Power System Fault Detection Automation Based on Fuzzy Logic

Petrović, Ivica; Nikolovski, Srete; Glavaš, Hrvoje; Relić, Filip

doi:10.1109/sst49455.2020.9264039

Cited by 5 publications

(1 citation statement)

References 13 publications

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“…The analysis of competencies and protection requirements are carried out by considering the basic principles of harmonization of relay protection, where the design and dimensioning of devices and relay protection must be harmonized and performed with the associated software tools. Since there are many possible applications of failure analysis, it is of high importance to predefine the achievability of the analysing algorithm and possible improvements of its applications [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

A New Protection System Design of Active MV Distribution Network

Provči¹,

Stojkov

Marić

et al. 2023

Teh. vjesn.

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The increasing implementation of renewable energy sources (RES), along with the diversity of energy source types, has additionally imposed significant operational and management problems in distribution networks. These problems are manifested in voltage regulations, system stability and coordination of protection, both in the distribution and transmission networks. For the medium voltage (MV) network, this includes new energy sources and higher amounts of fault currents, invisibility of several faults in the existing protection scheme, reduction of the range of protection devices and reduction of the possibility of detecting small fault currents with existing protection relays. Such changes significantly reduce the possibility of proper distribution system protection, both in subordinate and superior networks. The subject of this paper is the presentation of a new concept of the use of automation in the management and arrangement of power system protection dependent on the scheme and configuration of an active MV network. The goals of this analysis and research are to find and define the necessary architecture in which the scheme and appearance of the MV network should be automatically detected, and based on network topology to establish new settings of protection devices (ground fault, overcurrent and short circuit protection). The contributions of generation units of RES in the MV network must be considered. This paper specifically analyses the problems of power system management with simultaneous harmonization of protection systems both in the transmission and in the radial distribution network, offering optimization algorithms that have the ability of achieving the optimal solution. The implementation of the proposed technique was tested on a radial connection integrated with a microgrid (MG) which has the possibility of two-way power supply. The obtained results indicate that the proposed technique can solve described problems in the coordination of protection system and network management, even with the dynamic character of operation mode of the networks.

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Section: Introductionmentioning

confidence: 99%

A New Protection System Design of Active MV Distribution Network

Provči¹,

Stojkov

Marić

et al. 2023

Teh. vjesn.

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Fault detection and classification in overhead transmission lines through comprehensive feature extraction using temporal convolution neural network

Tunio,

Hashmani,

Khokhar

et al. 2024

Engineering Reports

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Faults in transmission lines cause instability of power system and result in degrading end users sophisticated equipment. Therefore, in case of fault and for the quick restoration of problematic phases, reliable and accurate fault detection and classification techniques are required to categorize the faults in a minimum time. In this work, 500 kV transmission line (Jamshoro‐New Karachi), Sindh, Pakistan has been modeled in MATLAB. The discrete wavelet transform (DWT) has been used to extract features from the transient current signal for different faults in 500 kV transmission line under various parameters such as fault location, fault inception angle, ground resistance and fault resistance and time series data has been obtained for fault classification. Moreover, the temporal convolutional neural network (TCN) is used for fault classification in 500 kV transmission network due to its robust framework. From simulation results, it is found that faults in 500 kV transmission line are classified with 99.9% accuracy. Furthermore, the simulation results of the TCN model compared to bidirectional long short‐term memory (BiLSTM) and Gated Recurrent Unit (GRU) and it has been found that TCN model is capable of classifying faults in 500 kV transmission line with high accuracy due to its ability to handle long receptive field size, less memory requirement and parallel processing due to dilated causal convolutions. Through this work, the meantime to repair of 500 kV transmission line can be reduced.

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Circuit Breaker Condition Based Maintenance Using Advanced Fault Detection and Analysis on COMTRADE Event Data

Silva

Amaro

2022

Controlo 2022

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Power System Fault Detection Automation Based on Fuzzy Logic

Cited by 5 publications

References 13 publications

A New Protection System Design of Active MV Distribution Network

A New Protection System Design of Active MV Distribution Network

Fault detection and classification in overhead transmission lines through comprehensive feature extraction using temporal convolution neural network

Circuit Breaker Condition Based Maintenance Using Advanced Fault Detection and Analysis on COMTRADE Event Data

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