Fault Location Prediction in Power Transmission Lines Using an Artificial Neural Network Model

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dc.contributor.authorAlpsalaz, Feyyaz
dc.contributor.authorYalcinoz, Zehva
dc.contributor.authorKaygusuz, Asim
dc.contributor.authorMamis, Mehmet Salih
dc.date.accessioned2026-04-04T13:18:58Z
dc.date.available2026-04-04T13:18:58Z
dc.date.issued2024
dc.departmentİnönü Üniversitesi
dc.description8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024 -- 21 September 2024 through 22 September 2024 -- Malatya -- 203423
dc.description.abstractEnergy transmission lines are an important element that ensures the sustainability of existing living conditions and the uninterrupted need for electricity. Therefore, it is of great importance to locate short circuit faults that may occur in transmission lines and to intervene in these faults immediately. In this study, a fault location study is carried out in a power system designed as a real line model. Firstly, a 478.9 km long transmission line with three transpositions was created using the EMTP/ATP program. The study starts from a point close to the beginning of the line until the first transposition, and a three-phase ground fault is simulated in the system at certain intervals. The input current and voltage values of the line are then taken. The obtained data were analyzed by applying Modal Transformation to the current and voltage signals in the fault condition. Thus, the occurrence of high-frequency harmonics of the fault condition is characterized. Afterwards, in order to locate the fault in the system, Fast Fourier Transform (FFT) spectra were obtained using MATLAB software. These spectra were trained with Artificial Neural Networks (ANN) using fault data analyzed at 74 different points, and the fault location was determined with 99% accuracy. © 2024 IEEE.
dc.identifier.doi10.1109/IDAP64064.2024.10710637
dc.identifier.isbn979-833153149-2
dc.identifier.scopus2-s2.0-85207894295
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/IDAP64064.2024.10710637
dc.identifier.urihttps://hdl.handle.net/11616/108042
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20250329
dc.subjectartificial neural networks
dc.subjectfault location
dc.subjectFFT
dc.subjectpower transmission lines
dc.titleFault Location Prediction in Power Transmission Lines Using an Artificial Neural Network Model
dc.typeConference Object

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