/index.html.
[40] Filipe P, Tavares A F, Manuel A, Martins O G. Energy efficient building design using sensitivity analysis-A case study. Energy and Buildings, 2007, 39:23-31.
[41] Harputlugil G U, Hensen J L M, Wilde P. Simulation as a tool to develop guidelines for the design of school schemes for four climatic regions of Turkiye. Proceedings of Building Simulation 2007, 2007, 3:1806-1812.
[42]林宪德.东亚都市办公建筑围护结构节能对策分析.第六届中国城市住宅研讨会论文集. 2007.
[43]曾剑龙.性能可调节围护结构研究[博士学位论文].北京:清华大学, 2006.
[44]林威.新型围护结构应用评价研究[硕士学位论文].北京:清华大学, 2008.
[45] Yalcintas M, Ozturk U A. An energy benchmarking model based on artificial neuralnetwork method utilizing US Commercial Buildings Energy Consumption Survey (CBECS) database. International Journal of Energy Research, 2006, 31:412-421.
[46] CBECS (Commercial Building Energy Consumption Surveys) database [DB/OL]. http://www.eia.doe.gov/emeu/cbecs.
[47] Ramirez R F, Sebold T, Mayer M, Ciminelli M. A building simulation palooza: the California CEUS Project and DrCEUS. Proceedings of Building Simulation 2005, 2005, 1003-1010.
[48] Bruhns H, Steadman P, Herring H, A database for modeling energy use in the non-domestic building stock of England and Wales. Applied Energy, 2000, 66:277-297.
[49] Mathews E H, Heerden E, Arndt D C. A tool for integrated HVAC\ building\ energy and control analysis Part 1: overview of QUICKcontrol. Building and Environment, 1999, 34:429-449.
[50] Ellis M W, Mathews E H. A new simplied thermal design tool for architects. Building and Environment, 2001, 36:1009-1021.
[51] Corrado V, Fabrizio E. Assessment of building cooling energy need through a quasi-steady state model:Simplified correlation for gain-loss mismatch. Energy and Buildings. 2007, 39(5):569-579.
[52] Baker N, Steemer K. LT Method 3.0-a strategic energy-design tool for Southern Europe. Energy and Buildings, 1996, 23:251-256.
[53] Nielsen T R. Simple tool to evaluate energy demand and indoor environment in the early stages of building design. Solar Energy, 2005, 78:73-83.
[54] Yohanis Y G, Norton B. The early design model for prediction of energy and cost performance of building design options. Solar Energy, 2002, 22(2):47-61.
[55] Holland J H. Adaptation in natural and artifical systems. Ann Arbor, MI: The University of Michigan Press, 1975.
[56] Wright J A, Loosemore H A, Farmani Raziyeh. Optimization of building thermal design and control by multi-criterion genetic algorithm. Energy and Buildings, 2002, 34:959-972.
[57] Ooka R, Komamura K. Optimal design method for building energy systems using genetic algorithms. Building and Environment, 2009, 44:1538-1544.
[58] Ouarghi R, Krarti M. Building shape optimization using neural network and genetic algorithm approach. ASHRAE Transactions, 2006, 112(1):484-491.
[59] Chen H, Ooka R, Kato S. Study on optimum arrangement of pilotis for design of pleasant outdoor wind environment using CFD simulation and Genetic Algorithms (GA). The Sixth Asia-Pacific Conference on Wind Engineering (APCWE-VI), 2005.
[60] Wright J A, Hanby V I. The formulation, characteristics, and solution of HVAC system optimized design problems. ASHRAE Transaction, 1987, Pt 2, 93: 2133-2145.
[61] Xia C H, Zhu Y X, Lin B R. Building simulation as assistance in the conceptual design. Building Simulation, 2008, 1:46-52.
[62] Autodesk, Inc. & Ecotect. Ecotect 5.60 [CP]. http://ecotect.com/.
[63]姚润明,昆.斯蒂摩司,李百战.可持续城市与建筑设计.北京:中国建筑工业出版社, 2006.
