TY - GEN
T1 - PMU-based online change-point detection of imbalance in three-phase power systems
AU - Routtenberg, Tirza
AU - Xie, Yao
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/10/26
Y1 - 2017/10/26
N2 - In this paper, the problem of online change-point detection of voltage imbalance in a three-phase power system using phasor measurement unit (PMU) data is considered within a sequential hypothesis-testing framework. A general model for the positive-sequence data from a PMU measurement at the time domain and off-nominal frequencies is presented. The new formulation, which assumes an additional Gaussian noise, enables fast online detection of imbalance. Closed-form expressions of the cumulative sum (CUSUM) and generalized likelihood ratio (GLR) tests are developed for detection of imbalances. The performance of the change-point detection procedures is evaluated using the average-run-length and the expected detection delay. Numerical simulations show that the proposed method can be used for enhanced situational awareness in future grid management systems and demonstrate the ability to inform strategies for advancing grid capabilities by using change-point detection methods.
AB - In this paper, the problem of online change-point detection of voltage imbalance in a three-phase power system using phasor measurement unit (PMU) data is considered within a sequential hypothesis-testing framework. A general model for the positive-sequence data from a PMU measurement at the time domain and off-nominal frequencies is presented. The new formulation, which assumes an additional Gaussian noise, enables fast online detection of imbalance. Closed-form expressions of the cumulative sum (CUSUM) and generalized likelihood ratio (GLR) tests are developed for detection of imbalances. The performance of the change-point detection procedures is evaluated using the average-run-length and the expected detection delay. Numerical simulations show that the proposed method can be used for enhanced situational awareness in future grid management systems and demonstrate the ability to inform strategies for advancing grid capabilities by using change-point detection methods.
KW - Online change-point detection
KW - Phasor measurement unit (PMU)
KW - Power system monitoring
KW - State estimation
KW - Unbalanced power system
UR - http://www.scopus.com/inward/record.url?scp=85040194865&partnerID=8YFLogxK
U2 - 10.1109/ISGT.2017.8086085
DO - 10.1109/ISGT.2017.8086085
M3 - Conference contribution
AN - SCOPUS:85040194865
T3 - 2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017
BT - 2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017
PB - Institute of Electrical and Electronics Engineers
T2 - 2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017
Y2 - 23 April 2017 through 26 April 2017
ER -