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A Fault Diagnosis Method for Power Transmission Networks Based on Spiking Neural P Systems with Self-Updating Rules considering Biological Apoptosis Mechanism
Joint Authors
Wei, Xiaoguang
Huang, Tao
Wang, Tao
Wang, Jun
Liu, Wei
Zang, Tianlei
Huang, Zhu
Li, Chuan
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-01-21
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Abstract EN
Power transmission networks play an important role in smart girds.
Fast and accurate faulty-equipment identification is critical for fault diagnosis of power systems; however, it is rather difficult due to uncertain and incomplete fault alarm messages in fault events.
This paper proposes a new fault diagnosis method of transmission networks in the framework of membrane computing.
We first propose a class of spiking neural P systems with self-updating rules (srSNPS) considering biological apoptosis mechanism and its self-updating matrix reasoning algorithm.
The srSNPS, for the first time, effectively unitizes the attribute reduction ability of rough sets and the apoptosis mechanism of biological neurons in a P system, where the apoptosis algorithm for condition neurons is devised to delete redundant information in fault messages.
This simplifies the complexity of the srSNPS model and allows us to deal with the uncertainty and incompleteness of fault information in an objective way without using historical statistics and expertise.
Then, the srSNPS-based fault diagnosis method is proposed.
It is composed of the transmission network partition, the SNPS model establishment, the pulse value correction and computing, and the protection device behavior evaluation, where the first two components can be finished before failures to save diagnosis time.
Finally, case studies based on the IEEE 14- and IEEE 118-bus systems verify the effectiveness and superiority of the proposed method.
American Psychological Association (APA)
Liu, Wei& Wang, Tao& Zang, Tianlei& Huang, Zhu& Wang, Jun& Huang, Tao…[et al.]. 2020. A Fault Diagnosis Method for Power Transmission Networks Based on Spiking Neural P Systems with Self-Updating Rules considering Biological Apoptosis Mechanism. Complexity،Vol. 2020, no. 2020, pp.1-18.
https://search.emarefa.net/detail/BIM-1141006
Modern Language Association (MLA)
Liu, Wei…[et al.]. A Fault Diagnosis Method for Power Transmission Networks Based on Spiking Neural P Systems with Self-Updating Rules considering Biological Apoptosis Mechanism. Complexity No. 2020 (2020), pp.1-18.
https://search.emarefa.net/detail/BIM-1141006
American Medical Association (AMA)
Liu, Wei& Wang, Tao& Zang, Tianlei& Huang, Zhu& Wang, Jun& Huang, Tao…[et al.]. A Fault Diagnosis Method for Power Transmission Networks Based on Spiking Neural P Systems with Self-Updating Rules considering Biological Apoptosis Mechanism. Complexity. 2020. Vol. 2020, no. 2020, pp.1-18.
https://search.emarefa.net/detail/BIM-1141006
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1141006