• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.107_108
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• 2009

In this paper, a fault section detection algorithm to be considered variety measurement devices is proposed in ungrounded diatribution network. Ungrounded network is different from grounded netork. It's that a fault current doesn't generate when a single grounded fault by characteristic of ungrounded network. So, a fault section detection is very difficult. Thus, in this paper, a fault section detection method is proposed by data from variety measurement devices. The method is proved by matlap simulink.

• Journal of Electrical Engineering and Technology
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• v.3 no.4
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• pp.484-490
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• 2008

In this paper, an integrated fault section detection and isolation strategy is proposed based on the application of the Distribution Automation System(DAS) utilizing advanced IT and communication technologies. The Feeder Remote Terminal Unit(FRTU) has been widely used to collect data in the Korean distribution system. The achieved data is adopted in this method for detecting multiple fault types. Especially in the case of single phase-to-ground fault, the fault section is detected by comparison of the zero-sequence current phase angle. The test results have verified the effectiveness of the proposed method in a radial distribution system through extensive simulations in Matlab/Simulink. Furthermore, a communication-based demo system identical to the simulation model has been developed, and it can be applied as an online monitoring and control program for fault section detection and isolation.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2118-2126
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• 2017

The large-scale power system blackouts have indicated that conventional protection relays that based on local signals cannot fit for modern power grids with complicated setting or heavily loaded-flow transfer. In order to accurately detect various faulted lines and improve the fault-tolerance of wide-area protection, a novel multi-section weighed fault matching and detecting algorithm is proposed. The real protection vector (RPV) and expected section protection vectors (ESPVs) for five fault sections are constructed respectively. The function of multi-section weighed fault matching is established to calculate the section fault matching degrees between RPV and five ESPVs. Then the fault degree of protected line based on five section fault degrees can be obtained. Two fault detecting criterions are given to support the higher accuracy rate of detecting fault. With the enumerating method, the simulation tests illustrate the correctness and fault-tolerance of proposed algorithm. It can reach the target of 100% accuracy rate under 5 bits error of wide-area protections. The influence factors of fault-tolerance are analyzed, which include the choosing of wide-area protections, as well as the topological structures of power grid and fault threshold.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.31-32
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• 2007

In this paper, a fault section detection method is proposed for ungrounded system in the case of a single line-to-ground fault. A conventional method is used for faulted feeder selection according to the angular relationship between zero-sequence currents of the feeders and zero-sequence voltage of the system. Fault section detection is based on the comparison of phase angle of zero-sequence current. Proposed method has been testified in a demo system by Matlab/Simulink simulations. Based on Distribution Automation System(DAS), Feeder Remote Terminal Unit(FRTU) is used to collect those necessary data, at present a demo system is under developing using Manufacturing Message Specification (MMS) in IEC61850 standard.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.10
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• pp.2619-2627
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• 2009

The ground fault is occupying 70% among the total number of faults in ungrounded distribution power system. When the ground fault occurs in ungrounded system, the fault current is so small that it is hard to detect. But fault handling is very important because to continue power supply during fault conditions may cause the fault spreading and the distribution device in trouble. This paper presents the fault line detection method by using GPT signal detecting zero sequence voltage, and the fault section detection method by detecting whether GPT signal is disappeared or not during shifting normally open switch, which is connecting switch between distribution lines with open state in order to restore the outage area under emergency situation, and during isolating each section one by one which belongs to the fault line. This method is efficient because there is no whole power interruption during the fault section detection, and it is possible to perform both the fault section detection and the service restoration for the outage area at the same time, and it can apply to various distribution system configuration. Program for the fault restoration was developed applying proposed method, and it has been validated by applying to the pilot project of distribution automation system in Vietnam which has the ungrounded distribution system.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.487-488
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• 2007

Fault section detection and service restoration is very important in ungrounded distribution system. Techniques currently used to track down faults are time consuming and cumbersome. A new scheme is developed based on communication technology, and the simulation result shows that the method can satisfy the requirement proposed.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.2
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• pp.53-57
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• 2001

This paper presents the new methods of fault diagnosis through multiple alarm processing of protective relays and circuit breakers in power systems using probabilistic neural networks. In this paper, fault section detection neural network (FSDNN) for fault diagnosis is designed using the alarm information of relays or circuit breakers. In contrast to conventional methods, the proposed FSDNN determines the fault section directly and fast. To show the possibility of the proposed method, it is simulated through simulation panel for Sinyangsan substation system in KEPCO (Korea Electric Power Corporation) and the case studies show the effectiveness of the probabilistic neural network mehtod for the fault diagnosis.

• International Journal of Contents
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• v.8 no.4
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• pp.1-6
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• 2012

Mutual Exclusion is one of the most studied topics in distributed systems where processes communicate by asynchronous message passing. It is often necessary for multiple processes at different sites to access a shared resource or data called a critical section (CS) in distributed systems. A number of algorithms have been proposed to solve the mutual exclusion problem in distributed systems. In this paper, we propose the new algorithm which is modified from Garg's algorithm[1] thus works properly in a fault-tolerant system. In our algorithm, after electing the token generator, the elected process generates a new token based on the information of the myreqlist which is kept by every process and the reqdone which is received during election. Consequently, proposed algorithm tolerates any number of process failures and also does even when only one process is alive.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.125-127
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• 1999

We generally use Yes-No algorithms for feeder automation algorithm. This logic determines the faulty section by fault current detection information of the fault indicators of each switches in distribution feeder. This paper presents the data acquisition method such as breaker's open status in fault and the determination method of faulty section using fault indicator's information of each switches.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.10
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• pp.1321-1327
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• 2014

Faulted section identification is one of the most important function in distribution automation systems. Conventional over current detection based fault indicators frequently mal-operate due to the reverse fault current from the renewable energy resources. This paper present a new faulted section identification method based on the fuzzy decision making technique. In order to establish feasibility of the proposed method, case studies using Matlab Simulink has been performed.