基于数字孪生的城轨供电系统高保真建模方法

High Fidelity Modeling Method of Urban Rail Power Supply System Based on Digital Twin

针对传统模型难以对具备时变特性的城轨牵引供电系统进行精准模拟的问题,总结分析了传统建模在预设负荷、固定参数及离线计算等方面的缺点,提出了一种基于数字孪生技术的模型与数据混合驱动建模方法;并结合城轨牵引供电系统实际特点,设计了数字孪生模型的运行架构及计算算法,建立信息交互体系对系统模型负荷进行精确输入,采用基于群智能优化的混合闭环校正算法实现模型参数的主动校正。理论分析及仿真结果表明:系统参数的全局优化校正可以通过基于群智能优化的闭环校正算法实现,采取子系统参数辨识和整体参数校正的混合校正策略有助于减小参数的寻优范围,降低群智能优化在系统参数校正的计算时间成本,保证模型对于参数变化的校正响应速度;具备负荷精确输入和参数主动校正能力的数字孪生模型,其潮流计算结果高度逼近采样数据,相比传统模型大幅提升了潮流计算的精度,对于牵引供电系统运行决策及设计优化具有实际意义。

In order to solve the problem that the traditional model is difficult to accurately simulate the urban rail traction power supply system with time-varying characteristics, the shortcomings of traditional modeling in the aspects of preset load, fixed parameters and off-line calculation were summarized and analyzed, and a hybrid driven modeling method based on digital twin technology was proposed in this paper. Combined with the actual characteristics of urban rail traction power supply system, the operation structure and calculation algorithm of digital twin model were designed. An information interaction system was established to input the load of the system model accurately. The closed-loop correction algorithm based on swarm intelligence optimization was adopted to realize the active correction of model parameters. Theoretical analysis and simulation results show that the global optimization correction of system parameters can be realized by the closed-loop correction algorithm based on the swarm intelligence optimization. The hybrid correction strategy of subsystem parameter identification and global parameter correction helps to reduce the optimization range of parameters, which will reduce the calculation time cost of the swarm intelligence optimization in system parameter correction and ensure the response speed of the model to parameter changes. The power flow calculation results of the digital twin model with the ability of accurate load input and active parameter correction are highly close to the sampling data. Compared with the traditional model, the accuracy of power flow calculation is greatly improved, which has practical significance for the operation decision and design optimization of traction power supply system.