Abstract
PMU data are expected to be GPS-synchronized measurements with highly accurate magnitude and phase angle information. However, this potential accuracy is not always achieved in actual field installations due to various causes. It has been observed in some PMU measurements that the voltage and current phasors are corrupted by noise and bias errors. This paper presents a novel method for detection and correction of errors in PMU measurements with the concept of calibration factors. The proposed method uses nonlinear optimal estimation theory to calculate calibration factor using a traditional model of an untransposed transmission line with unbalanced load. This method is intended to work as a prefiltering scheme that can significantly improve the accuracy of the PMU measurement for further use in system state estimation, transient stability monitoring, wide area protection, etc. Case studies based on simulated data are presented to demonstrate the effectiveness and robustness of the proposed method.
| Original language | English (US) |
|---|---|
| Article number | 6279481 |
| Pages (from-to) | 1575-1583 |
| Number of pages | 9 |
| Journal | IEEE Transactions on Smart Grid |
| Volume | 3 |
| Issue number | 4 |
| DOIs | |
| State | Published - 2012 |
Fingerprint
Keywords
- Bad data detection
- bias errors
- calibration factor
- non-linear estimation theory
- PMU measurements
- transmission line modeling
ASJC Scopus subject areas
- Computer Science(all)
Cite this
An adaptive method for detection and correction of errors in PMU measurements. / Shi, Di; Tylavsky, Daniel; Logic, Naim.
In: IEEE Transactions on Smart Grid, Vol. 3, No. 4, 6279481, 2012, p. 1575-1583.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - An adaptive method for detection and correction of errors in PMU measurements
AU - Shi, Di
AU - Tylavsky, Daniel
AU - Logic, Naim
PY - 2012
Y1 - 2012
N2 - PMU data are expected to be GPS-synchronized measurements with highly accurate magnitude and phase angle information. However, this potential accuracy is not always achieved in actual field installations due to various causes. It has been observed in some PMU measurements that the voltage and current phasors are corrupted by noise and bias errors. This paper presents a novel method for detection and correction of errors in PMU measurements with the concept of calibration factors. The proposed method uses nonlinear optimal estimation theory to calculate calibration factor using a traditional model of an untransposed transmission line with unbalanced load. This method is intended to work as a prefiltering scheme that can significantly improve the accuracy of the PMU measurement for further use in system state estimation, transient stability monitoring, wide area protection, etc. Case studies based on simulated data are presented to demonstrate the effectiveness and robustness of the proposed method.
AB - PMU data are expected to be GPS-synchronized measurements with highly accurate magnitude and phase angle information. However, this potential accuracy is not always achieved in actual field installations due to various causes. It has been observed in some PMU measurements that the voltage and current phasors are corrupted by noise and bias errors. This paper presents a novel method for detection and correction of errors in PMU measurements with the concept of calibration factors. The proposed method uses nonlinear optimal estimation theory to calculate calibration factor using a traditional model of an untransposed transmission line with unbalanced load. This method is intended to work as a prefiltering scheme that can significantly improve the accuracy of the PMU measurement for further use in system state estimation, transient stability monitoring, wide area protection, etc. Case studies based on simulated data are presented to demonstrate the effectiveness and robustness of the proposed method.
KW - Bad data detection
KW - bias errors
KW - calibration factor
KW - non-linear estimation theory
KW - PMU measurements
KW - transmission line modeling
UR - http://www.scopus.com/inward/record.url?scp=84872090625&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84872090625&partnerID=8YFLogxK
U2 - 10.1109/TSG.2012.2207468
DO - 10.1109/TSG.2012.2207468
M3 - Article
AN - SCOPUS:84872090625
VL - 3
SP - 1575
EP - 1583
JO - IEEE Transactions on Smart Grid
JF - IEEE Transactions on Smart Grid
SN - 1949-3053
IS - 4
M1 - 6279481
ER -