基于完全分解模型的综合运输系统 能耗影响因素研究

交通运输系统工程与信息 ›› 2014, Vol. 14 ›› Issue (6): 15-20.

• 综合交通运输体系论坛 • 上一篇下一篇

基于完全分解模型的综合运输系统能耗影响因素研究

左大杰^*a,b,c，赵柯达^a,b,c，谢媛娣^a

西南交通大学a.交通运输与物流学院；b. 综合交通运输智能化国家地方联合工程实验室; c. 综合运输四川省重点实验室，成都610031

收稿日期:2014-06-30 修回日期:2014-08-21 出版日期:2014-12-25 发布日期:2014-12-30
作者简介:左大杰（1978－），男，副教授，博士.
基金资助:
西部交通战略与区域发展研究中心项目（XJQ010）；综合运输四川省重点实验室项目（B01A1202）；中央高校基本科研业务费专项资金科技创新项目（A0920502051413-108）.

Influencing Factors of Energy Consumption for Integrated Transportation System Based on Complete Decomposition Model

ZUO Da-jie^a,b,c, ZHAO Ke-da^a,b,c, XIE Yuan-di^a

a.School of Transportation and Logistics; b. Comprehensive Transportation Intelligent national local United Engineering Laboratory; c. Key Laboratory of Comprehensive Transportation of Sichuan Province, Southwest Jiaotong University, Chengdu 610031,China

Received:2014-06-30 Revised:2014-08-21 Online:2014-12-25 Published:2014-12-30

摘要/Abstract

摘要：

随着工业化和城市化程度的提高，交通与能源矛盾日益突出.现有研究认为运输业能源消耗与运输量、能源消耗强度有关，然而忽视了综合运输系统结构对能源消耗的影响.为了解综合运输系统能耗与运输量、能耗强度、运输系统结构三者的定性与定量关系，找出综合运输系统能耗快速增长的真正推动因素，本文以综合运输系统为研究对象，建立基于完全分解的综合运输系统能耗影响分析模型，将能耗的影响因素分解成系统结构、运输量、能源消耗强度三大因子，并对1995–2011 年的统计数据进行实例计算.研究发现，运输量的大量增加是运输业能耗显著增加的主要因素.但值得关注的是，运输结构对能源消耗的影响日益突出.所以，我国进一步构建综合运输系统时，应当做好各种运输方式在能耗方面的优势比较及合理的整体发展规划，使得各种运输方式协调发展.应该大力发展能源消耗率低且对环境影响小的铁路和水路运输.

关键词: 综合交通运输, 能耗分解, 完全分解模型, 综合运输系统, 能耗强度

Abstract:

The contradiction between transportation and energy increased with the development of industrialization and urbanization. Current research indicates that energy consumption of transportation are related with traffic volume and energy consumption intensity, however, neglecting impaction of system structure of integrated transportation. This paper takes the integrated transportation system as a research object, and the complete decomposition model is built up. The influencing factors of energy consumption is divided into three parts, traffic volume, energy consumption intensity and system structure of integrated transportation. A calculation example is gave based on the statistical data of 1995–2011, to discuss thequalitative and quantitative relationship between energy consumption of transportation and its influencing factors, and find out the main promotion factor that effects energy consumption increasing. By analyzing the data，we can draw the conclusion that the energy consumption of transportation increase significantly with the increase of traffic volume. But it is necessary to point out that the effects of transport structure become more and more outstanding. Therefore, when government constructing integrated transportation system, should analysis comparative advantage energy consumption of each transportation ways and make the whole developing planning to realize the coordination of transport modes. In particular, should greatly develop transportation of railway and waterway which are low energy consumption and little effect on environment.

Key words: integrated transportation, energy consumption decomposition, completely decomposition model, integrated transportation system, energy consumption intensity

中图分类号:

U491

左大杰，赵柯达，谢媛娣. 基于完全分解模型的综合运输系统能耗影响因素研究[J]. 交通运输系统工程与信息, 2014, 14(6): 15-20.

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链接本文: http://www.tseit.org.cn/CN/abstract/abstract18882.shtml

http://www.tseit.org.cn/CN/Y2014/V14/I6/15

参考文献

[1] XI Ji, CHEN G q. Exergy analysis of energy utilization in the transportation sector in China[J]. Energy Policy, 2006, 34(14): 1709-1719 .

