城市典型生命线系统耦联多维测度方法研究
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摘要
以供热、电力、燃气系统为代表的典型生命线是城市运行的重要基础设施,其具有的系统耦联性往往会诱发系统运行异常的不良连锁效应。系统耦联测度研究对于识别城市典型生命线各系统之间的复杂耦联关系并优化其布局与运行具有重要意义。针对城市典型生命线系统耦联测度问题,首先以结构性、功能性和阶段性维度为切入点进行了系统耦联机理分析;然后提出了一种基于主客观信息的系统耦联多维测度方法,借助二元语义表示模型与决策试验和评价实验室(DEMATEL)法处理和集结各维度的主客观耦联信息,进而通过计算各系统的中心耦联度和关系耦联度来确定系统耦联的强弱和类型;最后应用所提方法测度了北京某样区内城市典型生命线的系统耦联性。结果表明:中心耦联度值最高的电力系统在系统耦联中发挥了显著作用;关系耦联度为负值的供热系统为结果型耦联系统,关系耦联度为正值的电力和燃气系统为原因型耦联系统;需要根据测度结果制定针对性的优化策略。
Urban typical lifelines,i.e.,heating,electricity and gas systems,are vital and basic infrastructures for urban operation.Coupling phenomena among these systems often induce the poor cascading effect of abnormal operation.Study on system coupling measurement is significant to identify the complex coupling relationships among systems of urban typical lifelines and to improve their placement and operation.In this paper,firstly,mechanism analysis on system coupling of urban typical lifelines is conducted from the structural,functional and phased dimensions.Then,a multi-dimensional measurement method for system coupling based on subjective and objective information is proposed.By processing and aggregating subjective and objective coupling information on these dimensions according to ideas of 2-tuple linguistic representation model as well as decision making trial and evaluation laboratory(DEMATEL),the prominence and relation couple degrees of each system are calculated to determine the coupling role and classification of each system.Finally,the proposed method is applied to conduct the multi-dimensional measurement for system coupling of urban typical lifeline in a sample area of Beijing.The results show that: 1) electricity system with the highest value of prominence coupling degree plays an important role in system coupling;2) heating system with the negative value of relation couple degree is an effect coupling system,while electricity and gas system with the positive value of relation couple degree is a cause coupling system;3) it is necessary to make targeted policies for optimizing the operation of urban typical lifeline according to the measurement results.
Urban typical lifelines,i.e.,heating,electricity and gas systems,are vital and basic infrastructures for urban operation.Coupling phenomena among these systems often induce the poor cascading effect of abnormal operation.Study on system coupling measurement is significant to identify the complex coupling relationships among systems of urban typical lifelines and to improve their placement and operation.In this paper,firstly,mechanism analysis on system coupling of urban typical lifelines is conducted from the structural,functional and phased dimensions.Then,a multi-dimensional measurement method for system coupling based on subjective and objective information is proposed.By processing and aggregating subjective and objective coupling information on these dimensions according to ideas of 2-tuple linguistic representation model as well as decision making trial and evaluation laboratory(DEMATEL),the prominence and relation couple degrees of each system are calculated to determine the coupling role and classification of each system.Finally,the proposed method is applied to conduct the multi-dimensional measurement for system coupling of urban typical lifeline in a sample area of Beijing.The results show that: 1) electricity system with the highest value of prominence coupling degree plays an important role in system coupling;2) heating system with the negative value of relation couple degree is an effect coupling system,while electricity and gas system with the positive value of relation couple degree is a cause coupling system;3) it is necessary to make targeted policies for optimizing the operation of urban typical lifeline according to the measurement results.
引文
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[2]李宏男,柳春光.生命线工程系统减灾研究趋势与展望[J].大连理工大学学报,2005,45(6):931-936.[Li Hongnan,LiuChunguang.Trends and Prospects for Research on Disaster Mitigationin Lifeline Engineering System[J].Journal of DaLian University ofTechnology,2005,45(6):931-936.]
[3]尤建新,陈桂香,陈强.城市生命线系统的非工程防灾减灾[J].自然灾害学报,2006,15(5):194-198.[You Jianxin,ChenGuixiang,Chen Qiang.Non-structural Disaster Prevention andReduction Measures of Urban Lifeline Systems[J].Journal ofNatural Disasters,2006,15(5):194-198.]
[4]刘惠敏.大型基础设施对地缘区人居环境的影响研究[J].中国人口.资源与环境,2011,21(11):139-145.[Liu Huimin.Effect Degree Modeling of Large-Scale Infrastructure to Geo-regionalHuman Settlements[J].China Population,Resources andEnvironment,2011,21(11):139-145.]
