Extended Petri net models for fault diagnosis for substation automation

Lo, K.L.; Ng, H.S.; Grant, Don; Trécat, J.

doi:10.1049/ip-gtd:19990071

Cited by 58 publications

(15 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(5) The delay of the circuit breaker relative to backup protective relay is: (6) The delay of the circuit breaker relative to second backup protective relay is:…”

Section: The Timing Characteristics Of Alert Informationmentioning

confidence: 99%

“…Step 3: Examination: This step checks whether the propagation process is completed by calculating the fuzzy min operation of and F. If the result is a null vector, the updating of the truth state transformation incomplete, so perform the equation (6). When transformation completed, the result of contains the confidence level of the fault device.…”

Section: The Reasoning Algorithm Of Cfdgmentioning

confidence: 99%

“…Of these approaches, expert systems [1][2]; artificial neural networks [3][4]; Petri nets [5][6]; optimization models [7]; Data Grid [8]; Cause-effect nets [9][10][11][12]; Bayesian networks [13] are the main methods. When obtaining the complete failure information, these methods can basically get satisfactory results [12].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fault Diagnosis Research for Power System Based on Timing Constraint Fuzzy Directed Graph

Chen¹,

Hui-Hao²,

Xiao³

et al. 2016

IJCA

View full text Add to dashboard Cite

show abstract

“…(5) The delay of the circuit breaker relative to backup protective relay is: (6) The delay of the circuit breaker relative to second backup protective relay is:…”

Section: The Timing Characteristics Of Alert Informationmentioning

confidence: 99%

Section: The Reasoning Algorithm Of Cfdgmentioning

confidence: 99%

See 1 more Smart Citation

Fault Diagnosis Research for Power System Based on Timing Constraint Fuzzy Directed Graph

Chen¹,

Hui-Hao²,

Xiao³

et al. 2016

IJCA

View full text Add to dashboard Cite

show abstract

“…It is discussed that application of Petri net reduces processing time and increases accuracy, thus methodology is more efficient than that the traditional approaches, especially when the complexity of the problem increases. Petri net models for fault diagnosis for substation automation discussed in [22] are the extension of the work presented in [21]. Here, backup and secondary backup have been included to improve the overall performance in fault diagnosis.…”

Section: Power System Protectionmentioning

confidence: 99%

Current Status of Petri Nets Theory in Power Systems

Jamil¹

2004

Electric Power Components and Systems

View full text Add to dashboard Cite

For the last two decades increasing attention has been given to Petri net's applications for the representation and analysis of large, complex, distributed, stochastic and discrete-event systems like flexible manufacturing, industrial control systems, communication protocol, distributed-software systems, distributed-database system, multiprocessor memory systems, data flow computing systems, fault-tolerant systems, and computer industries. Since power system is a large geographically wide distributed system, in the recent past, application of Petri net's theory in power systems have also been reported. This article presents literature survey of recent papers published in the area of power systems using Petri nets. Basics of Petri net's theory and its different forms applicable to power systems are also discussed. A method of detecting type of faults on three phase transmission line by using Petri net theory is discussed in details. Different examples based on Petri nets shows that such methodology is more efficient than the traditional approaches especially when the complexity of the problem increases.

show abstract

“…Enhanced with the well-established fuzzy logic, the fuzzy Petri nets (FPNs) [15][16][17][18][19][20], superior to the traditional Petri nets [21,22], are capable of modeling inexactness and uncertainties. Graphical FPN models are built in [16] for fault section identification, but the model structure is not optimized and the matrix execution algorithm is not addressed.…”

Section: Introductionmentioning

confidence: 99%