[2] 李春荣．吉林省交通运输行业能源消耗分析与能源需求预测研究[D]．长春：吉林大学，2012. [Li C R.Research on energy consumption analysis and energy demand forecast of traffic transport industry in jilin province[D]. ChangChun: Jilin University, 2012.]
[3] Ediger V ?, Çamdali Ü. Energy and exergy efficiencies in Turkish transportation sector, 1988-2004[J]. Energy Policy, 2007, 35(2): 1238-1244.
[4] Saidur R, Sattar M A, Masjuki H H, et al. An estimation of the energy and exergy efficiencies for the energy resources consumption in the transportation sector in Malaysia[J]. Energy Policy, 2007, 35(8): 4018-4026.
[5] Myers J G, Nakamura L I. Saving energy in manufacturing: the post- embargo record[M]. United States: Ballinger Publishing Company, 1978.
[6] Sun J-w. Changes in energy consumption and energy intensity: A complete decomposition model[J]. Energy Economics, 1998, 20(1): 85-100.
[7] ZHOU Yang, ZONG Ke. Analysis of energy consumption in Shandong Province-Based on Complete Decomposition Model[J]. Energy Procedia, 2011, 5:1647-1653.
[8] LIU C. A stud on decomposition of industry energy consumption[J]. Wseas Transactions on Mathematics,2007, 6(6): 741-744.
[9] NING Y, DING T, TONOOKA Y. Feature analysis of Chinese energy consumption based on a complete decomposition model[C]//ICMREE 2011- Proceedings 2011 International Confer, 2．Shanghai, China, United States：IEEE Computer Society, 2011: 1313-1317.
[10] KANG R, YANG F, GUAN Y. Energy consumption reduction decomposition model based on input-output analysis and comprehensive evaluation[C]//2012 International Conference on Sustainable Energ．Guangzhou, China, Switzerland： Trans Tech Publications Ltd, 2013: 1221-1226.
[11] 姜秀山, 于立凯, 胡思继. 基于完全分解模型的能源消费变动及影响因素分析[J]. 北京交通大学学报(社会科学版), 2012, (3)：38-42. [JIANG X S, YU L K, HU S J. An analysis of changes and influnencing factors of energy consumption in China based on complete decomposition model[J]. Journal of Beijing Jiaotong University(Social Sciences Edition), 2012,(3):38-42. ]
[12] 李凯, 李明玉, 郁培丽, 等. 辽宁省能源消费的因素分解——基于完全分解模型[J]. 东北大学学报(自然科学版), 2007, 28(11)：1656-1659. [LI K, LI M Y, YU P L. Economic factors analysis based on complete decomposition modal for energy consumption in liaoning province[J]. Journal of Northeastern University(Natural Science), 2007,28(11):1656-1659. ]
[13] FULTON L, EADS. IEA/SMP model documentation and reference case projection [R], 2004.
[14] 孙启鹏，王庆云，毛保华. 不同交通方式能耗因子及其可比性研究框架设计[J]. 交通运输系统工程与信息, 2009,（9）4：10-14．[SUN Q P, WANG Q Y, MAO B H. Framework design of different tranportation modes' energy consunption factors and comparabilities study[J].Journal of Transportation Systems Engineering and Information Technology, 2009,9(4):10-14.]
[15] 毛保华，贾顺平，孙启鹏，等. 不同交通方式能耗因子及其可比性研究[R]. 北京交通大学中国综合交通研究中心, 2009． [MAO B H, JIA S P, SUN Q P, et al.Analysis of different tranportation modes' energy consunption factors and comparabilities[R]. Integrated Transport Research Center of China, Beijing Jiaotong University, 2009. ]
[16] IEA. Energy statistics and balances(1995- 2011) [DB/OL], 1995-2011.

基于完全分解模型的综合运输系统能耗影响因素研究

Influencing Factors of Energy Consumption for Integrated Transportation System Based on Complete Decomposition Model

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基于完全分解模型的综合运输系统 能耗影响因素研究

Influencing Factors of Energy Consumption for Integrated Transportation System Based on Complete Decomposition Model

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基于完全分解模型的综合运输系统能耗影响因素研究