[64] Bansal N K, Hauser G, Minke G. Passive Building Design: A Handbook of Natural Climatic Control. USA: Elsevier Science Ltd, 1994.
[65]诺波特.莱希纳(著),张利(译).建筑师技术设计指南(采暖降温照明).北京:中国建筑工业出版社, 2001.
[66]卜一德.绿色建筑技术指南.北京:中国建筑工业出版社, 2008.
[67]大卫.劳埃德.琼斯.建筑与环境(生态气候学建筑设计).北京:中国建筑工业出版社, 2005.
[68]黄光德,付祥钊,张慧玲.中国建筑节能气候分区及适用技术. 2006暖通空调制冷学术年会, 2006.
[69]美国绿色建筑委员会USGBC, LEED[DB/OL]. http://www.usgbc.org/programs/leed.htm.
[70]日本可持续建筑协会等. CASBEE建筑物综合环境性能评价体系—绿色设计工具.北京:中国建筑工业出版社, 2005.
[71]绿色奥运建筑研究课题组.绿色奥运建筑评估体系.北京:中国建筑工业出版社, 2003.
[72] Rabah K V O, Mito C O. Pre-design guidelines for passive solar architectural buildings in Kenya. International Journal of Sustainable Energy, 2003, 23(3):83-119.
[73]日本公共建筑协会.绿色厅舍的计划指南与解说[M]. 1999.
[74] Climate Surface software [CP]. http://www.bph.hbt.arch.ethz.ch/contents/subfolder/software/climatesurf_download.html.
[75] Heed software [CP]. http://www2.aud.ucla.edu/energy-design-tools/.
[76] Reinhart C, Bourgeois D, Dubrous F, Laouadi A, Lopez P, Stelescu O. Daylight1-2-3: A state-of-the-art daylighting/energy analysis software for initial design investigations. Proceedings of Building Simulation 2007, 2007, 3:1669-1676.
[77] Marks W. Multi-criteria optimization of shape of energy saving buildings. Building and Environment, 1997, 32(4):331–339.
[78] Kolokotroni M, Webb B C, Hayes S D. Summer cooling with night ventilation for office building in moderate climates. Energy and Buildings, 1998, 27(3):231-237.
[79]邸倩倩,陈华,律宝莹.办公楼夜间通风方式下室内热环境及节能分析.暖通与设备, 2008, 6:20-22.
[80]朱颖心(主编),彦启森(主审).建筑环境学(第二版).北京:中国建筑工业出版社, 2005.
[81]邵建涛,刘京,赵加宁,付志鹏张文武.建筑水平屋面对流换热特性的实验研究.华南理工大学学报(自然科学版), 2008, 36(3):134-139.
[82]雷涛.中庭空间生态设计策略的计算机模拟研究[硕士学位论文].北京:清华大学, 2004.
[83]朱颖心,江亿.用于空调系统设计的全年双负荷曲线分析法.暖通空调HV&AC, 1998, 28(4): 43-46.
[84]杨东华.火用分析和能级分析.北京:科学出版社,1986. 1～3.
[85]清华大学建筑技术科学系. (2006大型公共建筑能耗调研实习汇报演示文稿)安定门国资委办公大楼建筑能耗调查与节能诊断—第一阶段报告[R]. 2006.
[86]清华大学建筑技术科学系. (2005年大型公共建筑能耗调研实习报告)国家统计局六里桥办公楼能耗诊断报告书[R]. 2005.
[87] Reinhart C F. Daysim softeware [CP]. http://irc.nrc-cnrc.gc.ca/ie/lighting /daylight/daysim_e.html -User Manual.
[88]陈红兵.办公建筑的天然采光与能耗分析[博士学位论文].天津:天津大学, 2004.
[89]国家质量技术监督局,中华人民共和国建设部. GB 50096-1999.住宅设计规范.北京:中国建筑工业出版社, 1999.
