New approach to directional fault location for overhead power distribution feeders

Johns, A.T.; Lai, Loi Lei; El-hami, M.; Daruvala, D.J.

doi:10.1049/ip-c.1991.0044

Cited by 20 publications

(5 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The first is based on detecting fault-induced high frequency components. This enables the detection of discharges from the low-level breakdown of insulators; the fault direction is determined by filtering the output voltage from stack tuners and comparing the resulting signal levels on each side of a tuned trap circuit unit [2]. These methods are complex and expensive given their need for specially tuned filters.…”

Section: Introductionmentioning

confidence: 99%

A ‘Binocular’ Method for Detecting Faults in Electrical Distribution Networks with Distributed Generation

Alcalá¹,

Gonzalez-Juarez²,

Valino³

et al. 2016

ElAEE

View full text Add to dashboard Cite

The increase in the number of renewable energy generating facilities has transformed the electricity distribution network into a Distributed Generation (DG) system. This has given rise to a new monitoring scenario for protective devices already installed across radial distribution networks, which may execute unexpected and inappropriate protective actions that cause loss of supply to consumers. These devices are affected by the new condition of the electricity distribution network, as network currents vary. A common practice is to use electrical impedance-based fault localizers. This work describes a novel method for fault detection in radial networks with DG, which does not require knowing the electrical impedances of the lines that compose the network. The method only requires input data regarding the short circuit currents provided by the main feeder and the DG units in the area in which a fault has occurred. This information is sufficient to allow the area where the fault lies to be identified. The underlying idea is that the measurement of the current at two points provides a binocular view of the fault, thus allowing its location to be pinpointed. The method was tested using the IEEE 13-node test feeder system, locating different types of faults in different areas of a simulated radial network.

show abstract

Section: Introductionmentioning

confidence: 99%

A ‘Binocular’ Method for Detecting Faults in Electrical Distribution Networks with Distributed Generation

Alcalá¹,

Gonzalez-Juarez²,

Valino³

et al. 2016

ElAEE

View full text Add to dashboard Cite

show abstract

“…Roughly, it is possible to classify three different kinds of methods: (a) travelling-wave based methods [2,3]; (b) high-frequency components based methods [4,5]; and (c) impedance-based methods [6][7][8]. Travelling wave-based methods depend on wave propagation, which is a complex phenomena that is difficult to analyze with detailed precision due to sensitive dependency to system parameters and network configurations [9].…”

Section: Introductionmentioning

confidence: 99%

Optimal placement of faulted circuit indicators in power distribution systems

Almeida

Costa

Xavier‐de‐Souza

et al. 2011

Electric Power Systems Research

View full text Add to dashboard Cite

a b s t r a c tPower distribution utilities often use impedance-based methods for locating faults along their feeders. For feeders with laterals, these techniques may identify different possible locations for the same fault. This leads to higher costs and longer restoration time. In order to improve impedance-based methods, faultedcircuit indicators (FCI) can be allocated along the feeder to reduce, or even eliminate, the uncertainty about the fault location. This paper proposes a technique for optimally allocating a given number of FCIs along distribution feeders using the Chu-Beasley genetic algorithm to solve the optimization problem. The proposed objective functions measure the number of locations that are suspected to be the actual fault location or the distance among them. Additionally, it is possible to consider the presence of priority areas. We present results for the IEEE 34-bus system and for a 475-bus actual system. The results show the effectiveness of the proposed technique in improving impedance-based fault location methods.

show abstract

“…The methods used in this approach can be divided into two categories. The first category uses the high Frequency components of currents and voltages caused by the faults which start voltage and current travelling waves between the fault and the line terminals [1]. This method is similar to that proposed for transmission lines and is complex and expensive.…”

Section: Introductionmentioning

confidence: 99%

A new fault location technique on radial distribution systems using artificial neural network

Dehghani

Nezami

2013

22nd International Conference and Exhibition on Electricity Distribution (CIRED 2013)

View full text Add to dashboard Cite

In this paper, an effective fault location technique is proposed. Using the current samples of the distribution feeder measured at the substation, the proposed technique first determines the type of fault. Furthermore, an artificial neural network (ANN) is trained for each type of fault. The ANNs are trained to estimate the fault distance to the substation (FDANN).The Inputs of the ANNs are data of 3 phase voltages, currents and active powers of the feeder are measured at the substation in pre-fault and fault stages. The proposed method does not need data of loads of consumers. The proposed method is tested on IEEE 34-bus test feeder. Each ANN is trained by operating patterns. In order for ANNs cover the total operating space of the radial distribution network; fault location, fault resistance and loads are changed in each pattern. The outputs of ANNs for the operating test patterns, not presented in the training stage, are shown the accuracy of the ANNs. The trained FDANNs can estimate fault distance to the substation; even the structure of the distribution network is changed. Proposed method is effective while the input data are contained errors of measuring.

show abstract

New approach to directional fault location for overhead power distribution feeders

Cited by 20 publications

References 10 publications

A ‘Binocular’ Method for Detecting Faults in Electrical Distribution Networks with Distributed Generation

A ‘Binocular’ Method for Detecting Faults in Electrical Distribution Networks with Distributed Generation

Optimal placement of faulted circuit indicators in power distribution systems

A new fault location technique on radial distribution systems using artificial neural network

Contact Info

Product

Resources

About