TY - JOUR
T1 - A Stochastic Event-Triggered Robust Cubature Kalman Filtering Approach to Power System Dynamic State Estimation With Non-Gaussian Measurement Noises
AU - Li, Zhen
AU - Li, Sen
AU - Liu, Bin
AU - Yu, Samson S.
AU - Shi, Peng
N1 - Publisher Copyright:
© 1993-2012 IEEE.
PY - 2023/3/1
Y1 - 2023/3/1
N2 - In power system communication and control, the wide-area measurement system (WAMS) is usually adversely affected by noisy measurements and data congestion, posing great challenges to the stability and functionality of modern power grids. This study proposes a stochastic event-triggered robust dynamic state estimation (DSE) method for non-Gaussian measurement noises, using the cubature Kalman filter (CKF) technique. To reduce the computational burden and data transmission congestion resulting from centrally processing the measurement data, the proposed event-triggered robust CKF (ET-RCKF) is deployed at a local level with appropriate system formulation. The proposition of the novel robust DSE strategy is detailed in this brief, with its stability mathematically analyzed and proven, and simulation study on the IEEE 39-bus benchmark test system verifies the effectiveness of the proposed ET-RCKF approach. This novel DSE method is able to cope with non-Gaussian measurement noises and produce highly satisfactory estimation results, leading to wide applicability in real-world power system applications.
AB - In power system communication and control, the wide-area measurement system (WAMS) is usually adversely affected by noisy measurements and data congestion, posing great challenges to the stability and functionality of modern power grids. This study proposes a stochastic event-triggered robust dynamic state estimation (DSE) method for non-Gaussian measurement noises, using the cubature Kalman filter (CKF) technique. To reduce the computational burden and data transmission congestion resulting from centrally processing the measurement data, the proposed event-triggered robust CKF (ET-RCKF) is deployed at a local level with appropriate system formulation. The proposition of the novel robust DSE strategy is detailed in this brief, with its stability mathematically analyzed and proven, and simulation study on the IEEE 39-bus benchmark test system verifies the effectiveness of the proposed ET-RCKF approach. This novel DSE method is able to cope with non-Gaussian measurement noises and produce highly satisfactory estimation results, leading to wide applicability in real-world power system applications.
KW - Non-Gaussian noises
KW - phasor measurement unit (PMU)
KW - robust cubature Kalman filter (RCKF)
KW - stochastic event-triggered dynamic state estimation (DSE)
UR - http://www.scopus.com/inward/record.url?scp=85133815535&partnerID=8YFLogxK
U2 - 10.1109/TCST.2022.3184467
DO - 10.1109/TCST.2022.3184467
M3 - Article
AN - SCOPUS:85133815535
SN - 1063-6536
VL - 31
SP - 889
EP - 896
JO - IEEE Transactions on Control Systems Technology
JF - IEEE Transactions on Control Systems Technology
IS - 2
ER -