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Regional Sensitivity Analysis Applied To Train Traffic Rescheduling in Case of Power Shortage

机译:区域敏感性分析在缺电情况下的列车交通调度中的应用

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摘要

The present work addresses train traffic rescheduling that is needed when an electric incident limits the power available for train traction. This is a difficult process of prime importance and we propose a decision-support tool to help the operator. The railway network is a complex multi-physics dynamic system, with many operational constraints, and its simulation is expensive. This makes the management of an incident difficult. The proposed approached applies regional sensitivity in order to study the influence of the different adjustment variables (train delays, speed references ...) on traffic quality indicators and operational constraints (catenary voltage, for example). The analysis is divided in two parts: Monte Carlo filtering for factor mapping (qualitative analysis), and two samples Kolmogorov-Smirnov test for prioritization and fixing factors (quantitative analysis). The results provide information about the behavior of the system and the influence of the different traffic adjustment variables, and help reorganizing the train traffic in an optimal way. As a result of the analysis, we obtain a set of feasible solutions that are organized according to different performance criteria. Pareto-optimal front are plotted in order to guide the decisionmaker. The proposed approach is illustrated for a simple case representative of suburban traffic.
机译:当前的工作解决了在发生电气事故而限制火车牵引力的情况下所需的火车交通调度。这是一个极其重要的困难过程,我们建议使用决策支持工具来帮助操作员。铁路网络是一个复杂的多物理场动力学系统,具有许多操作约束,并且其仿真成本很高。这使事件的管理变得困难。为了研究不同的调整变量(火车延误,速度参考值...)对交通质量指标和运行限制(例如,类别电压)的影响,所提出的方法运用了区域敏感性。该分析分为两个部分:用于因子映射的Monte Carlo滤波(定性分析)和用于确定优先级和固定因子的两个样本Kolmogorov-Smirnov检验(定量分析)。结果提供有关系统行为以及不同交通调整变量的影响的信息,并有助于以最佳方式重组火车交通。分析的结果是,我们获得了一组根据不同性能标准组织的可行解决方案。绘制帕累托最优阵线以指导决策者。针对代表郊区交通的简单案例说明了所建议的方法。

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