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Recent Research Progress in Fault Analysis of Complex Electric Power SystemsWANG, Z. , ZHANG, Y. , ZHANG, J. , MA, J. |
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Author keywords
complexity, graph theory, multivariate statistical analysis theory, fault analysis, electric power system
References keywords
power(10), analysis(7), electric(6), cluster(6), system(5), systems(4), dynamics(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2010-02-27
Volume 10, Issue 1, Year 2010, On page(s): 28 - 33
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2010.01005
Web of Science Accession Number: 000275458900005
SCOPUS ID: 77954676685
Abstract
In this paper, we adopt a novel approach to the fault analysis of complex electric power systems. Electric power system is one of the most complex artificial systems in the world. Its safe, steady, economical and reliable operating plays a very important part in guaranteeing socioeconomic development, and even in safeguarding social stability. The complexity of electric power system is determined by its characteristics about constitution, configuration, operation, organization, etc. No matter if, we adopt new analytical methods or technical means, we must have a distinct recognition of electric power system itself and its complexity, and increase analysis continuously, operation and control level. In this paper, utilizing real-time measurements of phasor measurement unit, based on graph theory and multivariate statistical analysis theory, we are using mainly Breadth-first search, Depth-first search and cluster analysis. Then, we seek for the uniform laws of marked changes of electrical quantities. Then we can carry out fast and exact analysis of fault component. Finally, we can accomplish fault isolation. According to line fault and bus-bar fault (single-phase fault, phase-to-phase fault and three-phase fault) in complex electric power systems, we have carried out a great deal of simulation experiments and obtained ideal results. These researches have proven that the faults in complex electric power systems can be explored successfully by analysis and calculation based on graph theory and multivariate statistical analysis theory. |
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[1] Analysis of Chain of Events in Major Historic Power Outages, HUANG, T., VORONCA, S. L., PURCAREA, A. A., ESTEBSARI, A., BOMPARD, E., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 3, Volume 14, 2014.
Digital Object Identifier: 10.4316/AECE.2014.03008 [CrossRef] [Full text]
[2] Wide-Area Protection Fault Identification Algorithm Based on Multi-Information Fusion, Zhenxing Li, , Xianggen Yin, , Zhe Zhang, , Zhiqin He,, IEEE Transactions on Power Delivery, ISSN 0885-8977, Issue 3, Volume 28, 2013.
Digital Object Identifier: 10.1109/TPWRD.2013.2247638 [CrossRef]
[3] Post-processing of Deep Web Information Extraction Based on Domain Ontology, LIU, L., PENG, T., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 13, 2013.
Digital Object Identifier: 10.4316/AECE.2013.04005 [CrossRef] [Full text]
[4] A Regional Protection Partition Strategy Considering Communication Constraints and Its Implementation Techniques, Li, Zhenxing, Gong, Yang, Wang, Lu, Tan, Hong, Kativu, Prominent, Wang, Pengfei, Energies, ISSN 1996-1073, Issue 10, Volume 11, 2018.
Digital Object Identifier: 10.3390/en11102502 [CrossRef]
[5] New Fault Discrimination under the Influence of Rayleigh Noise, ZHANG, Y., WANG, Z., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 3, Volume 13, 2013.
Digital Object Identifier: 10.4316/AECE.2013.03005 [CrossRef] [Full text]
[6] Fault Identification Based on Nlpca in Complex Electrical Engineering, Zhang, Yagang, Wang, Zengping, Zhang, Jinfang, Journal of Electrical Engineering, ISSN 1335-3632, Issue 4, Volume 63, 2012.
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[7] Circuit theory approach for voltage stability assessment of reconfigured power network, Chitra, Subramanian, Devarajan, Narayanasamy, IET Circuits, Devices & Systems, ISSN 1751-858X, Issue 6, Volume 8, 2014.
Digital Object Identifier: 10.1049/iet-cds.2013.0325 [CrossRef]
[8] PCA Fault Feature Extraction in Complex Electric Power Systems, ZHANG, Y., WANG, Z., ZHANG, J., MA, J., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 3, Volume 10, 2010.
Digital Object Identifier: 10.4316/aece.2010.03017 [CrossRef] [Full text]
[9] MAP Fault Localization Based on Wide Area Synchronous Phasor Measurement Information, Zhang, Yagang, Wang, Zengping, International Journal of Emerging Electric Power Systems, ISSN 2194-5756, Issue 1, Volume 16, 2015.
Digital Object Identifier: 10.1515/ijeeps-2014-0107 [CrossRef]
[10] Universal Adaptive Differential Wavelet Energy-Based Protection Scheme for an AC Microgrid, Sahu, Sameep, Ansari, Salauddin, Gupta, Om Hari, Electric Power Components and Systems, ISSN 1532-5008, 2024.
Digital Object Identifier: 10.1080/15325008.2024.2313583 [CrossRef]
[11] A Novel Fault Identification Using WAMS/PMU, ZHANG, Y., WANG, Z., ZHANG, J., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 12, 2012.
Digital Object Identifier: 10.4316/aece.2012.02004 [CrossRef] [Full text]
[12] A Novel Approach to Fault Detection in Complex Electric Power Systems, ZHANG, Y., WANG, Z., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 3, Volume 14, 2014.
Digital Object Identifier: 10.4316/AECE.2014.03003 [CrossRef] [Full text]
[13] Software Tool for Real-Time Power Quality Analysis, MIRON, A., CHINDRIS, M. D., CZIKER, A. C., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 13, 2013.
Digital Object Identifier: 10.4316/AECE.2013.04021 [CrossRef] [Full text]
[14] Bayes-Based Fault Discrimination in Wide Area Backup Protection, WANG, Z., ZHANG, J., ZHANG, Y., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 1, Volume 12, 2012.
Digital Object Identifier: 10.4316/aece.2012.01015 [CrossRef] [Full text]
[15] Principal components fault location based on WAMS/PMU measure system, Wang, Zengping, Zhang, Yagang, Zhang, Jinfang, 2011 IEEE Power and Energy Society General Meeting, ISBN 978-1-4577-1000-1, 2011.
Digital Object Identifier: 10.1109/PES.2011.6039102 [CrossRef]
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Stefan cel Mare University of Suceava, Romania
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