Distribution network fault section identification and fault location using artificial neural network

The Scientific Bulletin of Electrical Engineering Faculty

2019

Self Cite

Nowadays, many factors lead to selection and utilization of distributed generations (DG) in distributed networks. But more penetration of DG's in network faced with problem due to existence of passive and inactive distribution networks. One of these essential issues is voltage rise due to injection of active power generated by DG's. That in this paper, control strategies for controlling of voltage profile of distribution network and adjustment of increase of DG's penetration is assessed and an optimal strategy for voltage rise with mathematical formulation is presented that will include both local and coordinated control approaches of reactive power generation. Finally, in this paper an implementation plan with smart control tools of DG's is suggested.

Section: Reactive Power Generation Controlmentioning

confidence: 99%

“…The applied algorithm on the explained network is done in mode of N G =N=3. Three nodes that have voltage drop include V b = (7,11,17).…”

Section: Calculation Of Matrix [A]mentioning

confidence: 99%

Voltage Control in Distribution Networks in Presence of Distributed Generators Based on Local and Coordinated Control Structures

The Scientific Bulletin of Electrical Engineering Faculty

2019

Self Cite

“…Fault locating algorithms presented in [9][10][11][12], and also the method presented in this article are of this type. In [19][20][21][22][23], the artificial neural network is used to detect the faulted section and fault location.…”

Section: Introductionmentioning

confidence: 99%

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

The Scientific Bulletin of Electrical Engineering Faculty

2019

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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.

“…Various methods have hitherto been proposed for fault detection to accelerate network repair and improve reliability [1]. Moreover, in addition to fault-finding methods, methods are proposed to determine the section or distance of fault, especially in distribution networks [2].…”

Section: Introductionmentioning

confidence: 99%

“…Learning-based strategies, if executed properly in different conditions and despite the certainty in the system, can show acceptable flexibility and performance. The extraction of efficient features and the application of an appropriate learning algorithm are two main and influential issues in the foundation of learning-based methods [2], [9].…”

Section: Introductionmentioning

confidence: 99%

Fault Location in the Transmission Network Based on Extraction of Fault Components Using Wavelet Transform

The Scientific Bulletin of Electrical Engineering Faculty

2019

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In this paper, a Discrete Wavelet Transform (DWT) has been utilized for processing the current signal in order to fault-location evaluation in network transmission using pre-fault and post-fault current data of both the terminals of a transmission line. In fact, the basis of the work is based on the information recorded before the fault at the end of the line and after the fault at the beginning of the line received by the relay. Obviously, high-frequency components are created at the time of the fault, which is a way of extracting these components using a wavelet transform. In this design, characteristics extorted from synchronous recording of three-phase current signals at the two terminals using DWT. In the following, can accurately estimate the exact location of the fault in the transmission network by extraction and subtracting of the minimum and maximum components of the DWT approximate and detail components of the signal before and after the fault (pre-fault and post-fault). The simulation results reveal that the minimum and maximum extracted components are highly dependent on the fault resistance. Hence, due to increase the fault resistance, the level of signal decomposition has to be increased so that the algorithm is not compromised. Eventually, the proposed method is tested on the transmission network of 735 kV at different distances of the transmission line, which indicates that the proposed algorithm can accurately estimate the fault distance, depending on the type of fault (including low-impedance and high-impedance fault) by changing the signal decomposition level.