走向居住社区绿色性能多要素协同优化
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摘要
在建筑单体绿色性能分析和节能技术不断发展的今天,可持续城市和绿色建筑的目标仍然任重道远。对城镇居住社区建设而言,绿色性能的问题远不止是将单体建筑最优化绿色性能简单叠加,城市街区尺度下复杂多元要素的协同优化还存在着广泛的挖潜空间。通过对国内外可持续城市和绿色建筑前沿研究的分析,认为目前学界出现的关于多要素协同计算元模型的概念是符合设计思维的源头创新工具,以期对推动绿色建筑的研究起到一定的启发作用。
Though the green performance analysis of individual building and energy saving technology reach to a high level nowadays, we realize that the goal of sustainable city and green building is still a long way to go. In terms of urban residential buildings, the issue of green performance of residential areas is far from a simple superposition of the optimized green performance of different individual buildings. There's still a wide potential for collaborative optimization of complex multiple elements in the urban scale. Based on the analysis of the recent research on sustainable cities and green buildings, this paper puts forward that the concept of multi-factor collaborative computing meta-model is the original innovation tool in accordance with the design thinking. In order to play a certain role in enlightening to promote the research of green building.
Though the green performance analysis of individual building and energy saving technology reach to a high level nowadays, we realize that the goal of sustainable city and green building is still a long way to go. In terms of urban residential buildings, the issue of green performance of residential areas is far from a simple superposition of the optimized green performance of different individual buildings. There's still a wide potential for collaborative optimization of complex multiple elements in the urban scale. Based on the analysis of the recent research on sustainable cities and green buildings, this paper puts forward that the concept of multi-factor collaborative computing meta-model is the original innovation tool in accordance with the design thinking. In order to play a certain role in enlightening to promote the research of green building.
引文
[1]绿色建筑评价标准:GB/T 50378-2014[S].北京:中国建筑工业出版社,2014.
[2]秦佑国,林波荣,朱颖心.中国绿色建筑评估体系研究[J].建筑学报,2007(3):68-71.
[3]USGBC.LEED v4 for Building Design and Construction[EB/OL].2018-11-02.
[4]李王鸣,刘吉平.精明、健康、绿色的可持续住区规划愿景--美国LEED-ND评估体系研究[J].国际城市规划,2011(5):66-70.
[5]民用建筑能耗标准:GB/T 51161-2016[S].北京:中国建筑工业出版社,2016.
[6]夏热冬冷地区居住建筑节能设计标准:JGJ 134-2010[S].北京:中国建筑工业出版社,2010.
[7]民用建筑绿色设计规范:JGJ/T 229-2010[S].北京:中国建筑工业出版社,2010.
[8]居住建筑节能设计标准:DGJ08-205-2015[S].上海:同济大学出版社,2015.
[9]住宅建筑绿色设计标准:DGJ08-2139-2014[S].上海:同济大学出版社,2014.
[10]江亿.我国建筑耗能状况及有效的节能途径[J].工程质量,2005(8).
[11]Fanger P.O.Fundamentals of thermal comfort[C]//Bloss W.h.,Pfisterer F.Advances in Solar Energy Technology.Oxford:Pergamon,1988:3056-3061.
[12]Chenari B,Carrilho J D,da Silva M G.Towards sustainable,energy-efficient and healthy ventilation strategies in buildings:A review[J].Renewable and Sustainable Energy Reviews,2016,59:1426-1447.
[13]Larsen T S,Heiselberg P.Single-sided natural ventilation driven by wind pressure and temperature difference[J].Energy and Buildings,2008,40(6):1031-1040.
[14]Jing H,Chen Z,Li A.Experimental study of the prediction of the ventilation flow rate through solar chimney with large gap-to-height ratios[J].Building and Environment,2015,89:150-159.
[15]Moosavi L,Mahyuddin N,Ab Ghafar N,et al.Thermal performance of atria:an overview of natural ventilation effective designs[J].Renewable and Sustainable Energy Reviews,2014,34:654-670.
