TY - GEN
T1 - A linear estimator for transmission line parameters based on distributed parameter line model
AU - Jiao, Xiangqing
AU - Liao, Yuan
PY - 2017/5/30
Y1 - 2017/5/30
N2 - Transmission line parameters are critical inputs to a variety of power system analysis algorithms. To ensure the precision of line parameters, this paper proposes a novel linear method to estimate transmission line parameters, including series resistance, series reactance, and shunt susceptance, for non-compensated and series-compensated lines. Voltage and current phasors obtained by phasor measurement units (PMUs) from both ends are utilized in the algorithm. Linear least squares method is applied when multiple sets of measurements are available for improved accuracy. Distributed parameter line model is employed in developing the algorithm. An optimal estimator is also proposed, which can detect and identify possible measurement errors, although this type of method is no longer linear. The estimated line parameters can be used to determine line temperature and conductor sag. Evaluations studies demonstrate the effectiveness of the proposed methods.
AB - Transmission line parameters are critical inputs to a variety of power system analysis algorithms. To ensure the precision of line parameters, this paper proposes a novel linear method to estimate transmission line parameters, including series resistance, series reactance, and shunt susceptance, for non-compensated and series-compensated lines. Voltage and current phasors obtained by phasor measurement units (PMUs) from both ends are utilized in the algorithm. Linear least squares method is applied when multiple sets of measurements are available for improved accuracy. Distributed parameter line model is employed in developing the algorithm. An optimal estimator is also proposed, which can detect and identify possible measurement errors, although this type of method is no longer linear. The estimated line parameters can be used to determine line temperature and conductor sag. Evaluations studies demonstrate the effectiveness of the proposed methods.
KW - bad measurement detection and identification
KW - distributed parameter line model
KW - linear estimation
KW - transmission line parameter estimation
UR - http://www.scopus.com/inward/record.url?scp=85025643347&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85025643347&partnerID=8YFLogxK
U2 - 10.1109/PECI.2017.7935724
DO - 10.1109/PECI.2017.7935724
M3 - Conference contribution
AN - SCOPUS:85025643347
T3 - 2017 IEEE Power and Energy Conference at Illinois, PECI 2017
BT - 2017 IEEE Power and Energy Conference at Illinois, PECI 2017
T2 - 2017 IEEE Power and Energy Conference at Illinois, PECI 2017
Y2 - 23 February 2017 through 24 February 2017
ER -