使用者行为驱动的建筑节能途径探索
|
摘要
为挖掘使用者行为在建筑领域的节能潜力,本文讨论了行为因素相关的节能手段。重点阐述了基于行为干预的建筑节能途径。首先,建立行为干预研究框架,明确行为干预试验流程。其次,对比分析干预策略特征及适用范围。再次,建立行为干预模型,提出结合社会学理论的未知变量分析方法,描述博弈论、观点动力学理论及代理人模拟技术在定量分析模型中的应用。最后,提出本领域待解决的问题及建议。行为干预策略为政府制定节能政策提供参考,行为干预模型为智能建筑的绿色升级提供途径。研究成果与"绿色行动方案"结合,创建符合国情的建筑节能行为引导机制和绿色智能建筑体系,对建筑业节能减排,应对气候变化,具有积极的理论意义和应用价值。
In order to tap the energy-saving potential of occupants` behavior in building sector, the energy efficient measures related to behavioral factors are discussed in the paper. Approach to occupants' behavior driven energy efficiency of buildings is highlighted. Firstly, the behavioral intervention research framework is established and the behavioral intervention trial process is defined. Secondly, the characteristics of the intervention strategies and the applicable ranges are comparative analyzed. Thirdly, the behavior intervention model is set up. The combined with social science analysis method of unknown variables is suggested, and the applications of Game Theory, Opinion Dynamics Theory and Agent-Based modeling technology in quantitative analysis model are described. Finally, the problems and suggestions to be solved in this field are presented. Behavior intervention strategies are references for the government to formulate energy-saving policies, and the behavioral intervention models provide ways for the green upgrading of intelligent buildings. Research results being combined with the Green Action Plan, creating building energy conservation behavior guide mechanism conforming to the national conditions and the green intelligent building system have positive theoretical significance and application value for saving energy, cutting greenhouse gas emissions and fighting climate change.
In order to tap the energy-saving potential of occupants` behavior in building sector, the energy efficient measures related to behavioral factors are discussed in the paper. Approach to occupants' behavior driven energy efficiency of buildings is highlighted. Firstly, the behavioral intervention research framework is established and the behavioral intervention trial process is defined. Secondly, the characteristics of the intervention strategies and the applicable ranges are comparative analyzed. Thirdly, the behavior intervention model is set up. The combined with social science analysis method of unknown variables is suggested, and the applications of Game Theory, Opinion Dynamics Theory and Agent-Based modeling technology in quantitative analysis model are described. Finally, the problems and suggestions to be solved in this field are presented. Behavior intervention strategies are references for the government to formulate energy-saving policies, and the behavioral intervention models provide ways for the green upgrading of intelligent buildings. Research results being combined with the Green Action Plan, creating building energy conservation behavior guide mechanism conforming to the national conditions and the green intelligent building system have positive theoretical significance and application value for saving energy, cutting greenhouse gas emissions and fighting climate change.
