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

机译:基于聚类的次级动态参数在线识别,用于基于测量的复合载荷建模

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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:电力负载的准确建模和参数识别始终是一个难题,尚未解决,但对于电力系统的稳定性分析,预测和决策至关重要。广域测量系统(WAMS)的开发提供了进一步解决挑战的可能方法。在此工作的基础上,基于现有的在线建模主参数的载荷建模方法,对聚类方法进行了改进,将复合载荷模型的电抗作为次要动态参数。给出了相应的理论分析,设计原理和系统实现。选择扰动期间的无功功率阻尼时间常数作为聚类特征。仿真结果表明,我们的改进具有令人满意的准确性。

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