Transformer protection by distinguishing inrush and fault current with harmonic analysis using fuzzy logic

Deshmukh, Madhura; Barhate, Vinay

doi:10.1109/iccre.2016.7476151

Cited by 10 publications

(1 citation statement)

References 5 publications

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“…In this context, other methods are employed, considering approaches that involve impedance-based techniques (Al-Tallaq et al 2003), Least-Square Method or Ordinary Least Squares (Rahman et al 1982), Artificial Neural Networks (Gondane et al 2018), Fuzzy Logic (Deshmukh et al 2016). Also, more broadly and recently, wavelet transform (Saleh et al 2003, Abbas et al 2016, Sendilkumar et al 2010, Megahed et al 2008, Jettanasen et al 2012.…”

Section: Introductionmentioning

confidence: 99%

Inrush Current Detection based on Linear Prediction

Chagas

Grimaldi

Montalvão

et al. 2020

Anais Do Simpósio Brasileiro De Sistemas Elétricos 2020

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The occurrence of inrush currents in power transformers is directly related with the reduction of its lifetime, as well as safe operation of electric power systems. In this paper, a new method for inrush current detection, based on linear prediction, is proposed. Linear predictors of order 2 and four are implemented, and the linear prediction error is employed as main parameter on the detection process. The methods performance is evaluated making use of a database built from simulations on Alternative Transients Program, and the modeled electric system is based on real distribution network. Aiming to evaluate the reliability of the method, Gaussian noise is added to the signals, and a noise sensitivity analysis is performed. The results indicate viability of linear prediction as a tool for fast and robust detection of inrush currents, which performed successfully in situations with SNR of 55 dB.

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