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Online Identification of Transmission Line Positive-Sequence Parameters Based on Adaptive Robust Least Squares |
Xue Ancheng, Zhang Zhaoyang, Bi Tianshu |
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Source North China Electric Power University Beijing 102206 China |
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Abstract Aiming at the actual situation that there often exist random measurement noises even bad data in online PMU(phasor measurement unit) data, a method of adaptive robust least squares is proposed for online identification of transmission line positive-sequence parameters. Firstly, the least-squares identification model of transmission line parameters is presented based on the multi- period PMU data of both ends. And then, after the brief introduction of robust least squares, to fully use measurement information, the IGG (Institute of Geodesy & Geophysics, Chinese Academy of Sciences) weight function (scheme I) is adopted to realize “three segments” robust identification. Finally, the expectation and variance of the equation residual sequence are online estimated effectively by using the median principle to adjust the robustness threshold of IGG adaptively. The proposed method does not need to determine the measurement error of measurement equipment, and has strong robustness ability and high reliability of identification results, and also eliminates the problem that the method is sensitive to the parameter iterative initial values. The examples based on PSCAD simulation data and PMU data show that the proposed method is very effective, and is more suitable for online parameter identification.
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Received: 12 April 2013
Published: 25 May 2015
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