scholarly journals Fuzzy Timing Petri Net for Fault Diagnosis in Power System

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Alireza Tavakholi Ghainani ◽  
Abdullah Asuhaimi Mohd Zin ◽  
Nur ‘Ain Maiza Ismail
Keyword(s):  
Fault Diagnosis ◽  
Power System ◽  
Petri Net ◽  
Delay Time ◽  
Uncertain Information ◽  
Circuit Breakers ◽  
Inference Procedure ◽  
Use Of Time ◽  
Time Information ◽  
Firing Sequence

A model-based system for fault diagnosis in power system is presented in this paper. It is based on fuzzy timing Petri net (FTPN). The ordinary Petri net (PN) tool is used to model the protective components, relays, and circuit breakers. In addition, fuzzy timing is associated with places (token)/transition to handle the uncertain information of relays and circuits breakers. The received delay time information of relays and breakers is mapped to fuzzy timestamps,π(τ), as initial marking of the backward FTPN. The diagnosis process starts by marking the backward sub-FTPNs. The final marking is found by going through the firing sequence,σ, of each sub-FTPN and updating fuzzy timestamp in each state ofσ. The final marking indicates the estimated fault section. This information is then in turn used in forward FTPN to evaluate the fault hypothesis. The FTPN will increase the speed of the inference engine because of the ability of Petri net to describe parallel processing, and the use of time-tag data will cause the inference procedure to be more accurate.

A New Power System Fault Diagnosis Model under UNIX Platform

2014 ◽  
Vol 556-562 ◽  
pp. 2157-2160
Author(s):  
Lei Wang ◽  
Qing Chen ◽  
Zhan Jun Gao ◽  
Bin Chen ◽  
Min Wei Chen ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Power System ◽  
Information Fusion ◽  
Petri Net ◽  
High Performance ◽  
Intelligent Algorithm ◽  
Software Service ◽  
Diagnosis Model ◽  
Computing Method ◽  
Performance Computing

A new power system fault diagnosis model is proposed in this paper and it will be used in the UNIX platform. It includes the Petri net system's structure, software service and hardware integration method. Though technology of Petri net is quite successful, its application to power system fault diagnosis is deficient. According to the UNIX platform, a new power system fault diagnosis model is designed and it takes an example to explain how to use its high performance computing method (or parallel computing method) and UNIX environment to design a new intelligent algorithm with information fusion and multi-data resources in power system fault diagnosis.

scholarly journals Stochastic Programming-Based Fault Diagnosis in Power Systems Under Imperfect and Incomplete Information

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2565 ◽  
Author(s):  
Huizhong Song ◽  
Ming Dong ◽  
Rongjie Han ◽  
Fushuan Wen ◽  
Md. Salam ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Stochastic Programming ◽  
Power Systems ◽  
Power System ◽  
Programming Approach ◽  
Chance Constrained Programming ◽  
Circuit Breakers ◽  
On Line ◽  
Protective Relays ◽  
Constrained Programming

When a fault occurs in a section or a component of a given power system, the malfunctioning of protective relays (PRs) and circuit breakers (CBs), and the false and missing alarms, may manifestly complicate the fault diagnosis procedure. It is necessary to develop a methodologically appropriate framework for this application. As a branch of stochastic programming, the well-developed chance-constrained programming approach provides an efficient way to solve programming problems fraught with uncertainties. In this work, a novel fault diagnosis analytic model is developed with the ability of accommodating the malfunctioning of PRs and CBs, as well as the false and/or missing alarms. The genetic algorithm combined with Monte Carlo simulations are then employed to solve the optimization model. The feasibility and efficiency of the developed model and method are verified by a real fault scenario in an actual power system. In addition, it is demonstrated by simulation results that the computation speed of the developed method meets the requirements for the on-line fault diagnosis of actual power systems.

Fault Diagnosis Method of Vehicle Power System Using Bayesian Network

2014 ◽  
Vol 556-562 ◽  
pp. 3134-3138
Author(s):  
He Jia Li ◽  
Yan Wei Cheng ◽  
Cheng Yao ◽  
Hai Feng Xu ◽  
Zhao Yao ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Power System ◽  
Bayesian Network ◽  
Graph Model ◽  
Small Sample ◽  
Uncertain Information ◽  
Multiple Faults ◽  
Diagnosis Method ◽  
Mutual Relations ◽  
Network Fault

The fault diagnosis of vehicle power system that the structure and characteristics of components are complex, each module and internal modules exist coupling, cross-linked mutual relations and the uncertainties, the system status and working conditions are difficult to describe by precisely mathematical model, and test cost expensive, less fault samples. Thus its fault diagnosis is the decision problem of uncertain information in a small sample. it is proposed that combining multi-signal flow graph model with Bayesian network fault diagnosis method. The fault diagnosis model of power system and the corresponding Bayesian network structure are built, which achieve the fault diagnosis of power system, Diagnosis example shows that the method of the vehicle power has a higher failure troubleshooting capabilities of the system single and multiple faults.

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