2010•Unpublished venueRequires access

An improved fault locating system of distribution network based on fuzzy identification

Xiaohui Zhu, Xin Lü, Dong Liu, Zhang Bingda

Open publisher page 5 citations

Abstract

Fault locating system, which is designed for the fast power recovery, is very important in the economical operating of the distribution network. But, for the uncertainty of the fault information, the incorrect conclusion may be obtained by the traditional fault location calculation, so the most fault locating system can not be employed in the distribution network. In this paper, an improved fault locating system is proposed, which is composed of the fault signal acquisition unit and the fault location analysis center. Fuzzy identification is employed in the fault location analysis center to deal with the uncertainty of fault information. The failure and mistake rates of indicator action are used as the fuzzy parameters to calculate the fuzzy difference of the fault sequence and the standard fault set. The fault indicator is the primary device of fault information acquisition. The radio frequency and GPRS technology construct the communication channel of fault signal acquisition unit, which cuts down the construction cost and also ensures the obtaining accuracy of the fault information. The fault location system is working on the distribution network and operating well. With the accurate fault location, power supply recovers fast. The loss of power failure is reduced effectively.

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What this paper is about

Fault locating system, which is designed for the fast power recovery, is very important in the economical operating of the distribution network. But, for the uncertainty of the fault information, the incorrect conclusion may be obtained by the traditional fault location calculation, so the most fault locating system can not be employed in the distribution network. In this paper, an improved fault locating system is proposed, which is composed of the fault signal acquisition unit and the fault location analysis center. Fuzzy identification is employed in the fault location analysis center to deal with the uncertainty of fault information. The failure and mistake rates of indicator action are used as the fuzzy parameters to calculate the fuzzy difference of the fault sequence and the standard fault set. The fault indicator is the primary device of fault information acquisition. The radio frequency and GPRS technology construct the communication channel of fault signal acquisition unit, which cuts down the construction cost and also ensures the obtaining accuracy of the fault information. The fault location system is working on the distribution network and operating well. With the accurate fault location, power supply recovers fast. The loss of power failure is reduced effectively.

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Available abstract

Fault locating system, which is designed for the fast power recovery, is very important in the economical operating of the distribution network. But, for the uncertainty of the fault information, the incorrect conclusion may be obtained by the traditional fault location calculation, so the most fault locating system can not be employed in the distribution network. In this paper, an improved fault locating system is proposed, which is composed of the fault signal acquisition unit and the fault location analysis center. Fuzzy identification is employed in the fault location analysis center to deal with the uncertainty of fault information. The failure and mistake rates of indicator action are used as the fuzzy parameters to calculate the fuzzy difference of the fault sequence and the standard fault set. The fault indicator is the primary device of fault information acquisition. The radio frequency and GPRS technology construct the communication channel of fault signal acquisition unit, which cuts down the construction cost and also ensures the obtaining accuracy of the fault information. The fault location system is working on the distribution network and operating well. With the accurate fault location, power supply recovers fast. The loss of power failure is reduced effectively.

Key concepts: Fault indicator, Fault (geology), Stuck-at fault, Fault coverage, Fault model, Real-time computing, Fuzzy logic, Computer science

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