【作者】 冯旭杰；

【导师】 孙全欣；

【作者基本信息】 北京交通大学 ， 交通运输规划与管理， 2014， 博士

【摘要】 高速铁路作为快速、大运量的城市间公共交通运输方式,能够较好地解决国内人口较多以及人均资源不足的矛盾。近年来,在国家政策支持下,高速铁路建设速度明显加快。然而,高速铁路基础设施建设工程量大、高速列车行驶的电力消耗高,特别是国内“以桥代路”的高速铁路建设思想和仍然以效率较低、排放较高的煤电为主的电力生产结构,导致从生命周期的角度重新审视高速铁路的环境影响具有重要的现实意义。为实现该目的,以环境影响中的能源消耗和碳排放为对象,在总结生命周期视角下高速铁路能源消耗和碳排放特征的基础上,提出高速铁路基础设施建设阶段的能源消耗和碳排放的分析框架和测算方法。基于机械做功,构建运营阶段高速列车牵引能耗的数值计算模型。从生命周期的视角,评估高速铁路的节能和碳减排效果。最后,从节能目标出发,建立了高速列车的运行速度优化模型。主要研究内容和结论如下：(1)将高速铁路按全生命周期划分为设计、建设、运营、维护和拆解5个阶段,分析了各阶段的典型活动。总结了生命周期视角下高速铁路的能源消耗和碳排放特征：第一,转移性,即以电力为主要能源的运营阶段的典型活动不直接造成碳排放,而是转移到了上游电力生产过程中；第二,隐藏性,即大规模基础设施建设导致高速铁路全生命周期的能源消耗和碳排放有较大比重隐藏在建设阶段。而不同地区高速铁路的生命周期评估结果具有明显的地域性特征：虽然不同地区的评估结果都表明建设阶段和运营阶段是全生命周期中能源消耗和碳排放的主要阶段,但建设阶段和运营阶段的相对比重在不同地区之间差异较大。(2)将高速铁路拆分成桥涵、隧道、路基、轨道和电气化系统5个子模型,通过计算各子模型的建筑材料使用总量和建设设备运转时间,结合具有地域性特征的生产数据清单,测算高速铁路建设阶段的能源消耗和碳排放。对京沪高速铁路的应用结果表明：京沪高速铁路建设造成的能源消耗为145502TJ,引起的碳排放为19154Kt C02e,两者90%以上都来自建筑材料使用。建设单位里程的隧道所造成的能源消耗最大,引起的碳排放也最多,分别是排名第2位的桥涵的1.9和1.7倍。不过,由于京沪高速铁路高达86%的桥涵比重,导致其建设能源消耗的67%和碳排放的66%来源于桥涵建设。水泥和钢材是影响高速铁路建设碳排放的显著要素,若两者生命周期碳排放系数分别降低20%,则高速铁路建设碳排放总量可以分别降低13%和7%。(3)基于机械做功,构建了高速列车牵引能耗的数值计算模型。模型兼顾高速列车因停站间距过短而达不到预定速度目标值的情形,通过引入发动机传动效率,提出在列车牵引力或电流曲线缺失条件下,能够满足一定精度要求的牵引能耗计算模型。模型表明,速度目标值对牵引能耗的影响主要表现在加速到的峰值上,从200到350km/h,不同停站方案下列车牵引能耗关于速度目标值的弹性系数为1.8-2.1。停站次数对牵引能耗的影响主要表现在加速的周期上,在169km、共9个客运站的高速铁路上运行的站站停列车的牵引能耗约是直达列车的1.7倍。(4)采用概率理论和蒙特卡洛方法评估了生命周期视角下高速铁路的节能和碳减排效果。以三角形分布描述客运方式的能源消耗强度和座位利用率及燃料(包括电力)生命周期能源消耗系数和碳排放系数的不确定性,以均匀分布描述客流转移比例的不确定性,在高速铁路客流发育的皮尔生长曲线基础上,评估高速铁路运营阶段每年的节能和碳减排水平及概率,以及因建设和维护基础设施所造成的能源消耗和碳排放在运营时所需要的偿还期。评估结果表明,从生命周期角度看,高速铁路的节能效果依然明显,但高速铁路的碳减排效果具有一定的不确定性,不如其节能效果明显。而电力生命周期碳排放系数、高速铁路座位利用率以及客流转移和诱增结构都是影响高速铁路碳减排效果的显著因素。(5)提出了基于节能考虑的高速列车运行速度优化模型。当高速铁路线路建成、列车型号确定后,通过优化运输组织是降低牵引能耗的重要手段。模型以铁路运输部门的利润最大和铁路旅客出行的广义费用最小为优化目标。运行速度通过影响列车的牵引能耗而对铁路运输部门的成本产生影响,通过与公路大巴和小汽车的客流竞争而对收入产生影响,并且运行速度也与旅客出行广义费用中的快速性直接相关。在运输供给、列车到发时间和列车数配置等约束下,建立运行速度优化的多目标非线性规划模型,并采用基于模糊折中思想的算法进行求解。模型优化结果表明：在一定经济发展程度下,一味地追求高速度并不能减少铁路旅客出行的广义费用,反而造成牵引能耗的大量增加。更多还原