[90]朱莉娅.麦克莫罗.建筑设计速查手册.大连:大连理工大学出版社, 2008.
[91] Reinhart C F, Walkenhorst O. Validation of dynamic RADIANCE-based daylight simulations for a test office with external blinds. Energy and Buildings, 2001(33):683-697.
[92]中华人民共和国建设部,国家质量监督检验检疫总局. GB/T 50033-2001.建筑采光设计标准.北京:中国建筑工业出版社, 1999.
[93]雷英杰,张善文,李续武,周创明. Matlab遗传算法工具箱及应用.西安:西安电子科技大学出版社, 2005.
[94] The Mathworks, Inc. Matlab 7.0a software [CP]. http://www.mathworks.cn/.
[95] Chipperfield A, Fleming P, Pohlheim H, Fonseca C. Genetic algorithm Toolbox user’s guide. Dept. of Automatic Control and Systems Engineering, University of Sheffield.
[96]清华大学建筑科学系,中国气象局气象信息中心气象资料室.中国建筑热环境分析专用气象数据集.北京:中国建筑工业出版社, 2005.
[97] Koltai T, Terlaky T. The difference between the managerial andmathematic al interpretation of sensitivity analysis results in linear programming. International Journal of Production Economics, 2000, 65:257–274.
[2]中华人民共和国建设部. GB50189-2005.公共建筑节能标准.北京:中国建筑工业出版社, 2005
[3]薛志峰.大型公共建筑节能研究[博士学位论文].北京:清华大学, 2005.
[4] Energy Information Administration. International Energy outlook 2008.USA: EIA Publication, 2008.
[5]杨旭东.建筑节能的基础科学问题.“国家重点基础研究发展规划”申报演示文稿[R].北京:清华大学, 2007.
[6]张伶伶,李存东.建筑创作思维的过程与表达[M].北京:中国建筑工业出版社. 2001.
[7] Warren P. IEA-BCS ANNEX 30 final report: Bring simulation into application [R/OL]. [2008-05-22]. http://www.ecbcs.org/docs/annex_30_tsr_web.pdf.
[8]夏春海.面向建筑方案的节能设计方法研究[博士学位论文].北京:清华大学, 2008.
[9]夏伟.基于被动式设计策略的气候分区研究[博士学位论文].北京:清华大学, 2008.
[10] Square One research Ltd. Ecotect 5.5[CP]. http://www.squ1.com.
[11]云鹏. ECOTECT建筑环境设计教程.北京:中国建筑工业出版社, 2007
[12]清华大学DeST开发组.建筑环境系统模拟分析方法—DeST.北京:中国建筑工业出版社, 2006.
[13] United States Department of Energy (USDOE). EnergyPlus software [CP]. http://www.eere.energy.gov/buildings/energyplus/.
[14] United States Department of Energy (USDOE). eQuest software [CP]. http://www.doe2.com/equest/.
[15] Thermal Energy System Specialists, LLC (T.E.S.S.). Trnsys software [CP]. http://www.trnsys.com/.
[16] Integrated Environmental Solutions (IES) Ltd. Virtual Environment software [CP]. http://www.iesve.com/content/default.asp?page=.
[17] Clarke J A, McLean D. ESP-A building and plant energy simulation system. Strathclyde: Energy Simulation Research Unit, University of Strathclyede, 1988.
[18]清华大学建筑节能研究中心.中国建筑节能年度发展研究报(2007).北京:中国建筑工业出版社, 2007.
[19] Yik F W H, Wan K S Y. An evaluation of the appropriateness of using overall thermal transfer value (OTTV) to regulate envelope energy performance of air-conditioned buildings. Energy, 2005, 30:41-71.
[20] Krarti M, Erickson P M, Hillman T C. A simplified method to estimate energy savings of artificial lighting. Building and Environment, 2005, 40:747-754.
[21]王刚,邵伟,毕晓云,宋晓鹏.体育馆天窗采光影响因素模拟分析.低温建筑技术. 2008, 3: 128-130.
