The dynamic characteristic evaluation is an important prerequisite for safe and reliable operation of the medium-voltage DC integrated power system (MIPS), and the dynamic state estimation is an essential technical approach to the evaluation. Unlike the electromechanical transient process in a traditional power system, periodic change in pulse load of the MIPS is an electromagnetic transient process. As the system state suddenly changes in the range of a smaller time constant, it is difficult to estimate the dynamic state due to periodic disturbance. This paper presents a dynamic mathematical model of the MIPS according to the network structure and control strategy, thereby overcoming the restrictions of algebraic variables on the estimation and developing a dynamic state estimation method based on the extended Kalman filter. Using the method of adding fictitious process noise, it is possible to solve the problem that the linearized algorithm of the MIPS model is less reliable when an abrupt change occurs in the pulse load. Therefore, the accuracy of the dynamic state estimation and the stability of the filter can be improved under the periodic disturbance of pulse load. The simulation and experimental results confirm that the proposed model and method are feasible and effective.

中文翻译：

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带脉冲负载的中压直流集成电力系统的动态状态估计

动态特性评估是中压直流集成电源系统（MIPS）安全可靠运行的重要先决条件，而动态状态评估是进行评估的必要技术手段。与传统电源系统中的机电瞬变过程不同，MIPS的脉冲负载的周期性变化是电磁瞬变过程。由于系统状态在较小的时间常数范围内突然变化，因此由于周期性干扰而难以估计动态状态。根据网络结构和控制策略，提出了MIPS的动态数学模型，克服了代数变量对估计的约束，提出了基于扩展卡尔曼滤波的动态状态估计方法。使用添加虚拟过程噪声的方法，可以解决以下问题：当脉冲负载发生突然变化时，MIPS模型的线性化算法不太可靠。因此，在脉冲负载的周期性扰动下，可以提高动态状态估计的精度和滤波器的稳定性。仿真和实验结果验证了所提模型和方法的可行性和有效性。