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Cited by 119Power Systems Fault DetectionPower System Optimization and StabilityPower System Reliability and Maintenance

The DOI matches its Crossref record, with a small difference in title or year.

A Fault Diagnosis Method of Power Systems Based on Improved Objective Function and Genetic Algorithm-Tabu Search

Lin, Xiangning, Ke, Shuohao, Li, Zhengtian, Weng, Hanli, Han, Xionghui·2010·IEEE Transactions on Power Delivery
DOI 10.1109/tpwrd.2010.2044590
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Abstract

Based on the improved optimization objective function of fault diagnosis, a genetic algorithm-Tabu search (GATS) method is introduced for the purpose of fault diagnosis of power systems. The genetic algorithm has good global search ability, while the Tabu search algorithm has good local search ability. Integrating the advantages of these two algorithms, a new hybrid algorithm, called GATS, can be obtained. Using the function of Shcaffer, the advantages of GATS are proven in this paper. The results of case studies show that GATS is superior to conventional methods in terms of the sensitivity of original solution and the dependency of original parameters. The satisfactory results can be obtained when the GATS method is applied in the event of abnormal operations of protective relays and circuit breakers or the multiple-fault scenarios.

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Research works printed but not linked: 13

  1. wen, 2002, A new approach to time constrained fault diagnosis using the tabu search method, Intell Syst Eng, 120, 19
  2. bi, 2005, improved petri net based fault diagnosis approach for power networks, Power Syst Technol, 29, 52
  3. 10.1109/PES.2006.1709100 · DOI
  4. li, 1998, hybrid strategy combining genetic algorithm and tabu search algorithm, J Syst Eng, 13, 28
  5. zhou, 1993, a neural network approach to fault diagnosis for power systems, Proc IEEE TENCON, 2, 885
  6. 10.1109/PTC.1999.826561 · DOI
  7. 10.1109/TPWRS.2004.836256 · DOI
  8. 10.1109/59.574957 · DOI
  9. 10.1016/0378-7796(95)00974-6 · DOI
  10. wen, 1994, fault section estimation in power system using genetic algorithm and simulated annealing, Proc CSEE, 14, 29
  11. 10.1109/59.387936 · DOI
  12. 10.1109/61.131123 · DOI
  13. 10.1016/S0954-1810(97)00006-X · DOI

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Metadata

Authors
Lin, X., Ke, S., Li, Z., Weng, H., & Han, X.
Affiliations
Huazhong University of Science and Technology (CN)
ORCID
Venue
IEEE Transactions on Power Delivery
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2010-07
Volume
25
Issue
3
Pages
1268-1274
ISSN
  • 0885-8977 (ISSN-L)
  • 1937-4208
DOI
10.1109/tpwrd.2010.2044590
OpenAlex
W2107303657
Cited by
119
References
0
Citations by year
2026: 2 · 2025: 3 · 2024: 5 · 2023: 4 · 2022: 3 · 2021: 12 · 2020: 10 · 2019: 15 · 2018: 8 · 2017: 11 · 2016: 5 · 2015: 6 · 2014: 11 · 2013: 8 · 2012: 14
FWCI
12.74
Type
journal article
Language
en
Open access
closed
Licence
ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
Locations
IEEE Transactions on Power Delivery (publishedVersion)
Topics
  • Physical Sciences › Engineering › Control and Systems Engineering › Power Systems Fault Detection
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Power System Optimization and Stability
  • Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Power System Reliability and Maintenance
Keywords
power system fault diagnosis, objective function optimization, circuit breaker faults, multiple faults, parameter sensitivity

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CoChat. (2026). Citation check: A Fault Diagnosis Method of Power Systems Based on Improved Objective Function and Genetic Algorithm-Tabu Search. https://app.cochat.ai/papers/10.1109/tpwrd.2010.2044590
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Lin, X., Ke, S., Li, Z., Weng, H., & Han, X. (2010). A Fault Diagnosis Method of Power Systems Based on Improved Objective Function and Genetic Algorithm-Tabu Search. IEEE Transactions on Power Delivery. https://doi.org/10.1109/tpwrd.2010.2044590