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Abstract: We propose a new and efficient algorithm to detect, identify, and correct measurement errors and branch parameter errors of power systems. A dynamic state estimation algorithm is used based on the kalman filter theory. The proposed algorithm also successfully detects and identifies sudden load changes in power systems. The method uses three normalized vectors to process errors at each sampling time: normalized measurement residual, normalized Lagrange multiplier, and normalized innovation vector. An IEEE 14-bus test system was used to verify and demonstrate the effectiveness of the proposed method. Numerical results are presented and discussed to show the accuracy of the method.

This paper proposed a new and efficient algorithm for simultaneous detection, identification and correction of measurement and branch parameter errors based on the DSE algorithm and KF theory. The proposed correction methodology also successfully detected and identified the sudden load changes. The suitable results were obtained and it was shown that the proposed method successfully processed the anomalies and identified and corrected the errors, with high accuracy. The ideas in the paper are interesting and the theoretic results obtained have some potential in applications.

一种针对测试误差、参数误差和负荷突变故障分析的多功能动态状态估计器

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