【Abstract】 As a rapid intercity public transit mode with large capacity, the high-speed railway (HSR) is expected to mitigate the contradiction between the numerous population and inadequate resources per capita in China. As a result, the HSR construction has accelerated significantly with the support of national policies in recent years. However, the infrastructure construction of the HSR involves a large amount of engineering quantity and the high-speed train (HST) also consumes high electricity to run. In addition, in China the infrastructure of bridges and culverts is built extensively along the HSR to replace the at-grade foundation. Besides China has a dominate ratio of low efficiency and high emissions coal-based electricity in generation, which is why the environmental impact of the HSR in China needs to be reexamined in the perspective of a life cycle.To achieve the above-referred goals, of all the environmental impacts, the research focuses on energy consumption (EC) for and greenhouse gas (GHG) emissions from the HSR. Based on the characteristics of the life cycle EC of and GHG emissions from the passenger transport of the HSR, an analysis frame and measuring approach is presented to assess the EC and GHG emissions due to the infrastructure construction of the HSR. On account of the mechanical work, a numerical model is proposed to calculate the traction electricity requirement for the running of HST, which is a primary activity in the operation phase of the HSR. The abilities of saving. energy and reducing GHG emissions of the HSR are reappraised from the perspective of a life cycle. Finally, parts of energy-saving transport organization schemes of the HSR are raised for application. The main contents and conclusions of the dissertation are as follows.(1) The life cycle of the HSR is divided into five elementary phases including the conception, construction, operation, maintenance and disposal, where representative activities are illustrated. The characteristics of the life cycle EC of and GHG emissions from the passenger transport of the HSR consists of two aspects. On one hand, the operation phase of the HSR where energy requirements of its typical activities are highly dependent on the electricity does not usually cause GHG emissions, whereas they are transferred into the process of the electricity generation. On the other hand, as a result of building the large-scale infrastructure, a noticeable ratio of the life cycle EC of and GHG emissions from the HSR is hidden in the construction phase. Worldwide, the life cycle assessment of the HSRs has an obvious regional characteristic. The construction and operation phase are confirmed as the dominating phases for the EC and GHG emissions in the life cycle of the HSR, yet the proportions for the two phases are distinguishing in a different region.(2) The HSR line is split into five sub-models:bridge and culvert, tunnel, at-grade foundation, track as well as electrification system. Combined with the regional inventory of product data, the EC and GHG emissions due to the infrastructure construction of the HSR are estimated via evaluating the building materials requirements and equipment use of the five sub-models. The application of the approach in the Beijing-Shanghai HSR demonstrates the EC resulting from building its infrastructure reaches145,502TJ, while the GHG emissions are19,154Kt CO2-equivalent. Moreover,90%of the EC and GHG emissions are both from the use of building materials. Of all the five sub-models, the tunnel construction on a per-km basis consumes the most energy and emits the most GHG, which are respectively1.9and1.7times of the second place that is the bridge and culvert construction. Even so, the bridge and culvert construction of the Beijing-Shanghai HSR contributes67%of the EC and66%of the GHG emissions in view of the fact that its proportion of bridges and culverts is up to86%. Cement and steel have significant impacts on the GHG emissions from the HSR infrastructure construction. The GHG emissions are expected to be reduced by13%and7%respectively following a20%decrease of the carbon intensity for the cement and steel production.(3) A numerical model is proposed to estimate the traction electricity requirement for the running of HSTs via a calculation of mechanical work. The model is capable to manage the situation that the stopping section is too short to achieve the preliminarily set target speed for the HST. Besides, with an introduction of the transmission efficiency of the engines, the model is also effective in a certain level of accuracy requirements even lack of the traction force curve or the current curve of the HST. The application of the model indicates that the target speed influences the traction electricity consumption of the HST by acting on the peak speed it might accelerate to. Regarding the target speed raised from200to350km/h, the elasticity for the traction electricity consumption about the target speed is1.8to2.1approximately for all the stop schedules. The impact of the stopping times of the HST on its traction electricity consumption is expressed by the acceleration cycles, and the traction electricity requirement for an all-stop HST is around1.7times of that for a through HST while running on an HSR with a length of169km and9passenger stations totally.(4) The Monte Carlo Method is adopted to assess the abilities of the HSR in saving energy and reducing GHG emissions with the introduction of the probability theory. The triangular distribution describes the uncertainty of the EC intensities and load factors of passenger transport modes as well as the life cycle EC and GHG emission factors of fuels, including electricity. The uniform distribution is used regarding to the uncertainty of the shifted ratios of HSR passengers from other transport modes. Moreover, a R. Pearl growth curve is employed to fit the development of the HSR passengers. Consequently, the volume and probability of the HSR in saving energy and reducing GHG emissions yearly in the operation phase is assessed, and the recuperation times after operating for the EC and GHG emissions due to the construction and maintenance of the HSR infrastructure is also assessed. The assessment demonstrates that the ability of the HSR in saving energy is still strong examined from the perspective of the life cycle while its ability in reducing GHG emissions has some uncertainty and is not as strong as its ability in saving energy. As expected, the life cycle GHG emission intensity of the electricity, the load factor of the HSR and the ratios of the shifted and induced passengers of the HSR are all significant contributors to the ability of the HSR in reducing GHG emissions.(5) The speed optimization model of the HST is proposed considering its traction electricity. The transport organization scheme becomes an effective measure to improve the environmental benefits of the HSR after the line has been constructed and the HST has been selected. The objectives of the optimization model are the maximum profits for the HSR transport section and the minimum generalized travel cost for the HSR passengers. The speed has an influence on the cost of the HSR transport section by affecting the traction electricity requirement of the HST, and on the income by competing for the passengers with the bus and private car. Restrained by the transport supply, the departure and arrival time of the HSTs and the number of the HSTs, a multi-objective nonlinear model for the speed optimization is established, which is solved by the application of the algorithm based on fuzzy compromise programming. The results show that under a certain level of economic development, the HST with an ultrahigh speed is not able to reduce the generalized cost of passengers choosing the HSR, but result in a significant increase in electricity requirements for moving.更多还原