2015
DOI: 10.1109/tpwrd.2014.2369500
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Parameter Estimation of Multiterminal Transmission Lines Using Joint PMU and SCADA Data

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Cited by 81 publications
(46 citation statements)
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“…In [15], with field SCADA data, a multi-point parameter estimation model was developed based on the Levenberg-Marquardt algorithm. In [16] and [17], WAMS and SCADA data were incorporated for estimating multi-terminal transmission lines with a nonlinear weighted least square algorithm.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…In [15], with field SCADA data, a multi-point parameter estimation model was developed based on the Levenberg-Marquardt algorithm. In [16] and [17], WAMS and SCADA data were incorporated for estimating multi-terminal transmission lines with a nonlinear weighted least square algorithm.…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, it is necessary to select appropriate measured data for estimation. In [16] and [17], a scheme of selecting 3 measurement points was proposed for estimation. In [10], 8 sets of simulated data within 16 minutes were chosen for estimation with even time interval of 2 minutes.…”
Section: Introductionmentioning
confidence: 99%
“…In [29], the placement of the PMUs on the buses has been presented using intelligent algorithms, and a system observability analysis method in [30] is proposed to ensure fast and reliable results. It is known that, the PMUs of WAMS are not sufficient for static state estimation in most of the existing power systems because of the high price [31][32][33]. So, the state estimation with enough PMU measurements cannot be carried out normally at present.…”
Section: Introductionmentioning
confidence: 99%
“…[8][9][10][11][12][13][14][15][16][17][18][19] In particular, the work in Lowe 19 provides a very good review and discussion of the main methods used to estimate the line constants of perfectly transposed and untransposed 3-phase lines, with emphasis on the untransposed case.…”
Section: Introductionmentioning
confidence: 99%