引文
[1] 中国建筑节能协会能耗统计专委会. 中国建筑能耗研究报告[R]. 上海:中国建筑节能协会能耗统计专委会,2017
[2] 仇保兴. 我国绿色建筑发展和建筑节能的形势与任务[J]. 城市发展研究,2012,19(5):1-7,11
[3] 林波荣,肖娟,刘彦辰,等. 绿色建筑技术效果和运行性能后评估[J]. 世界建筑,2016,(6):28-33,126
[4] 路宾,宋业辉,曹勇,等. 我国绿色建筑运行维护存在的问题及对策[J]. 建筑科学,2015,31(8):46-50
[5] 屈利娟,沈小丽.基于能耗监测平台的高校典型建筑待机能耗分析[J]. 建筑节能,2016,44(1):90-93,101
[6] 陈淑琴,王之晗,廖航,等. 初探国内外高校建筑使用者用能行为及成因[J]. 建筑节能,2014,42(11):64-67,71
[7] Komor P, Kempton W, Haberl J. Energy Use, Information, and Behavior in Small Commercial Buildings[R]. Princeton: Center for Energy and Environmental Studies, 1989
[8] Haldi F, Cali D, Andersen R K, et al. Modelling diversity in building occupant behavior: a novel statistical approach[J] Journal of Building Performance Simulation, 2017, 10(6): 527-544
[9] Song K, Kwon N, Anderson K, et al. Predicting hourly energy consumption in buildings using occupancy-related characteristics of end-user groups[J]. Energy and Buildings, 2017,156: 121-133
[10] Gucyeter B. Evaluating diverse patterns of occupant behavior regarding control-based activities in energy performance simulation[J]. Frontiers of Architectural Research, 2018, 7 (2): 167-179
[11] 燕达, 丰晓航, 王闯,等. 建筑中人行为模拟研究现状和展望[J]. 建筑科学, 2015, 31(10):178-187
[12] 李兆坚,江亿,魏庆芃. 北京市某住宅楼夏季空调能耗调查分析[J].暖通空调,2007,37(4):46-51
[13] 贾媛,闫增峰. 基于灰关联分析的使用者行为对建筑能耗影响研究[J]. 建筑科学,2016,32(4):108-113
[14] 张志昆. 湿热地区住宅分体空调的人行为控制节能案例模拟研究[J]. 建筑科学,2018,34(4):19-24,77
[15] Allcott H, Mullainathan S. Behavior and Energy Policy[J]. Science, 2010, 327 (5970): 1204-1205
[16] Wilson T. The Power of Social Psychological Interventions[J]. Science, 2006, 313 (5791): 1251-1252
[17] Cohen G, Garcia J, Apfel N, et al. Reducing the racial achievement gap: a social-psychological intervention[J]. Science, 2006, 313 (5791): 1307
[18] Harzem P. Watson John Broadus (1878-1958)[J]. International Encyclopedia of the Social & Behavioral Sciences, 2001,(2001):16389-16391
[19] Kok G, Lo S, Peters G, et al. Changing energy-related behavior: An Intervention Mapping approach[J]. Energy Policy, 2011, 39 (9): 5280-5286
[20] Richler J. Energy Conservation Behavior: Savings Without Billing[J]. Nature Energy, 2016,1 (12): 16199
[21] Shen M, Cui Q, Young B. The normative feedback approach for energy conservation behavior in the military community[J]. Energy Policy, 2016, 98: 19-32
[22] 芈凌云,杨洁,俞学燕,等. 信息型策略对居民节能行为的干预效果研究——基于Meta分析[J]. 软科学,2016,30(04):89-92
[23] Khosrowpour A, Xie Y, Taylor J, et al. One size does not fit all: Establishing the need for targeted eco-feedback[J]. Applied Energy, 2016, 184 (12):523-530
[24] Anderson K, Lee S. Modeling occupant energy use interventions in evolving social networks[C]// Proceedings of the 2013 Winter Simulation Conference. Washington DC. USA.: 2013: 3051-3058
[25] Jain R, Taylor J, Peschiera G. Assessing eco-feedback interface usage and design to drive energy efficiency in buildings[J]. Energy and Buildings, 2012, 48 (01): 8-17
[26] Chen H, Lin C, Heieh S, et al. Persuasive feedback model for inducing energy conservation behaviors of building users based on interaction with a virtual object[J]. Energy and Buildings, 2012, 45 (2): 106-115
[27] Cornelius M, Armel K, Hoffman K, et al. Increasing energy- and greenhouse gas-saving behaviors among adolescents: a school-based cluster-randomized controlled trial[J]. Energy Efficiency, 2014, 7 (2): 217-242
[28] Deci E, Koestner R, Ryan R. A Meta-Analytic Review of Experiments Examining the Effects of Extrinsic Rewards on Intrinsic Motivation[J]. Psychological Bulletin, 1999, 125 (6): 627-668
