Open AccessModelling and detection of live tree‐related high impedance fault in distribution systems
Author(s) -
Bahador Nooshin,
Namdari Farhad,
Matinfar Hamid Reza
Publication year - 2018
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2017.0211
Subject(s) - tree (set theory) , computer science , wavelet , fault (geology) , kernel density estimation , electrical impedance , electric power system , kernel (algebra) , power (physics) , high impedance , block (permutation group theory) , biological system , pattern recognition (psychology) , algorithm , artificial intelligence , mathematics , engineering , statistics , biology , mathematical analysis , electrical engineering , paleontology , physics , geometry , quantum mechanics , combinatorics , estimator
Despite the importance of high‐impedance fault (HIF) modelling as a key issue in numerous power system studies, there is no single model accurately representing the behaviour of each type of HIFs. Tree‐related HIF (THIF) is a complex type that occurs when a power line comes in contact with a live tree. Given that available models for HIF cannot represent the expected behaviour of a live THIF, the need for a more accurate model seems obvious. So, in this study, based on experimental data obtained from measurements, the effective factors in HIF caused by live trees are studied and a new mathematical model of THIF provided in order to present the effects of both environmental conditions and biological classification. This model represents low and high frequency behaviours of THIFs, which are, respectively, derived in block‐oriented feed‐forward form and sinusoidal functions. Moreover, this study proposes a hybrid technique based on the combination of kernel density estimation and wavelet analysis to perform a feature extraction from THIF signals.