Fault Section Identification in Distribution Networks with DFIG and PMSG Generators Using Current Transients

Authors

Keywords:

Distribution Network, Fault Section Identification Machine learning, Discrete Wavelet Transform, Wind Power

Abstract

This paper presents a methodology for fault section identification (FSI) in distribution networks with embedded wind power generation. The phase currents are measured only at the distribution substation (DS), using a waveform window of two cycles (one before and one after the fault detection). The proposed approach is divided into two stages: the first stage, Fault Identification (FI), aims to identify whether a short-circuit fault lies on a main feeder or one of the branches effectively addressing the challenge of multiple fault locations that may arise when several branches correspond to the estimated fault point; the second stage, Fault Location (FL), estimates the distance between the DS and the fault location. The algorithm employs discrete wavelet transform (DWT) in combination with artificial neural networks (ANNs). Energy and Relative Energy Entropy, both in per unit (EPU and REEPU), are proposed and calculated from DWT decomposition, with regularization indexes applied to EPU and REEPU. These indexes serve as input to multi-layer ANN models, which work as classifiers for FI and predictors for FL. Various fault scenarios with different fault inception angle, fault type, fault resistance and fault location are simulated using MATLAB® software and the IEEE 34-node benchmark feeder as test system. The results demonstrate that the proposed methodology performs effectively the FSI task, achieving an accuracy of up to 95% for FI and a maximum error of 5.2% for FL.

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Author Biographies

Juan Carlos Peqqueña Suni, Universidade Federal do Ceará

Juan Carlos Peqquena Suni was born in Arequipa, Peru. He received the Ph.D. degree in 2024 in electrical engineering from State University of Campinas (UNICAMP), Campinas in Brazil. He is currently a professor of Electrical Engineering at the Federal University of Ceará (UFC), Sobral campus in Brazil, where he has been teaching and conducting research in electrical power systems since 2014. His areas of interest include synchronous machine parameters, analysis of distribution systems and renewable energies using artificial intelligence.

M.G.S.P. Paredes, Universidade Estadual de Campinas

Mariana Pérez received a B.S. degree in electronic engineering from the Technological University of Peru, Lima, Peru, and M.S. and Ph.D. degrees in electrical engineering from the University of Campinas, Campinas, Brazil, in 2013 and 2018, respectively. From 2015 to 2016 I worked at the Hitachi Research Laboratory, Japan, in its green mobility field. She is a postdoctoral researcher at the Faculty of Mechanical Engineering at the University of Campinas (UNICAMP), Brazil. Her research focuses on interests include renewable energy, electric machine drives, and electric vehicles.

M.V. de Paula, Universidade Estadual de Campinas

Marcelo Vinicius received the B.S. degree in electrical engineering from the Federal University of Goias, Brazil, in 2016, the M.Sc. degree in electrical engineering from University of Campinas (UNICAMP), Campinas, Brazil, in 2018, and Ph.D. in mechatronics engineering from UNICAMP, Campinas, Brazil, 2022. Currently, he is a Professor at Faculty of Mechanical Engineering of UNICAMP.  He involves in the areas of electric machines and drives, power electronics, and transportation electrification. His research interests include renewable energy, electric machine drives and electric vehicles.

E. Ruppert Filho, Universidade Estadual de Campinas

Ernesto Ruppert was born in Jundiaí, Sao Paulo, Brazil. He got the B.Sc degree in Electrical Engineering in 1971, MSc degree in 1974 and PhD degree in 1982 at Computer and Electrical Engineering School of the Campinas State University in Brazil (UNICAMP). During his professional life he worked as project engineer and/or as consultant for several large companies such as Itaipu, Petrobras, General Electric, Alstom, Copel, CPFL, and Elektro in Brazil and abroad. He has been with the Campinas State University (UNICAMP) in Campinas, Brazil, since 1972 as Professor and Researcher. His research interests are power electronics, superconductor current limiters, electrical power systems, distributed generation, electric machines and motor drives. He has published many technical papers in international journals and conferences and has advised several M.Sc. and PhD thesis along his career.

J.A. Martinez-Velasco, Universitat Politecnica de Catalunya

Juan Martinez was born in Barcelona, Spain. He received the Ph.D. degree in 1982 from the Universitat Politecnica de Catalunya (UPC), Barcelona, Spain. He was with the Department of Electrical Engineering, UPC. He is retired since September 2017. His teaching and research interests included transmission and distribution, power system analysis, and Electro Magnetic Transients Program (EMTP) applications.

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Published

2025-05-14

How to Cite

Peqqueña Suni, J. C., Pérez Paredes , M. G. S. ., Vinicius de Paula , M., Ruppert Filho, E., & Martinez Velasco, J. A. (2025). Fault Section Identification in Distribution Networks with DFIG and PMSG Generators Using Current Transients . IEEE Latin America Transactions, 23(6), 487–496. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/9488

Issue

Vol. 23 No. 6 (2025): Ordinary Issue

Section

Electric Energy