[16]Gros A,Bozonnet E,Inard C,et al.Simulation tools to assess microclimate and building energy:a case study on the design of a new district[J].Energy and Buildings,2016,114:112-122.
[17]李麟学,季天裔.基于环境应变的绿色住区设计路径解析[J].住宅科技,2011(7):11-14.
[18]王静,周璐,郭夏清.绿色建筑设计中被动设计与性能工具的应用思路与策略研究[J].华中建筑,2014,32(8):88-95.
[19]Harvey Bernstein,Stephen Jones,Michele Russo.Green BIM:how building information modeling is contributing to green design and construction[J].Journal of Information Technology in Civil Engineering and Architecture,2015(2).
[20]何关陪.BIM总论[M].北京:中国建筑工业出版社,2011.
[21]李宝鑫,张津奕,刘军,等.基于BIM的建筑可持续设计方法研究与实践[J].绿色建筑,2015(3):67-71.
[22]中国气象局气象信息中心气象资料室,清华大学建筑技术科学系.中国建筑热环境分析专用气象数据集[M].北京:中国建筑工业出版社,2005.
[23]张晴原,Huang J.中国建筑用标准气象数据集[M].北京:中国建筑工业出版社,2004.
[24]Oke T.R.Boundary layer climates[M].London:Routledge,2002.
[25]杨小山,赵立华,孟庆林.城市微气候模拟数据在建筑能耗计算中的应用[J].太阳能学报,2015,36(6):1344-1351.
[26]Bruse M.,Fleer H.Simulating surface-plantair interactions inside urban environments with a three dimensional numerical model[J].Environmental Modelling&Software,1998,13(3):373-384.
[27]冯晶琛,丁云飞,吴会军.EnergyPlus能耗模拟软件及其应用工具[J].建筑节能,2012(1):64-67.
[28]叶海,杨峰.从量化指标到模拟验证--绿色建筑设计中的环境模拟应用[C]//孙澄,邢凯,夏楠,等.模拟·编码·协同:2012年全国建筑院系建筑数字技术教学研讨会论文集.北京:中国建筑工业出版社,2012.
[29]潘毅群,左明明,李玉明.建筑能耗模拟--绿色建筑设计与建筑节能改造的支持工具之一:基本原理与软件[J].制冷与空调,2008,22(3):10-16.
[30]燕达,谢晓娜,宋芳婷,等.建筑环境设计模拟分析软件DeST--第一讲建筑模拟技术与DeST发展简介[J].暖通空调,2004,34(7):48-56.
[31]杨小山,赵立华.城市微气候对建筑能耗影响的研究方法综述[J].建筑科学,2015,31(12):1-7.
[32]Han S.G.,Mun S.H.,Huh J.H.Changes of the microclimate and building cooling load due to the green effect of a restored stream in Seoul,Korea[C]//Proceedings of Building Simulation.Beijing:Tsinghua Press,2008.
[33]Hsieh C.M.,Aramaki T.,Hanaki K.The feedback of heat rejection to air conditioning load during the nighttime in subtropical climate[J].Energy and Buildings,2007,39(11):1175-1182.
[34]Bouyer J.,Inard C.,Musy M.Microclimatic coupling as a solution to improve building energy simulation in an urban context[J].Energy and Buildings,2011,43(7):1549-1559.
[35]黄媛.夏热冬冷地区基于节能的气候适应性街区城市设计方法论研究[D].武汉:华中科技大学,2010.
[36]陈卓伦.绿化体系对湿热地区建筑组团室外热环境影响研究[D].广州:华南理工大学,2010.
[37]Yi C.Y.,Peng C.Microclimate change outdoor and indoor coupled simulation for passive building adaptation design[J].Procedia Computer Science,2014,32:691-698.
