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Accurate knowledge of transmission line (TL) impedance parameters helps to improve accuracy in relay settings and power flow modeling. To improve TL parameter estimates, various algorithms have been proposed in the past to identify TL parameters based on measurements from Phasor Measurement Units (PMUs). These methods are based on the positive sequence TL models and can generate accurate positive sequence impedance parameters for a fully-transposed TL when measurement noise is absent; however these methods may generate erroneous parameters when the TLs are not fully transposed or when measurement noise is present. PMU field-measure data are often corrupted with noise and this noise is problematic for all parameter identification algorithms, particularly so when applied to short transmission lines. This paper analyzes the limitations of the positive sequence TL model when used for parameter estimation of TLs that are untransposed and proposes a novel method using linear estimation theory to identify TL parameters more reliably. This method can be used for the most general case: short or long lines that are fully transposed or untransposed and have balanced or unbalance loads. Besides the positive or negative sequence impedance parameters, the proposed method can also be used to estimate the zero sequence parameters and the mutual impedances between different sequences. This paper also examines the influence of noise in the PMU data on the calculation of TL parameters. Several case studies are conducted based on simulated data from ATP to validate the effectiveness of the new method. Through comparison of the results generated by this novel method and several other methods, the effectiveness of the proposed approach is demonstrated

PMU data are expected to be GPS-synchronized measurements with highly accurate magnitude and phase angle information. However, this potential accuracy is not always achieved in actual field installations due to various causes. It has been observed in some PMU measurements that the voltage and current phasors are corrupted by noise and bias errors. This paper presents a novel method for detection and correction of errors in PMU measurements with the concept of calibration factors. The proposed method uses nonlinear optimal estimation theory to calculate calibration factor using a traditional model of an untransposed transmission line with unbalanced load. This method is intended to work as a prefiltering scheme that can significantly improve the accuracy of the PMU measurement for further use in system state estimation, transient stability monitoring, wide area protection, etc. Case studies based on simulated data are presented to demonstrate the effectiveness and robustness of the proposed method.

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