Fault diagnosis system for large power generation station and its transmission lines based on fuzzy relations
Summary This paper proposes a fault diagnosis system based on the fuzzy relation theory to estimate the faulty item/section(s) of a large power generation station and its transmission lines. Therefore, it diagnoses the faulted item/section(s) in terms of the degree of membership. Besides that, it al...
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Published in | International transactions on electrical energy systems Vol. 25; no. 5; pp. 753 - 769 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Hoboken
Blackwell Publishing Ltd
01.05.2015
Hindawi Limited |
Subjects | |
Online Access | Get full text |
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Summary: | Summary
This paper proposes a fault diagnosis system based on the fuzzy relation theory to estimate the faulty item/section(s) of a large power generation station and its transmission lines. Therefore, it diagnoses the faulted item/section(s) in terms of the degree of membership. Besides that, it also examines the mis‐operation of corresponding circuit breakers. The proposed method utilizes the final information of protective relays and corresponding circuit breakers to build the sagittal diagrams which represent the fuzzy relations for each item/section(s). In order to testify the validity and feasibility of that method, a computer simulation of High Dam power generation station and its 500 kV double‐circuit transmission lines is used. It is shown from two study cases that proposed fault diagnosis system is useful in diagnosing multiple faults as well as simple faults. Moreover, it has rapid reasoning, correct efficient and using flexible in a power generation station and its transmission lines for online fault diagnosis. Finally, it enables, assists and supports the operator of the power generation station control room to make the right decision, especially in case of loss of the communication with the dispatch center. Copyright © 2014 John Wiley & Sons, Ltd. |
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Bibliography: | ArticleID:ETEP1782 ark:/67375/WNG-TQK0XJSD-L istex:F62F632D5A58581F7A8826A125CB93FF099E333B |
ISSN: | 2050-7038 2050-7038 |
DOI: | 10.1002/etep.1782 |