TY - GEN
T1 - Efficient computation of covariance matrix entries
AU - Lin, Yuzhang
AU - Abur, Ali
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/11/20
Y1 - 2015/11/20
N2 - It was shown earlier that network parameter errors could be identified using their normalized Lagrange multipliers. However, normalization requires computation of their covariance matrix which is computationally very time-consuming, thus limiting its practical use for large-scale systems. This paper presents an effective algorithm to address this shortcoming. The proposed algorithm is described and simulation results are provided to illustrate the dramatic reduction in computational costs for large power systems.
AB - It was shown earlier that network parameter errors could be identified using their normalized Lagrange multipliers. However, normalization requires computation of their covariance matrix which is computationally very time-consuming, thus limiting its practical use for large-scale systems. This paper presents an effective algorithm to address this shortcoming. The proposed algorithm is described and simulation results are provided to illustrate the dramatic reduction in computational costs for large power systems.
KW - computational efficiency
KW - Lagrange multipliers
KW - network parameter errors
KW - sparse inverse
KW - state estimation
UR - http://www.scopus.com/inward/record.url?scp=84961837438&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84961837438&partnerID=8YFLogxK
U2 - 10.1109/NAPS.2015.7335139
DO - 10.1109/NAPS.2015.7335139
M3 - Conference contribution
AN - SCOPUS:84961837438
T3 - 2015 North American Power Symposium, NAPS 2015
BT - 2015 North American Power Symposium, NAPS 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - North American Power Symposium, NAPS 2015
Y2 - 4 October 2015 through 6 October 2015
ER -