Transformer Differential Protection

Transformer differential protection using wavelet transform

This paper will propose a cascade of minimum description length criterion with entropy approach along with artificial neural network (ANN) as an optimal feature extraction and selection tool for a wavelet packet transform based transformer differential protection. The proposed protection method provides a reliable and computationally efficient tool for distinguishing between internal faults and...

Differential Protection for Power Transformer Using Wavelet Transform and PNN

A new approach for protection of power transformer is presented using a time-frequency transform known as Wavelet transform. Different operating conditions such as inrush, Normal, load, External fault and internal fault current are sampled and processed to obtain wavelet coefficients. Different Operating conditions provide variation in wavelet coefficients. Features like energy and Standard dev...

Transformer differential protection with fuzzy logic based inrush stabilization ¬リニ

Second harmonic restraint is still commonly used to discriminate fault current and transformer inrush conditions. Such approach, however, has some disadvantages and limitations. Therefore various other criteria signals for power transformer inrush discrimination have been analysed. The paper presents a new multi-criteria stabilization algorithm that employs fuzzy reasoning technique for better ...

Numerical Differential Protection of Power Transformer using GA Trained ANN

This paper presents the use of ANN as a pattern classifier for differential protection of power transformer, which makes the discrimination among normal, magnetizing inrush, over-excitation, external fault and internal fault currents. The Back Propagation Neural Network Algorithm and Genetic Algorithm are used to train the multi-layered feed forward neural network and simulated results are comp...

Digital Differential Protection of Power Transformer Using Matlab