TY - JOUR
T1 - Stochastic Event-Triggered Cubature Kalman Filter for Power System Dynamic State Estimation
AU - Li, Sen
AU - Hu, You
AU - Zheng, Lini
AU - Li, Zhen
AU - Chen, Xi
AU - Fernando, Tyrone
AU - Iu, Herbert H.C.
AU - Wang, Qinglin
AU - Liu, Xiangdong
N1 - Publisher Copyright:
© 2004-2012 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - Accurate dynamic state estimation (DSE) plays an important role in power systems. Although various filtering methods, such as unscented Kalman filter (UKF) and particle filter (PF), have been applied for DSE based on phasor measurement units, they occupy a huge communication bandwidth without specific concern. In order to alleviate this communication burden, the event-triggered cubature Kalman filter (CKF) is proposed based on the stochastic event-triggered schedule in this brief. Based on the developed nonlinear event-triggered schedule, the CKF further provides more accurate estimation than UKF and has lower computational complexity than PF. The proposed filter can effectively reduce the communication rate while ensuring the accuracy of filtering. Finally, the standard IEEE 145-bus system is utilized to verify the feasibility and performance of the proposed method.
AB - Accurate dynamic state estimation (DSE) plays an important role in power systems. Although various filtering methods, such as unscented Kalman filter (UKF) and particle filter (PF), have been applied for DSE based on phasor measurement units, they occupy a huge communication bandwidth without specific concern. In order to alleviate this communication burden, the event-triggered cubature Kalman filter (CKF) is proposed based on the stochastic event-triggered schedule in this brief. Based on the developed nonlinear event-triggered schedule, the CKF further provides more accurate estimation than UKF and has lower computational complexity than PF. The proposed filter can effectively reduce the communication rate while ensuring the accuracy of filtering. Finally, the standard IEEE 145-bus system is utilized to verify the feasibility and performance of the proposed method.
KW - Event-triggered cubature Kalman filter (ETCKF)
KW - communication rate
KW - dynamic state estimation
KW - phasor measurement units (PMUs)
KW - stochastic event-triggered schedule
UR - http://www.scopus.com/inward/record.url?scp=85058651129&partnerID=8YFLogxK
U2 - 10.1109/TCSII.2018.2886690
DO - 10.1109/TCSII.2018.2886690
M3 - Article
AN - SCOPUS:85058651129
SN - 1549-7747
VL - 66
SP - 1552
EP - 1556
JO - IEEE Transactions on Circuits and Systems II: Express Briefs
JF - IEEE Transactions on Circuits and Systems II: Express Briefs
IS - 9
M1 - 8574958
ER -