TY - GEN
T1 - WAMS State Estimation Considering Possible One-Step Delayed Measurements
AU - Eskandari, Neda
AU - Dehghani, Maryam
AU - Mohammadi, Mohsen
AU - Vafamand, Navid
AU - Dragicevic, Tomislav
AU - Rodriguez, Jose
N1 - Funding Information:
Jose Rodriguez acknowledges the support of through projects FB0008, ACT192013, and 1170167.
Publisher Copyright:
© 2020 IEEE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/9/28
Y1 - 2020/9/28
N2 - Phasor Communication Delay in a large power system is indispensable. The delay can be mainly originated by the practical limitations of exploiting the communication line or the measurement units. In this paper, a linear Stochastic Delayed Kalman Filter (SDKF) is used for the wide-area measurement system (WAMS) application. It is considered that some or all information from the phasor measurement units (PMUs) may be received by a one-step delay. Therefore, the SDKF is utilized effectively to compensate for the influence of the wide-area monitoring system (WAMS) random delays on state estimation. To show the applicability of the SLKF, realtime simulations are carried out on the IEEE 14-bus benchmark via the OPAL-RT hardware. Real-time results show that the considered SLKF provides more accurate estimations than the conventional Kalman filter.
AB - Phasor Communication Delay in a large power system is indispensable. The delay can be mainly originated by the practical limitations of exploiting the communication line or the measurement units. In this paper, a linear Stochastic Delayed Kalman Filter (SDKF) is used for the wide-area measurement system (WAMS) application. It is considered that some or all information from the phasor measurement units (PMUs) may be received by a one-step delay. Therefore, the SDKF is utilized effectively to compensate for the influence of the wide-area monitoring system (WAMS) random delays on state estimation. To show the applicability of the SLKF, realtime simulations are carried out on the IEEE 14-bus benchmark via the OPAL-RT hardware. Real-time results show that the considered SLKF provides more accurate estimations than the conventional Kalman filter.
KW - Phasor Measurement Unit (PMU)
KW - Random Measurement Delay
KW - Stochastic Kalman Filter
KW - Wide-area Monitoring System (WAMS)
UR - http://www.scopus.com/inward/record.url?scp=85097523283&partnerID=8YFLogxK
U2 - 10.1109/PEDG48541.2020.9244436
DO - 10.1109/PEDG48541.2020.9244436
M3 - Conference contribution
AN - SCOPUS:85097523283
T3 - 2020 IEEE 11th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2020
SP - 328
EP - 333
BT - 2020 IEEE 11th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th IEEE International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2020
Y2 - 28 September 2020 through 1 October 2020
ER -
