使用时间序列模型和PMU测量的发电机参数识别

Tinghui Zhou, Ligang Zhao, Chao Hong, Guanbiao Huang, Hongyue Zhen, Changxiang Wang, Xiaoshan Wu, C. Jing
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引用次数: 0

摘要

动态仿真是电力系统运行和规划的重要工具之一。动态仿真结果的准确性直接取决于设备模型的准确性,特别是同步发电机模型的准确性。提出了一种基于时间序列的同步发电机参数估计技术,该技术采用相量测量单元(PMU)数据。对发电机机电动力学相关参数进行了估计,包括发电机惯性常数、调速常数、调速器时间常数等。利用线性系统参数辨识技术,将经典的发电机模型和摆动方程转化为时间序列模型,可以间接地估计其参数。一旦计算出时间序列模型的参数,就可以从时间序列模型中恢复发电机的参数。仿真结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generator Parameter Identification Using Time Series Model and PMU Measurements
Dynamic simulation is one of the most important tools for the operation and planning of electric power systems. Accuracy of the dynamic simulation results are directly determined by the accuracy of the equipment model, especially the models of synchronous generators. This paper proposes a time-series-based synchronous generator parameter estimation technique using phasor measurement unit (PMU) data. The generator electromechanical dynamics related parameters are estimated which include generator inertia constant, speed regulation constant, and time constant of the turbine-governor, etc. The classical generator model and swing equation are transformed into a time series model whose parameters can be estimated in an indirect way using linear system parameter identification technology. Once the parameters for the time series model are calculated, the generator parameters can be recovered from the time series model. Simulation results demonstrate the effectiveness of the proposed methodology.
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