Connected and Coordinated Train Operation and Traction Power Supply Systems (COOPS)

预计到2040年，由于人口增长、社会经济全球化和可持续的机动性去碳化，英国铁路运输需求将增加约40%。运力和效率的提高是铁路网面临的主要挑战，铁路网已经接近饱和状态。自动列车运行(ATO)采用先进的信号系统，如移动闭塞和虚拟耦合，以减少列车间隔距离和增加基础设施能力。然而，更多采用先进操作系统的列车影响了牵引供电系统的性能，例如，列车加速和制动运行的同步增加了峰值功率，并由于再生制动能量损失而降低了能效。目前的技术能力不允许在列车运行和电网之间进行准确和实时的交互评估。因此，重要的是制定一种全面的方法来提高铁路运力和效率。该合作项目将交流国际合作伙伴在列车运营和牵引电力系统方面的知识，并研究这两个不同系统之间的流动机制。将开发一个具有自适应时间尺度和实时数据馈送的数字孪生兄弟，以描述相互关联和协调的系统之间的相互作用。数字双胞胎的输出精确地复制了真实世界铁路网的特征。多场景仿真研究分析了各种系统设计和控制变量对性能的影响，如基础设施容量、效率和成本。将对系统性能进行评估，并与现有系统进行比较。该项目将通过与全球学术界和产业界合作伙伴的双边访问和参与研讨会，建立国际伙伴关系。该项目还将为未来在优化铁路运力和脱碳效率方面的合作提供路线图。

The British railway transport demand is forecast to increase by around 40% by 2040, as a result of population growth, socio-economic globalisation and sustainable mobility decarbonisation. The enhancement of capacity and efficiency is the major challenge to the railway network, which is already near saturation conditions. Automatic Train Operation (ATO) with advanced signalling systems, such as Moving Block and Virtual Coupling, have been investigated to reduce train separation distances and increase the infrastructure capacity. However, more trains with advanced operation systems affect the performance of traction power supply systems, For example, the synchronisation of train acceleration and braking operation increases the peak power and reduces the energy efficiency due to regenerative braking energy loss. The current technological capabilities do not permit accurate and real-time interaction assessment between the train operation and power networks. Therefore, it is important to develop a holistic approach to improving railway capacity and efficiency. This collaborative project will exchange the international partners' knowledge in train operation and traction power systems and investigate the flow mechanism between these two distinct systems. A digital twin with adaptive timescales and real-time data feeding will be developed to describe the interactions of the connected and coordinated systems. The outputs from the digital twin replicate the characteristics of real-world railway networks precisely. The multi-scenario simulation studies analyse the impact of various system design and control variables on performance, such as infrastructure capacity, efficiency and cost. The system performance will be evaluated and compared with the existing system. This project will build international partnerships through bilateral visits, and engagement workshops with global academic and industry partners. The project will also provide a roadmap for future collaboration on optimising the railway capacity and efficiency for decarbonisation.