[22] Aizlewood M. The daylighting of atria: a critical review ASHRAE Transaction, 1995,101: 841-857.
[23]林波荣,余琼,周潇儒,朱颖心.办公建筑中庭形体参数对自然采光影响评价.城市化进程中的建筑与城市物理环境(第十届全国建筑物理学术会议论文集).广州:华南理工大学出版社,2008.
[24]陈超,渡边俊行,谢光亚,于航.日本的建筑节能概念与政策.暖通空调2002, 32(6): 40-43.
[25]建设部标准定额研究. JGJ75-2003.夏热冬暖地区居住建筑节能设计标准.北京:中国建筑工业出版社, 2003.
[26] ASHRAE. ASHRAE/IESNA Standard 90.1-2001, Energy Standard for Buildings Except Low-Rise Residential Buildings. Atlanta: American Society of Heating, Refrigerating, and Air-Conditioning Engineers, Inc., 2001.
[27] Yohanis Y G, Norton B. Including embodied energy considerations at the conceptual stage of building design. Proceedings of the Institution of Mechanical Engineers. 2006, 220(3): 271-288.
[28] Lam J C, Hui S C M. Sensitivity analysis of energy performance of office buildings. Building and Environment, 1996, 31(1): 27-39.
[29]周潇儒. (演示文稿)基于模拟软件的建筑立案方案辅助评价[R].清华大学, 2006.
[30]林波荣,周潇儒. (演示文稿)Design with Simulation-Metro Valley SED Project [R].清华大学建筑技术系, 2008.
[31] Kassab M, Lee T. The development of integrated based-simulation design support system. Proceedings of Building Simulation 2007, 2007, 3: 1734-1739.
[32] US Department of Energy. Desktop Radiance [CP]. http://radsite.lbl.gov/radiance.
[33] Aksoy U T, Inalli M. Impacts of some building passive design parameters on heating demand for a cold region. Building and Environment, 2006, 41:1742-1754.
[34] Transsolar Energietechnik GmbH (www.transsolar.com).深圳-大梅沙万科中心纲要设计报告[R]. 2006.
[35]古军,周潇儒. 2007年招商地产绿色建筑设计大赛获奖作品,设计结合技术[R]. 2007.
[36] Mehta D P, Dynamic thermal response of buildings and systems [Ph.D. thesis]. USA: Iowa State University, 1980.
[37] Case K E, Fair R C. Principles of Economics [M]. USA: Prentice-Hall, 1989. 114-126.
[38] Cordon G C. Input-output sensitivity of building energy simulations. ASHRAE Transaction dS, 1992, Part I: 618-626.
[39] United States Department of Energy (USDOE). DOE-2 softerware [CP]. http://doe2.com/DOE2/index.html.
[40] Filipe P, Tavares A F, Manuel A, Martins O G. Energy efficient building design using sensitivity analysis-A case study. Energy and Buildings, 2007, 39:23-31.
[41] Harputlugil G U, Hensen J L M, Wilde P. Simulation as a tool to develop guidelines for the design of school schemes for four climatic regions of Turkiye. Proceedings of Building Simulation 2007, 2007, 3:1806-1812.
[42]林宪德.东亚都市办公建筑围护结构节能对策分析.第六届中国城市住宅研讨会论文集. 2007.
[43]曾剑龙.性能可调节围护结构研究[博士学位论文].北京:清华大学, 2006.
[44]林威.新型围护结构应用评价研究[硕士学位论文].北京:清华大学, 2008.
[45] Yalcintas M, Ozturk U A. An energy benchmarking model based on artificial neuralnetwork method utilizing US Commercial Buildings Energy Consumption Survey (CBECS) database. International Journal of Energy Research, 2006, 31:412-421.
[46] CBECS (Commercial Building Energy Consumption Surveys) database [DB/OL]. http://www.eia.doe.gov/emeu/cbecs.
