Locating Faults in Distribution Systems in the Presence of Distributed Generation using Machine Learning Techniques

Maruf, H M Mesbah; Muller, Felicitas; Hassan, Md. Shakawat; Chowdhury, Badrul

doi:10.1109/pedg.2018.8447728

Cited by 9 publications

(4 citation statements)

References 12 publications

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“…ANNs application to protection has drawn the attention of researchers [114, 115]. Although it can accurately detect the faulted segment, it has many disadvantages.…”

Section: Improvement Of Protection Systems In Distribution Network Wmentioning

confidence: 99%

“…Secondly, if the network configuration changes, the method is more likely to detect the faulted section incorrectly. Finally, the results indicate that ANN suffers from inaccuracy when a high impedance fault is developed, in which case the impedance fault cannot be predicted before the fault [115].…”

Section: Improvement Of Protection Systems In Distribution Network Wmentioning

confidence: 99%

See 1 more Smart Citation

Impact of distributed generation on the protection systems of distribution networks: analysis and remedies – review paper

Meskin

Domijan

Grinberg

2020

IET Generation, Transmission & Distribution

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“…ANNs application to protection has drawn the attention of researchers [114, 115]. Although it can accurately detect the faulted segment, it has many disadvantages.…”

Section: Improvement Of Protection Systems In Distribution Network Wmentioning

confidence: 99%

Section: Improvement Of Protection Systems In Distribution Network Wmentioning

confidence: 99%

Impact of distributed generation on the protection systems of distribution networks: analysis and remedies – review paper

Meskin

Domijan

Grinberg

2020

IET Generation, Transmission & Distribution

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“…A hybrid model combining SVM, decision tree, and ANN for FL is presented in ref. [20]. This model utilises current and voltage phasors to classify the faulted phase and identify the faulted line but only applies to single-phase faults.…”

Section: Introductionmentioning

confidence: 99%

Ensemble voting‐based fault classification and location identification for a distribution system with microgrids using smart meter measurements

et al. 2022

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This study presents an ensemble learning approach for fault classification and location identification in a smart distribution network containing photovoltaics (PV)-based microgrid. Lack of available data points and the unbalanced nature of the distribution system make fault handling a challenging task for utilities. The proposed method uses event-driven voltage data from smart meters to classify and locate faults. The ensemble voting classifier is composed of three base learners; random forest, k-nearest neighbours, and artificial neural network. The fault location (FL) task has been formulated as a classification problem where the fault type is classified in the first step and based on the fault type, the faulty bus is identified. The method is tested on IEEE-123 bus system modified with added PV-based microgrid along with dynamic loading conditions and varying fault resistances from 0 to 20 Ω for both unbalanced and balanced fault types. A further sensitivity analysis has been done to test the robustness of the proposed method under various noise levels and data loss errors in the smart meter measurements. The ensemble method shows improved performance and robustness compared to some previously proposed FL methods. Finally, the proposed method has been experimentally validated on a real-time simulation-based testbed using a state-of-the-art digital real-time simulator, industry standard DNP3 communication protocol and a cpu-based control centre running the FL algorithm.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…Por outro lado, métodos não analíticos, mas baseados em aprendizagem de máquina, têm sido aplicados para enfrentar os novos desafios propostos pela inserção de GD na rede. Entre esses métodos avaliados, estão as Redes Neurais Artificiais (RNAs), a Support Vector Machine (SVM), árvores de decisão e Adaptive Boosting (AdaBoost), além de outros métodos auxiliares como k-means, usado para predizer dados de medições incompletas (Maruf et al 2018).…”

Section: Introductionunclassified

A Localização de Faltas em um Sistema de Distribuição de Média Tensão com Geração Distribuída via Redes Neurais Artificiais

Paiva

Oleskovicz

2022

Proceedings IX Simpósio Brasileiro De Sistemas Elétricos

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This work aims to address the problem of fault location in a medium voltage distribution system in the presence of Distributed Generation (DG), applying artificial intelligence. The chosen method is learning-based through Artificial Neural Networks (ANNs). The methodology consisted of simulating three-phase faults via PSCAD/EMTDC software, pre-processing (normalization and formatting of training and test sets), empirical tests, routine tests without DG, routine tests with DG, and choosing the best ANN topology. The results presented illustrate the applied tests and the best ANN topology found.Resumo: Este trabalho tem como objetivo abordar o problema da localização de faltas em um sistema de distribuição de média tensão na presença de Geração Distribuída (GD), utilizando inteligência artificial. O método escolhido é baseado em aprendizagem pela aplicação de Redes Neurais Artificiais (RNAs). A metodologia consistiu na simulação de faltas trifásicas via o software PSCAD/EMTDC, no préprocessamento (normalização e formatação dos conjuntos de treinamento e de teste), e testes empíricos, testes sistemáticos sem GD, testes sistemáticos com GD, e na escolha da melhor topologia da RNA. Os resultados apresentados ilustram os testes aplicados e a escolha da melhor topologia da RNA encontrada.

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Locating Faults in Distribution Systems in the Presence of Distributed Generation using Machine Learning Techniques

Cited by 9 publications

References 12 publications

Impact of distributed generation on the protection systems of distribution networks: analysis and remedies – review paper

Impact of distributed generation on the protection systems of distribution networks: analysis and remedies – review paper

Ensemble voting‐based fault classification and location identification for a distribution system with microgrids using smart meter measurements

A Localização de Faltas em um Sistema de Distribuição de Média Tensão com Geração Distribuída via Redes Neurais Artificiais

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