TY - GEN
T1 - Robust collaborative state estimation for smart grid monitoring
AU - Li, Xiao
AU - Scaglione, Anna
PY - 2013/10/18
Y1 - 2013/10/18
N2 - This paper proposes a decentralized state estimation scheme via network gossiping with applications in smart grid wide-area monitoring. The proposed scheme allows distributed control areas to solve for an accurate global state estimate collaboratively using the proposed Gossip-based Gauss-Newton (GGN) algorithm. Furthermore, the proposed scheme mitigates the influence of bad data by adaptively updating the noise variances and re-weighting the contributions of the most recent measurements for state estimation. Compared with other distributed techniques, our scheme via gossiping is more flexible and resilient in case of network reconfigurations and failures. We further prove that the power flow equations satisfy the sufficient condition for the GGN algorithm to converge to the desired solution. Simulations of the IEEE-118 system show that the proposed scheme estimates and tracks the global state robustly, and degrades gracefully when there are random failures and bad data.
AB - This paper proposes a decentralized state estimation scheme via network gossiping with applications in smart grid wide-area monitoring. The proposed scheme allows distributed control areas to solve for an accurate global state estimate collaboratively using the proposed Gossip-based Gauss-Newton (GGN) algorithm. Furthermore, the proposed scheme mitigates the influence of bad data by adaptively updating the noise variances and re-weighting the contributions of the most recent measurements for state estimation. Compared with other distributed techniques, our scheme via gossiping is more flexible and resilient in case of network reconfigurations and failures. We further prove that the power flow equations satisfy the sufficient condition for the GGN algorithm to converge to the desired solution. Simulations of the IEEE-118 system show that the proposed scheme estimates and tracks the global state robustly, and degrades gracefully when there are random failures and bad data.
KW - convergence
KW - gossiping
KW - hybrid state estimation
UR - http://www.scopus.com/inward/record.url?scp=84890460191&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84890460191&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2013.6638663
DO - 10.1109/ICASSP.2013.6638663
M3 - Conference contribution
AN - SCOPUS:84890460191
SN - 9781479903566
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 5243
EP - 5247
BT - 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
T2 - 2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Y2 - 26 May 2013 through 31 May 2013
ER -