[5]Ouyang M,Dueas-Osorio L.An Approach to Design InterfaceTopologies Across Interdependent Urban Infrastructure Systems[J].Reliability Engineering and System Safety,2011,96(11):1462-1473.
[6]Min H S J,Beyeler W,Brown T,et al.Toward Modeling andSimulation of Critical National Infrastructure Interdependencies[J].Iie Transactions,2007,39(1):57-71.
[7]Torres-Vera M A,Canas J A.A lifeline Vulnerability Study inBarcelona,Spain[J].Reliability Engineering and System Safety,2003,80(2):205-210.
[8]Wang S L,Hong L,Chen X G.Vulnerability Analysis ofInterdependent Infrastructure Systems:A Methodological Framework[J].Physica A:Statistical Mechanics and its Applications,2012,391(11):3323-3335.
[9]Poljanek K,Bono F,Gutiérrez E.Seismic Risk Assessment ofInterdependent Critical Infrastructure Systems:The Case of EuropeanGas And Electricity Networks[J].Earthquake Engineering&Structural Dynamics,2012,41(1):61-79.
[10]陈卓淳,姚遂.中国电力系统低碳转型的路径探析[J].中国人口.资源与环境,2012,22(2):62-68.[Chen Zhuochun,YaoSui.Exploring Transition Pathways for a Decarbonized ElectricitySystem in China-Based on the Socio-Technical Transition Approach[J].China Population,Resources and Environment,2012,22(2):62-68.]
[11]姚保华,谢礼立,袁一凡.生命线系统相互作用及其分类[J].世界地震工程,2001,17(4):48-52.[Yao Baohua,Xie Lili,Yuan Yifan.Lifeline System Interaction and Its Classification[J].World Information on Earthquake Engineering,2001,17(4):48-52.]
[12]温瑞智,陶夏新,谢礼立.生命线系统的震害耦联[J].自然灾害学报,2000,9(2):105-110.[Wen Ruizhi,Tao Xiaxin,XieLili.Earthquake Damage Analysis of Coupling Lifeline Systems[J].Journal of Natural Disasters,2000,9(2):105-110.]
[13]Rinaldi S M,Peerenboom J P,Kelley T K.Identifying,Understanding,and Analyzing Critical Infrastructure Interdependencies[J].IEEEControl Systems Magazine,2001,21(6):11-25.
[14]Lee E E,Mitchell J E,Wallace W A.Restoration of Services inInterdependent Infrastructure Systems:A Network Flows Approach[J].IEEE Transactions on Systems,Man,and Cybernetics,PartC:Applications and Reviews,2007,37(6):1303-1317.
[15]Benoit R.A Method for the Study of Cascading Effects WithinLifeline Networks[J].International Journal of CriticalInfrastructures,2004,1(1):86-99.
[16]Dueas-Osorio L,Vemuru S M.Cascading Failures in ComplexInfrastructure Systems[J].Structural Safety,2009,31(2):157-167.
[17]Ouyang M,Hong L,Mao Z J,et al.A Methodological Approach toAnalyze Vulnerability of Interdependent Infrastructures[J].Simulation Modelling Practice and Theory,2009,12(5):817-828.
[18]张明媛,袁永博,李宏男.基于脆性理论的灾害作用下生命线系统耦联分析[J].防灾减灾工程学报,2009,29(4):462-466.[Zhang Mingyuan,Yuan Yongbo,Li Hongnan.Analysis ofthe Coupling of Lifeline Systems Based on Brittleness Theory UnderDisaster[J].Journal of Disaster Prevention and MitigationEngineering,2009,29(4):462-466.]
[19]Ge Y,Xing X T,Cheng Q M.Simulation and Analysis ofInfrastructure Interdependencies Using a Petri Net Simulator in aGeographical Information System[J].International Journal ofApplied Earth Observation and Geoinformation,2010,12(6):419-430.
[20]Johansson J,Hassel H.An Approach for Modeling InterdependentInfrastructures in the Context of Vulnerability Analysis[J].Reliability Engineering and System Safety,2010,95(12):1335-1344.
[21]Zhang P C,Peeta S.A Generalized Modeling Framework to AnalyzeInterdependencies Among Infrastructure Systems[J].Transportation Research,Part B:Methodological,2011,45(3):553-579.
[22]Herrera F,Martínez L.A 2-tuple Fuzzy Linguistic RepresentationModel for Computing with Words[J].IEEE Transactions on FuzzySystems,2000,8(6):746-752.
[23]Gabus A,Fontela E.World Problems,an Invitation to Furtherthought within the Framework of DEMATEL[R].SwitzerlandGeneva:Battelle Geneva Research Centre,1972.
[24]Papoulis A,Pillai S U.Probability,Random Variables,andStochastic Processes[M].New York:McGraw-Hill,2002.
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