中文核心期刊
CSCD来源期刊
中国科技核心期刊
RCCSE中国核心学术期刊

重庆交通大学学报(自然科学版) ›› 2019, Vol. 38 ›› Issue (03): 91-96.DOI: 10.3969/j.issn.1674-0696.2019.03.14

• 交通运输工程 • 上一篇    下一篇

基于系统动力学的道路运输能源需求预测——以辽宁省为例

唐丽敏, 王艺澄, 王盼   

  1. (大连海事大学 交通运输工程学院,辽宁 大连 116026)
  • 收稿日期:2017-09-10 修回日期:2018-10-16 出版日期:2019-03-20 发布日期:2019-03-20
  • 作者简介:唐丽敏(1963—),女,辽宁大连人,教授,博士,主要从事交通运输工程方面的研究。E-mail: tlmin@dlmu.edu.cn。

Road Transport Energy Demand Forecasting Based on System Dynamics —— Taking Liaoning Province as an Example

TANG Limin, WANG Yicheng, WANG Pan   

  1. (School of Traffic & Transportation Engineering, Dalian Maritime University, Dalian 116026, Liaoning, P. R. China)
  • Received:2017-09-10 Revised:2018-10-16 Online:2019-03-20 Published:2019-03-20

摘要: 深入分析了辽宁省道路运输与经济、人口及能源子系统间的相互作用关系,构建了辽宁省道路运输能源需求系统动力学模型,并参照社会经济发展及道路运输相关规划目标,进行了预测与情景模拟。研究表明:2020年辽宁省道路运输能源需求量约1800万吨标准煤;“十三五”期间,辽宁省货运周转量年均增长2.38%,客运周转量年均增长4.2%;产业结构调整将改变能源需求量,第三产业比重增加5%时,能源需求量能够减少1.1%;营运货车单位周转量能源消耗量降低14.3%时,能源需求量可降低2.2%。

关键词: 交通运输工程, 道路运输, 能源需求量, 系统动力学, 预测, 情景模拟

Abstract: The interaction between road transportation and economic, population and energy subsystems in Liaoning province was analysed in depth, and the system dynamics model of energy demand for road transportation in Liaoning Province was established. In the light of the relevant planning objectives of social and economic development as well as road transportation, forecast and scenario simulation were carried out. The research results indicate that: firstly, the energy demand for road transportation in Liaoning province in 2020 is about 18 million tons of standard coal. The average annual growth rate of freight turnover and passenger turnover in Liaoning are 2.38% and 4.2% respectively in “thirteenth five-year plan” period. Secondly, the adjustment of industrial structure will change the energy demand. The energy demand can be reduced by 1.1%, when the proportion of the tertiary industry is increased by 5%. Thirdly, energy demand can be reduced by 2.2%, when the energy consumption per unit turnover of freight cars is reduced by 14.3%.

Key words: traffic and transportation engineering, road transport, energy demand, system dynamics, forecast, scenario simulation

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