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Clustering based online identification of secondary dynamic parameters for measurement based composite load modeling

机译:基于聚类基于测量的复合载荷建模的辅助动态参数的在线识别

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Accurate modeling and parameter identification of electrical load is always a difficult problem, remaining unsolved but critical for stability analysis, prediction and decision-making of power systems. The development of wide area measurement system (WAMS) provides possible way's to further address the challenge. In this work, based on an existing load modeling method for online identification of dominant parameters, we put forward an improvement with the clustering method, to get the reactance of the composite load model as a secondary dynamic parameter. Corresponding theoretical analysis, design principles and system implementation are presented. The reactive power damping time constant during disturbance is chosen as the clustering feature. Simulation results show effectiveness of our improvement with satisfactory accuracy.
机译:电荷的准确建模和参数识别始终是一个难题,剩余未解决的,对于电力系统的稳定性分析,预测和决策,剩余的未解决。广域测量系统(WAMS)的发展提供了进一步解决挑战的可能方法。在这项工作中,基于现有的负载建模方法进行在线识别主导参数,我们提出了对聚类方法的改进,使复合负载模型的电抗作为辅助动态参数。呈现了相应的理论分析,设计原则和系统实现。选择干扰期间的无功功率阻尼时间作为聚类特征。仿真结果表明我们以满意的准确性提高的有效性。

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