<abstract xmlns="http://www.w3.org/1999/xhtml"><p>One of the most important issues in employing distribution networks is detecting the fault location in medium-voltage distribution feeders. Due to the vastness of distribution networks and growing distributed generation (DG) sources in this network, detection is difficult with the common methods. The aim of this paper is to present a method based on voltage distributed meters in a medium-voltage distribution network (by smart meters installed along the feeder) in order to detect the fault location in the presence of DG sources. Due to vastness of distribution network and cost of installing smart meters, it is not economically possible to install meters in all the Buses of the network. That’s why in this article, combination of genetic and locating algorithms and fault-based on voltage drop has been used to suggest a method to optimize the meter locations. In order to evaluate the efficiency of the method suggested, first we determine the optimal number and location of the meters and then we apply the fault that has been simulated in different Buses of the sample network, using PSCAD/EMTDC software. After results analysis, the fault location is estimated by MATLAB. Simulation results show that the fault locating method by optimal number of meters has good efficiency and accuracy in detecting faults in different spots and in different resistance ranges.</p></abstract>

One of the most important issues in employing distribution networks is detecting the fault location in medium-voltage distribution feeders. Due to the vastness of distribution networks and growing distributed generation (DG) sources in this network, detection is difficult with the common methods. The aim of this paper is to present a method based on voltage distributed meters in a medium-voltage distribution network (by smart meters installed along the feeder) in order to detect the fault location in the presence of DG sources. Due to vastness of distribution network and cost of installing smart meters, it is not economically possible to install meters in all the Buses of the network. That’s why in this article, combination of genetic and locating algorithms and fault-based on voltage drop has been used to suggest a method to optimize the meter locations. In order to evaluate the efficiency of the method suggested, first we determine the optimal number and location of the meters and then we apply the fault that has been simulated in different Buses of the sample network, using PSCAD/EMTDC software. After results analysis, the fault location is estimated by MATLAB. Simulation results show that the fault locating method by optimal number of meters has good efficiency and accuracy in detecting faults in different spots and in different resistance ranges.

Detecting the Fault Section in the Distribution Network with Distributed Generators Based on Optimal Placement of Smart Meters

Electrical Engineering Department, Bushehr branch

The Scientific Bulletin of Electrical Engineering Faculty

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

One of the most important issues in employing distribution networks is detecting the fault location in medium-voltage distribution feeders. Due to the vastness...

Detecting the Fault Section in the Distribution Network with Distributed Generators Based on Optimal Placement of Smart Meters

Publié en ligne: 21 nov. 2019

Pages: 28 - 34

DOI: https://doi.org/10.1515/sbeef-2019-0017

Mots clés
Fault location, optimal placement, feeder smart meters, distributed generation sources

© 2019 Majid Dashtdar et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Detecting the Fault Section in the Distribution Network with Distributed Generators Based on Optimal Placement of Smart Meters

Publié en ligne: 21 nov. 2019

Pages: 28 - 34

DOI: https://doi.org/10.1515/sbeef-2019-0017

Mots clésFault location, optimal placement, feeder smart meters, distributed generation sources

© 2019 Majid Dashtdar et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
Fault location, optimal placement, feeder smart meters, distributed generation sources