[29] Marker A, Staiano A. Better Together: Outcomes of Cooperation Versus Competition in Social Exergaming[J]. Games for Health, 2015, 4 (1): 25-30
[30] Sussman R, Chikumbo M. Behavior Change Programs: Status and Impact American Council for an Energy-Efficient Economy[R]. Washington DC: 2016
[31] Barbu A, Griffiths N, Morton G. Achieving energy efficiency through behavior change: what does it take? [R]. Denmark: European Environment Agency, 2013
[32] D`Oca S, Chen C, Hong T, et al. Synthesizing building physics with social psychology: An interdisciplinary framework for context and occupant behavior in office buildings[J]. Energy Research & Social Science, 2017, 34: 240-251
[33] Lo S, Peters G, Breukelen G, et al. Only reasoned action? An inter-organizational study of energy-saving behaviors in office buildings[J]. Energy Efficiency, 2014, 7 (5): 761-775
[34] Stazi F, Naspi F, D'Orazio M. A literature review on driving factors and contextual events influencing occupants' behaviors in buildings[J]. Building and Environment, 2017, 118: 40-66
[35] Ratliff L, Jin M, Konstantakopoulos I, et al. Social game for building energy efficiency: Incentive design[C]// Fifty-second Annual Allerton Conference Communication, Control, and Computing IEEE. Illinois USA.: 2014: 1011-1018
[36] Shen M, Cui Q, Fu L. Personality traits and energy conservation[J]. Energy Policy, 2015, 85: 322-334
[37] Deffuant G, Neau D, Amblard F, et al. Mixing beliefs among interacting agents[J]. Advances in Complex Systems, 2000, 3 (01n04): 87-98
[38] Azar E, Menassa C. Framework to Evaluate Energy-Saving Potential from Occupancy Interventions in Typical Commercial Buildings in the United States[J]. Journal of Computing in Civil Engineering, 2014, 28 (1): 63-78
[2] 仇保兴. 我国绿色建筑发展和建筑节能的形势与任务[J]. 城市发展研究,2012,19(5):1-7,11
[3] 林波荣,肖娟,刘彦辰,等. 绿色建筑技术效果和运行性能后评估[J]. 世界建筑,2016,(6):28-33,126
[4] 路宾,宋业辉,曹勇,等. 我国绿色建筑运行维护存在的问题及对策[J]. 建筑科学,2015,31(8):46-50
[5] 屈利娟,沈小丽.基于能耗监测平台的高校典型建筑待机能耗分析[J]. 建筑节能,2016,44(1):90-93,101
[6] 陈淑琴,王之晗,廖航,等. 初探国内外高校建筑使用者用能行为及成因[J]. 建筑节能,2014,42(11):64-67,71
[7] Komor P, Kempton W, Haberl J. Energy Use, Information, and Behavior in Small Commercial Buildings[R]. Princeton: Center for Energy and Environmental Studies, 1989
[8] Haldi F, Cali D, Andersen R K, et al. Modelling diversity in building occupant behavior: a novel statistical approach[J] Journal of Building Performance Simulation, 2017, 10(6): 527-544
[9] Song K, Kwon N, Anderson K, et al. Predicting hourly energy consumption in buildings using occupancy-related characteristics of end-user groups[J]. Energy and Buildings, 2017,156: 121-133
[10] Gucyeter B. Evaluating diverse patterns of occupant behavior regarding control-based activities in energy performance simulation[J]. Frontiers of Architectural Research, 2018, 7 (2): 167-179
[11] 燕达, 丰晓航, 王闯,等. 建筑中人行为模拟研究现状和展望[J]. 建筑科学, 2015, 31(10):178-187
[12] 李兆坚,江亿,魏庆芃. 北京市某住宅楼夏季空调能耗调查分析[J].暖通空调,2007,37(4):46-51
[13] 贾媛,闫增峰. 基于灰关联分析的使用者行为对建筑能耗影响研究[J]. 建筑科学,2016,32(4):108-113
[14] 张志昆. 湿热地区住宅分体空调的人行为控制节能案例模拟研究[J]. 建筑科学,2018,34(4):19-24,77
[15] Allcott H, Mullainathan S. Behavior and Energy Policy[J]. Science, 2010, 327 (5970): 1204-1205
[16] Wilson T. The Power of Social Psychological Interventions[J]. Science, 2006, 313 (5791): 1251-1252
[17] Cohen G, Garcia J, Apfel N, et al. Reducing the racial achievement gap: a social-psychological intervention[J]. Science, 2006, 313 (5791): 1307