[47] Ramirez R F, Sebold T, Mayer M, Ciminelli M. A building simulation palooza: the California CEUS Project and DrCEUS. Proceedings of Building Simulation 2005, 2005, 1003-1010.
[48] Bruhns H, Steadman P, Herring H, A database for modeling energy use in the non-domestic building stock of England and Wales. Applied Energy, 2000, 66:277-297.
[49] Mathews E H, Heerden E, Arndt D C. A tool for integrated HVAC\ building\ energy and control analysis Part 1: overview of QUICKcontrol. Building and Environment, 1999, 34:429-449.
[50] Ellis M W, Mathews E H. A new simplied thermal design tool for architects. Building and Environment, 2001, 36:1009-1021.
[51] Corrado V, Fabrizio E. Assessment of building cooling energy need through a quasi-steady state model:Simplified correlation for gain-loss mismatch. Energy and Buildings. 2007, 39(5):569-579.
[52] Baker N, Steemer K. LT Method 3.0-a strategic energy-design tool for Southern Europe. Energy and Buildings, 1996, 23:251-256.
[53] Nielsen T R. Simple tool to evaluate energy demand and indoor environment in the early stages of building design. Solar Energy, 2005, 78:73-83.
[54] Yohanis Y G, Norton B. The early design model for prediction of energy and cost performance of building design options. Solar Energy, 2002, 22(2):47-61.
[55] Holland J H. Adaptation in natural and artifical systems. Ann Arbor, MI: The University of Michigan Press, 1975.
[56] Wright J A, Loosemore H A, Farmani Raziyeh. Optimization of building thermal design and control by multi-criterion genetic algorithm. Energy and Buildings, 2002, 34:959-972.
[57] Ooka R, Komamura K. Optimal design method for building energy systems using genetic algorithms. Building and Environment, 2009, 44:1538-1544.
[58] Ouarghi R, Krarti M. Building shape optimization using neural network and genetic algorithm approach. ASHRAE Transactions, 2006, 112(1):484-491.
[59] Chen H, Ooka R, Kato S. Study on optimum arrangement of pilotis for design of pleasant outdoor wind environment using CFD simulation and Genetic Algorithms (GA). The Sixth Asia-Pacific Conference on Wind Engineering (APCWE-VI), 2005.
[60] Wright J A, Hanby V I. The formulation, characteristics, and solution of HVAC system optimized design problems. ASHRAE Transaction, 1987, Pt 2, 93: 2133-2145.
[61] Xia C H, Zhu Y X, Lin B R. Building simulation as assistance in the conceptual design. Building Simulation, 2008, 1:46-52.
[62] Autodesk, Inc. & Ecotect. Ecotect 5.60 [CP]. http://ecotect.com/.
[63]姚润明,昆.斯蒂摩司,李百战.可持续城市与建筑设计.北京:中国建筑工业出版社, 2006.
[64] Bansal N K, Hauser G, Minke G. Passive Building Design: A Handbook of Natural Climatic Control. USA: Elsevier Science Ltd, 1994.
[65]诺波特.莱希纳(著),张利(译).建筑师技术设计指南(采暖降温照明).北京:中国建筑工业出版社, 2001.
[66]卜一德.绿色建筑技术指南.北京:中国建筑工业出版社, 2008.
[67]大卫.劳埃德.琼斯.建筑与环境(生态气候学建筑设计).北京:中国建筑工业出版社, 2005.
[68]黄光德,付祥钊,张慧玲.中国建筑节能气候分区及适用技术. 2006暖通空调制冷学术年会, 2006.
[69]美国绿色建筑委员会USGBC, LEED[DB/OL]. http://www.usgbc.org/programs/leed.htm.
[70]日本可持续建筑协会等. CASBEE建筑物综合环境性能评价体系—绿色设计工具.北京:中国建筑工业出版社, 2005.
[71]绿色奥运建筑研究课题组.绿色奥运建筑评估体系.北京:中国建筑工业出版社, 2003.
