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Title: Precise Fault Location on Transmission Lines Using Ensemble Kalman Filter

Journal Article · · IEEE Transactions on Power Delivery
 [1];  [2];  [1];  [3];  [1]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. ShanghaiTech Univ. (China)
  3. Global Energy Interconnection Research Inst. North America, San Jose, CA (United States)
+ Show Author Affiliations

Accurate pin-pointing of faults on transmission lines minimizes outage time, labor, and costs. This paper proposes a simple yet effective ensemble Kalman filter (EnKF) approach to accurately locating the faults on transmission lines within half-cycle time. The approach is easy to implement and does not require foreknowledge of either the fault type or an approximate guess of the fault location. Finally, extensive results validate the effectiveness and accuracy of the EnKF-based fault location approach.

Research Organization:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC05-76RL01830
OSTI ID:
1457786
Report Number(s):
PNNL-SA-130921
Journal Information:
IEEE Transactions on Power Delivery, Vol. 33, Issue 6; ISSN 0885-8977
Publisher:
IEEECopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 29 works
Citation information provided by
Web of Science

Cited By (2)

Dynamic State Estimation for Synchronous Machines Based on Adaptive Ensemble Square Root Kalman Filter journal November 2019
A Novel Arc Fault Detection Method Integrated Random Forest, Improved Multi-scale Permutation Entropy and Wavelet Packet Transform journal April 2019

Figures / Tables (5)

Fig. 1.(p. 2)figure Fig. 1.
Fig. 2.(p. 2)figure Fig. 2.
TABLE I(p. 3)table TABLE I
TABLE II(p. 3)table TABLE II
TABLE III(p. 3)table TABLE III

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Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
dynamic state estimation
ensemble Kalman filter
fault location
fault classification