基于PMU数据和时间序列模型的发电机参数识别(英文)

Generator Parameter Estimation Using PMU Data and Time Series Model

电力系统动态仿真的精度往往由同步发电机等元件模型及参数的精度所决定。在对同步发电机模型进行时间序列分析的基础上,提出了一套依靠同步相量测量单元对惯性时间常数、发电机转速调节常数以及涡轮调速器的时间常数等发电机动态参数进行识别的方法。该方法首先将发电机的经典模型和摇摆方程统一转换为一个时间序列模型,并利用线形参数辨识方法对此时间序列模型的参数予以辨识;最后通过求解发电机模型参数与时间序列模型参数的等式关系得到发电机的模型参数。对不同功率变化波形进行了仿真试验,按照本文方法计算得出的发电机参数与实际参数一致,验证了本文提出方法的有效性。

The accuracy of dynamic simulation results is determined by the accuracy of equipment models,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 including the generator inertia constant,speed regulation constant and time constant of turbine-governor are estimated. The classical generator model and swing equation are transformed into a time series model of which parameters can be estimated 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 are conducted using different input signals and the generator parameters are computed using the inputs and the corresponding collected outputs. The calculated generator parameters are consistent with the actual parameters,which demonstrates the effectiveness of the proposed methodology.