[18] Harzem P. Watson John Broadus (1878-1958)[J]. International Encyclopedia of the Social & Behavioral Sciences, 2001,(2001):16389-16391
[19] Kok G, Lo S, Peters G, et al. Changing energy-related behavior: An Intervention Mapping approach[J]. Energy Policy, 2011, 39 (9): 5280-5286
[20] Richler J. Energy Conservation Behavior: Savings Without Billing[J]. Nature Energy, 2016,1 (12): 16199
[21] Shen M, Cui Q, Young B. The normative feedback approach for energy conservation behavior in the military community[J]. Energy Policy, 2016, 98: 19-32
[22] 芈凌云,杨洁,俞学燕,等. 信息型策略对居民节能行为的干预效果研究——基于Meta分析[J]. 软科学,2016,30(04):89-92
[23] Khosrowpour A, Xie Y, Taylor J, et al. One size does not fit all: Establishing the need for targeted eco-feedback[J]. Applied Energy, 2016, 184 (12):523-530
[24] Anderson K, Lee S. Modeling occupant energy use interventions in evolving social networks[C]// Proceedings of the 2013 Winter Simulation Conference. Washington DC. USA.: 2013: 3051-3058
[25] Jain R, Taylor J, Peschiera G. Assessing eco-feedback interface usage and design to drive energy efficiency in buildings[J]. Energy and Buildings, 2012, 48 (01): 8-17
[26] Chen H, Lin C, Heieh S, et al. Persuasive feedback model for inducing energy conservation behaviors of building users based on interaction with a virtual object[J]. Energy and Buildings, 2012, 45 (2): 106-115
[27] Cornelius M, Armel K, Hoffman K, et al. Increasing energy- and greenhouse gas-saving behaviors among adolescents: a school-based cluster-randomized controlled trial[J]. Energy Efficiency, 2014, 7 (2): 217-242
[28] Deci E, Koestner R, Ryan R. A Meta-Analytic Review of Experiments Examining the Effects of Extrinsic Rewards on Intrinsic Motivation[J]. Psychological Bulletin, 1999, 125 (6): 627-668
[29] Marker A, Staiano A. Better Together: Outcomes of Cooperation Versus Competition in Social Exergaming[J]. Games for Health, 2015, 4 (1): 25-30
[30] Sussman R, Chikumbo M. Behavior Change Programs: Status and Impact American Council for an Energy-Efficient Economy[R]. Washington DC: 2016
[31] Barbu A, Griffiths N, Morton G. Achieving energy efficiency through behavior change: what does it take? [R]. Denmark: European Environment Agency, 2013
[32] D`Oca S, Chen C, Hong T, et al. Synthesizing building physics with social psychology: An interdisciplinary framework for context and occupant behavior in office buildings[J]. Energy Research & Social Science, 2017, 34: 240-251
[33] Lo S, Peters G, Breukelen G, et al. Only reasoned action? An inter-organizational study of energy-saving behaviors in office buildings[J]. Energy Efficiency, 2014, 7 (5): 761-775
[34] Stazi F, Naspi F, D'Orazio M. A literature review on driving factors and contextual events influencing occupants' behaviors in buildings[J]. Building and Environment, 2017, 118: 40-66
[35] Ratliff L, Jin M, Konstantakopoulos I, et al. Social game for building energy efficiency: Incentive design[C]// Fifty-second Annual Allerton Conference Communication, Control, and Computing IEEE. Illinois USA.: 2014: 1011-1018
[36] Shen M, Cui Q, Fu L. Personality traits and energy conservation[J]. Energy Policy, 2015, 85: 322-334
[37] Deffuant G, Neau D, Amblard F, et al. Mixing beliefs among interacting agents[J]. Advances in Complex Systems, 2000, 3 (01n04): 87-98
[38] Azar E, Menassa C. Framework to Evaluate Energy-Saving Potential from Occupancy Interventions in Typical Commercial Buildings in the United States[J]. Journal of Computing in Civil Engineering, 2014, 28 (1): 63-78