[38]杨小山.室外微气候对建筑空调能耗影响的模拟方法研究[D].广州:华南理工大学,2012.
[39]Norford L.K.Genetic algorithms for optimization of building envelopes and the design and control of HVACsystems[J].Journal Of Solar Energy Engineering,2003,125:343-351.
[40]Wang W,Zmeureanu R.,Rivard H.Applying multiobjective genetic algorithms in green building design optimization[J].Building and Environment,2005,40(11):1512-1525.
[41]Wright J.A.,Loosemore H.A.,Farmani R.Optimization of building thermal design and control by multi-criterion genetic algorithm[J].Energy and Buildings,2002,34(9):959-972.
[42]Djuric N.,Novakovic V.,Holst J.,et al.Optimization of energy consumption in buildings with hydronic heating systems considering thermal comfort by use of computer-based tools[J].Energy and Buildings,2007,39(4):471-477.
[43]Peippo K.,Lund P.D.,Vartiainen E.Multivariate optimization of design trade-offs for solar low energy buildings[J].Energy and Buildings,1999,29(2):189-205.
[44]Tian W,Choudhary R.,Augenbroe G.,et al.Importance analysis and meta-model construction with correlated variables in evaluation of thermal performance of campus buildings[J].Building and Environment,2015,92:61-74.
[45]Dong B,Cao C,Lee S E.Applying support vector machines to predict building energy consumption in tropical region[J].Energy and Buildings,2005,37(5):545-553.
[46]Eisenhower B.,O’Neill Z.,Narayanan S.,et al.Amethodology for meta-model based optimization in building energy models[J].Energy and Buildings,2012,47:292-301.
[47]?sterg?rd T.,Jensen R.L.,Maagaard S.E.Building simulations supporting decision making in early designA review[J].Renewable and Sustainable Energy Reviews,2016,61:187-201.
[48]Manfren M.,Aste N.,Moshksar R.Calibration and uncertainty analysis for computer models:a meta-mode based approach for integrated building energy simulation[J].Applied Energy,2013,103:627-641.
[49]Campolongo F.,Cariboni J.,Saltelli A.An effective screening design for sensitivity analysis of large models[J].Environmental Modelling&Software,2007,22(10):1509-1518.
[50]Mara T.A.,Tarantola S.Application of global sensitivity analysis of model output to building thermal simulations[C]//Proceedings of Building Simulation.Beijing:Tsinghua Press,2008.
[51]Eisenhower B.,O'Neill Z.,Fonoberov V.A.,et al.Uncertainty and sensitivity decomposition of building energy models[J].Journal of Building Performance Simulation,2012(3):171-184.
[52]Tian W.A review of sensitivity analysis methods in building energy analysis[J].Renewable and Sustainable Energy Reviews,2013,20:411-419.
[53]Sch?lkopf B.,Smola A.J.Learning with kernels:support vector machines,regularization,optimization and beyond[M].Massachusetts:MIT press,2002.
[2]秦佑国,林波荣,朱颖心.中国绿色建筑评估体系研究[J].建筑学报,2007(3):68-71.
[3]USGBC.LEED v4 for Building Design and Construction[EB/OL].2018-11-02.
[4]李王鸣,刘吉平.精明、健康、绿色的可持续住区规划愿景--美国LEED-ND评估体系研究[J].国际城市规划,2011(5):66-70.
[5]民用建筑能耗标准:GB/T 51161-2016[S].北京:中国建筑工业出版社,2016.
[6]夏热冬冷地区居住建筑节能设计标准:JGJ 134-2010[S].北京:中国建筑工业出版社,2010.
[7]民用建筑绿色设计规范:JGJ/T 229-2010[S].北京:中国建筑工业出版社,2010.
[8]居住建筑节能设计标准:DGJ08-205-2015[S].上海:同济大学出版社,2015.
[9]住宅建筑绿色设计标准:DGJ08-2139-2014[S].上海:同济大学出版社,2014.
