2017•Unpublished venueRequires access

A fault location method for feeder automation based on fault probability

Yu-Feng Forrest Lin, Mingjie Sun, Yiyun Guo, Yongzhi Chen, Yuhang Xu, Junyan Gao, Zhang We

Open publisher page 7 citations

Abstract

In order to solve the problem of distribution-feeder-automation fault-location in cases of misreporting or failed-reports of fault information, the characteristics of the fault indicator are analyzed, and the concept of the minimum fault location area of the distribution network is developed. Based on which, the mathematical model of fault location is evaluated. The characteristics of fault indicator signals are analyzed. Based on the two-in-three principle, a probabilistic fault-indicator combination-signal processing method is proposed. Based on the combination of the minimum fault-location area-model, the fault-indicator combination-signal and the interdependence between the fault indicators, a fault location method based on fault probability is proposed. The method is based on the similarity between the simulated fault signal and the real fault signal, and the detailed formula is given. The method has good fault-tolerance in the case of misreporting of, or of a failed-report of, fault information, and can more accurately determine the fault area. The fault probability of each area is given, and fault alternatives are provided. The proposed approach is feasible and valuable for the dispatching of maintenance personnel to deal with the fault.

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What this paper is about

In order to solve the problem of distribution-feeder-automation fault-location in cases of misreporting or failed-reports of fault information, the characteristics of the fault indicator are analyzed, and the concept of the minimum fault location area of the distribution network is developed. Based on which, the mathematical model of fault location is evaluated. The characteristics of fault indicator signals are analyzed. Based on the two-in-three principle, a probabilistic fault-indicator combination-signal processing method is proposed. Based on the combination of the minimum fault-location area-model, the fault-indicator combination-signal and the interdependence between the fault indicators, a fault location method based on fault probability is proposed. The method is based on the similarity between the simulated fault signal and the real fault signal, and the detailed formula is given. The method has good fault-tolerance in the case of misreporting of, or of a failed-report of, fault information, and can more accurately determine the fault area. The fault probability of each area is given, and fault alternatives are provided. The proposed approach is feasible and valuable for the dispatching of maintenance personnel to deal with the fault.

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Available abstract

In order to solve the problem of distribution-feeder-automation fault-location in cases of misreporting or failed-reports of fault information, the characteristics of the fault indicator are analyzed, and the concept of the minimum fault location area of the distribution network is developed. Based on which, the mathematical model of fault location is evaluated. The characteristics of fault indicator signals are analyzed. Based on the two-in-three principle, a probabilistic fault-indicator combination-signal processing method is proposed. Based on the combination of the minimum fault-location area-model, the fault-indicator combination-signal and the interdependence between the fault indicators, a fault location method based on fault probability is proposed. The method is based on the similarity between the simulated fault signal and the real fault signal, and the detailed formula is given. The method has good fault-tolerance in the case of misreporting of, or of a failed-report of, fault information, and can more accurately determine the fault area. The fault probability of each area is given, and fault alternatives are provided. The proposed approach is feasible and valuable for the dispatching of maintenance personnel to deal with the fault.

Key concepts: Fault (geology), Fault indicator, Stuck-at fault, Fault coverage, Fault model, Probabilistic logic, Automation, SIGNAL (programming language)

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