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A Robust approach for the identification of synchronous machine parameters and dynamic states based on PMU data

机译:基于PMU数据的同步电机参数和动态状态识别的鲁棒方法

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In this paper an approach for on-line identification of parameters and dynamic states of synchronous generator, is proposed. Synchrophasors data and Hybrid Dynamic Simulation provide the trajectories deviations caused by parameters errors. Simulated variables are combined with measurements to obtain Hybrid Trajectory Sensibility Functions (HTSF), which are used in the identification process based on Nonlinear Least Squares. This approach simplifies the calculation of HTSF. Constraints on the parameters range are enforced and the resulting constrained optimization problems is solved by a Primal-Dual Interior Points method. This solution is discussed in the paper. The method is applied to synthetic data and to a large generator of the Itaipu power plant.
机译:本文提出了一种在线辨识同步发电机参数和动态状态的方法。同步相量数据和混合动力仿真提供了由参数误差引起的轨迹偏差。将模拟变量与测量值结合以获得混合轨迹灵敏度函数(HTSF),该函数可用于基于非线性最小二乘法的识别过程。这种方法简化了HTSF的计算。强制执行参数范围约束,并通过“原始-对偶内部点”方法解决由此产生的约束优化问题。本文讨论了该解决方案。该方法适用于综合数据和伊泰普电厂的大型发电机。

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