[10]江亿.我国建筑耗能状况及有效的节能途径[J].工程质量,2005(8).
[11]Fanger P.O.Fundamentals of thermal comfort[C]//Bloss W.h.,Pfisterer F.Advances in Solar Energy Technology.Oxford:Pergamon,1988:3056-3061.
[12]Chenari B,Carrilho J D,da Silva M G.Towards sustainable,energy-efficient and healthy ventilation strategies in buildings:A review[J].Renewable and Sustainable Energy Reviews,2016,59:1426-1447.
[13]Larsen T S,Heiselberg P.Single-sided natural ventilation driven by wind pressure and temperature difference[J].Energy and Buildings,2008,40(6):1031-1040.
[14]Jing H,Chen Z,Li A.Experimental study of the prediction of the ventilation flow rate through solar chimney with large gap-to-height ratios[J].Building and Environment,2015,89:150-159.
[15]Moosavi L,Mahyuddin N,Ab Ghafar N,et al.Thermal performance of atria:an overview of natural ventilation effective designs[J].Renewable and Sustainable Energy Reviews,2014,34:654-670.
[16]Gros A,Bozonnet E,Inard C,et al.Simulation tools to assess microclimate and building energy:a case study on the design of a new district[J].Energy and Buildings,2016,114:112-122.
[17]李麟学,季天裔.基于环境应变的绿色住区设计路径解析[J].住宅科技,2011(7):11-14.
[18]王静,周璐,郭夏清.绿色建筑设计中被动设计与性能工具的应用思路与策略研究[J].华中建筑,2014,32(8):88-95.
[19]Harvey Bernstein,Stephen Jones,Michele Russo.Green BIM:how building information modeling is contributing to green design and construction[J].Journal of Information Technology in Civil Engineering and Architecture,2015(2).
[20]何关陪.BIM总论[M].北京:中国建筑工业出版社,2011.
[21]李宝鑫,张津奕,刘军,等.基于BIM的建筑可持续设计方法研究与实践[J].绿色建筑,2015(3):67-71.
[22]中国气象局气象信息中心气象资料室,清华大学建筑技术科学系.中国建筑热环境分析专用气象数据集[M].北京:中国建筑工业出版社,2005.
[23]张晴原,Huang J.中国建筑用标准气象数据集[M].北京:中国建筑工业出版社,2004.
[24]Oke T.R.Boundary layer climates[M].London:Routledge,2002.
[25]杨小山,赵立华,孟庆林.城市微气候模拟数据在建筑能耗计算中的应用[J].太阳能学报,2015,36(6):1344-1351.
[26]Bruse M.,Fleer H.Simulating surface-plantair interactions inside urban environments with a three dimensional numerical model[J].Environmental Modelling&Software,1998,13(3):373-384.
[27]冯晶琛,丁云飞,吴会军.EnergyPlus能耗模拟软件及其应用工具[J].建筑节能,2012(1):64-67.
[28]叶海,杨峰.从量化指标到模拟验证--绿色建筑设计中的环境模拟应用[C]//孙澄,邢凯,夏楠,等.模拟·编码·协同:2012年全国建筑院系建筑数字技术教学研讨会论文集.北京:中国建筑工业出版社,2012.
[29]潘毅群,左明明,李玉明.建筑能耗模拟--绿色建筑设计与建筑节能改造的支持工具之一:基本原理与软件[J].制冷与空调,2008,22(3):10-16.
[30]燕达,谢晓娜,宋芳婷,等.建筑环境设计模拟分析软件DeST--第一讲建筑模拟技术与DeST发展简介[J].暖通空调,2004,34(7):48-56.
[31]杨小山,赵立华.城市微气候对建筑能耗影响的研究方法综述[J].建筑科学,2015,31(12):1-7.
[32]Han S.G.,Mun S.H.,Huh J.H.Changes of the microclimate and building cooling load due to the green effect of a restored stream in Seoul,Korea[C]//Proceedings of Building Simulation.Beijing:Tsinghua Press,2008.
