2021
DOI: 10.1016/j.epsr.2020.106870
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Fault diagnosis method of distribution network based on time sequence hierarchical fuzzy petri nets

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Cited by 36 publications
(12 citation statements)
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“…From the DNS perspective, the fault is significantly related to an uncommon electric current state or unitability voltage [57,58]. From the failure statistics data, it is apparent that 80% of all customer interruptions are the leading cause of faults on DNS [59][60][61]. This is a condition required to control distribution faults in an effective and efficient approach to facilitate maintaining the quality of service by reducing the outage time [61].…”
Section: Change On Dns Fault Levelmentioning
confidence: 99%
“…From the DNS perspective, the fault is significantly related to an uncommon electric current state or unitability voltage [57,58]. From the failure statistics data, it is apparent that 80% of all customer interruptions are the leading cause of faults on DNS [59][60][61]. This is a condition required to control distribution faults in an effective and efficient approach to facilitate maintaining the quality of service by reducing the outage time [61].…”
Section: Change On Dns Fault Levelmentioning
confidence: 99%
“…Li et al [49] presented a layered fuzzy Petri net with a hierarchical structure for risk assessment. The fault diagnosis approach using time hierarchical fuzzy Petri net was proposed by Yuan et al [50]. The combination of fuzzy and colored PNs for runtime veryficaton of pacemaker was presented by Majma et al [51].…”
Section: Recent Studiesmentioning
confidence: 99%
“…According to (50), the vector of the new marking * M 0 takes the following form: * M 0 = Funding: This research was funded byPB23.EA.21.001.…”
Section: Conflicts Of Interestmentioning
confidence: 99%
“…Therefore, several fault diagnosis approaches of power systems for the aided decision making have been developed, such as expert systems [3], Bayesian networks [4], the rough set theory [5], artificial neural networks [6], Petri nets [7][8][9], cause-effect networks [10,11], the fuzzy theory [12], and spiking neural P systems (SNPSs) [13][14][15][16][17]. Among above methods, the SNPS is a class of distributed parallel computing models based on structures and functions of nerve cells.…”
Section: Introductionmentioning
confidence: 99%