[72] Rabah K V O, Mito C O. Pre-design guidelines for passive solar architectural buildings in Kenya. International Journal of Sustainable Energy, 2003, 23(3):83-119.
[73]日本公共建筑协会.绿色厅舍的计划指南与解说[M]. 1999.
[74] Climate Surface software [CP]. http://www.bph.hbt.arch.ethz.ch/contents/subfolder/software/climatesurf_download.html.
[75] Heed software [CP]. http://www2.aud.ucla.edu/energy-design-tools/.
[76] Reinhart C, Bourgeois D, Dubrous F, Laouadi A, Lopez P, Stelescu O. Daylight1-2-3: A state-of-the-art daylighting/energy analysis software for initial design investigations. Proceedings of Building Simulation 2007, 2007, 3:1669-1676.
[77] Marks W. Multi-criteria optimization of shape of energy saving buildings. Building and Environment, 1997, 32(4):331–339.
[78] Kolokotroni M, Webb B C, Hayes S D. Summer cooling with night ventilation for office building in moderate climates. Energy and Buildings, 1998, 27(3):231-237.
[79]邸倩倩,陈华,律宝莹.办公楼夜间通风方式下室内热环境及节能分析.暖通与设备, 2008, 6:20-22.
[80]朱颖心(主编),彦启森(主审).建筑环境学(第二版).北京:中国建筑工业出版社, 2005.
[81]邵建涛,刘京,赵加宁,付志鹏张文武.建筑水平屋面对流换热特性的实验研究.华南理工大学学报(自然科学版), 2008, 36(3):134-139.
[82]雷涛.中庭空间生态设计策略的计算机模拟研究[硕士学位论文].北京:清华大学, 2004.
[83]朱颖心,江亿.用于空调系统设计的全年双负荷曲线分析法.暖通空调HV&AC, 1998, 28(4): 43-46.
[84]杨东华.火用分析和能级分析.北京:科学出版社,1986. 1～3.
[85]清华大学建筑技术科学系. (2006大型公共建筑能耗调研实习汇报演示文稿)安定门国资委办公大楼建筑能耗调查与节能诊断—第一阶段报告[R]. 2006.
[86]清华大学建筑技术科学系. (2005年大型公共建筑能耗调研实习报告)国家统计局六里桥办公楼能耗诊断报告书[R]. 2005.
[87] Reinhart C F. Daysim softeware [CP]. http://irc.nrc-cnrc.gc.ca/ie/lighting /daylight/daysim_e.html -User Manual.
[88]陈红兵.办公建筑的天然采光与能耗分析[博士学位论文].天津:天津大学, 2004.
[89]国家质量技术监督局,中华人民共和国建设部. GB 50096-1999.住宅设计规范.北京:中国建筑工业出版社, 1999.
[90]朱莉娅.麦克莫罗.建筑设计速查手册.大连:大连理工大学出版社, 2008.
[91] Reinhart C F, Walkenhorst O. Validation of dynamic RADIANCE-based daylight simulations for a test office with external blinds. Energy and Buildings, 2001(33):683-697.
[92]中华人民共和国建设部,国家质量监督检验检疫总局. GB/T 50033-2001.建筑采光设计标准.北京:中国建筑工业出版社, 1999.
[93]雷英杰,张善文,李续武,周创明. Matlab遗传算法工具箱及应用.西安:西安电子科技大学出版社, 2005.
[94] The Mathworks, Inc. Matlab 7.0a software [CP]. http://www.mathworks.cn/.
[95] Chipperfield A, Fleming P, Pohlheim H, Fonseca C. Genetic algorithm Toolbox user’s guide. Dept. of Automatic Control and Systems Engineering, University of Sheffield.
[96]清华大学建筑科学系,中国气象局气象信息中心气象资料室.中国建筑热环境分析专用气象数据集.北京:中国建筑工业出版社, 2005.
[97] Koltai T, Terlaky T. The difference between the managerial andmathematic al interpretation of sensitivity analysis results in linear programming. International Journal of Production Economics, 2000, 65:257–274.