[33]Hsieh C.M.,Aramaki T.,Hanaki K.The feedback of heat rejection to air conditioning load during the nighttime in subtropical climate[J].Energy and Buildings,2007,39(11):1175-1182.
[34]Bouyer J.,Inard C.,Musy M.Microclimatic coupling as a solution to improve building energy simulation in an urban context[J].Energy and Buildings,2011,43(7):1549-1559.
[35]黄媛.夏热冬冷地区基于节能的气候适应性街区城市设计方法论研究[D].武汉:华中科技大学,2010.
[36]陈卓伦.绿化体系对湿热地区建筑组团室外热环境影响研究[D].广州:华南理工大学,2010.
[37]Yi C.Y.,Peng C.Microclimate change outdoor and indoor coupled simulation for passive building adaptation design[J].Procedia Computer Science,2014,32:691-698.
[38]杨小山.室外微气候对建筑空调能耗影响的模拟方法研究[D].广州:华南理工大学,2012.
[39]Norford L.K.Genetic algorithms for optimization of building envelopes and the design and control of HVACsystems[J].Journal Of Solar Energy Engineering,2003,125:343-351.
[40]Wang W,Zmeureanu R.,Rivard H.Applying multiobjective genetic algorithms in green building design optimization[J].Building and Environment,2005,40(11):1512-1525.
[41]Wright J.A.,Loosemore H.A.,Farmani R.Optimization of building thermal design and control by multi-criterion genetic algorithm[J].Energy and Buildings,2002,34(9):959-972.
[42]Djuric N.,Novakovic V.,Holst J.,et al.Optimization of energy consumption in buildings with hydronic heating systems considering thermal comfort by use of computer-based tools[J].Energy and Buildings,2007,39(4):471-477.
[43]Peippo K.,Lund P.D.,Vartiainen E.Multivariate optimization of design trade-offs for solar low energy buildings[J].Energy and Buildings,1999,29(2):189-205.
[44]Tian W,Choudhary R.,Augenbroe G.,et al.Importance analysis and meta-model construction with correlated variables in evaluation of thermal performance of campus buildings[J].Building and Environment,2015,92:61-74.
[45]Dong B,Cao C,Lee S E.Applying support vector machines to predict building energy consumption in tropical region[J].Energy and Buildings,2005,37(5):545-553.
[46]Eisenhower B.,O’Neill Z.,Narayanan S.,et al.Amethodology for meta-model based optimization in building energy models[J].Energy and Buildings,2012,47:292-301.
[47]?sterg?rd T.,Jensen R.L.,Maagaard S.E.Building simulations supporting decision making in early designA review[J].Renewable and Sustainable Energy Reviews,2016,61:187-201.
[48]Manfren M.,Aste N.,Moshksar R.Calibration and uncertainty analysis for computer models:a meta-mode based approach for integrated building energy simulation[J].Applied Energy,2013,103:627-641.
[49]Campolongo F.,Cariboni J.,Saltelli A.An effective screening design for sensitivity analysis of large models[J].Environmental Modelling&Software,2007,22(10):1509-1518.
[50]Mara T.A.,Tarantola S.Application of global sensitivity analysis of model output to building thermal simulations[C]//Proceedings of Building Simulation.Beijing:Tsinghua Press,2008.
[51]Eisenhower B.,O'Neill Z.,Fonoberov V.A.,et al.Uncertainty and sensitivity decomposition of building energy models[J].Journal of Building Performance Simulation,2012(3):171-184.
[52]Tian W.A review of sensitivity analysis methods in building energy analysis[J].Renewable and Sustainable Energy Reviews,2013,20:411-419.
[53]Sch?lkopf B.,Smola A.J.Learning with kernels:support vector machines,regularization,optimization and beyond[M].Massachusetts:MIT press,2002.