由于试验条件与发电机运行的实际工况有较大差异,常规的电机试验难以得到与饱和、涡流等密切相关的发电机动态参数的准确值,满足不了离线和在线安全分析及控制的要求。将PMU上传的定子电压和励磁电压量测作为输入信号、定子电流和励磁电流作为输出信号,基于PMU实测数据和同步发电机派克模型,考虑定子绕组暂态过程,实现了同步发电机原始参数的辨识。电力系统实际算例表明,与设计参数相比,基于该参数辨识结果的仿真曲线与实测发电机动态曲线的拟合程度明显要高,所提方法能够有效提高同步发电机的参数辨识精度。
Since test conditions are quite different from actual working conditions, it’s difficult for conventional test method to identify the exact value of synchronous machine dynamic parameters which are related to saturation and eddy currents. Thus, conventional test method cannot satisfy requirements of offline/online security analysis and control. Based on PMU measurements and taking transient processes of d-axis and q-axis stator windings into account, this paper proposes an online algorithm to estimate synchronous machine parameters in Park model. With stator voltage and field voltage as input signals, stator current and field current as output signals, the proposed algorithm chooses particle swarm algorithm as optimization algorithm. Practical examples show that, compared with the design parameters, the similarity between simulation data derived from identified parameters and measured data is much better. The proposed method can effectively improve the identification accuracy of synchronous machine parameters.