Prony-Based Optimal Bayes Fault Classification of Overcurrent Protection

The development of deregulation and demand for high-quality electrical energy has lead to a new requirement in different fields of power systems. In the protection field, this means that high sensitivity and fast operation during the fault are required while maltripping of relay protection is not acceptable. One case that may lead to a maltrip of the high-sensitive overcurrent relay is the starting current of the induction motor or inrush current of the transformer. This transient current has the potential to affect the correct operation of protection relays close to the component being switched. In the case of switching events, such transients must not lead to overcurrent relay operation; therefore, a reliable and secure relay response becomes a critical matter. Meanwhile, proper techniques must be used to prevent maltripping of such relays, due to transient currents in the network. In this paper, the optimal Bayes classifier is utilized to develop a method for discriminating the fault from nonfault events. The proposed method has been designed based on extracting the modal parameters of the current waveform using the Prony method. By feeding the fundamental frequency damping and ratio of the 2nd harmonic amplitude over the fundamental harmonic amplitude to the classifier, the fault case is discriminated from the switching case. The suitable performance of this algorithm is demonstrated by simulation of different faults and switching conditions on a power system using PSCAD/EMTDC software.     

Wavelet-based mann and morrison algorithm for improvement of three-phase unbalanced voltage dips characterisation

This work introduces a method for improvement of characterisation of voltage dip using a new technique based on a discrete wavelet transform. The proposed method estimates the amplitude and phase angle of the system voltages. Fourier transform method was already used to determine these items. The responses of the relevant algorithms under such conditions have errors because of the drawbacks of the Fourier transform. The proposed method is a combination of the discrete wavelet transform for obtaining the sinusoidal waveform of the system voltages, and the Mann and Morrison algorithm, for estimating the amplitude and phase angle of the three-phase voltage, which is then used to characterise the voltage dip. The use of a three-point Mann and Morrison algorithm results in a quicker and more accurate response in determining the voltage dip type, than the Fourier transform method. This is particularly true when the voltage dip duration is very short.     

Improved Overcurrent Protection Using Symmetrical Components

Transient currents are quite common in power systems. They can be presented for both faults and switching events. In the case of switching events, such transients should not cause an overcurrent relay operation; therefore a dependable and secure relay response becomes a critical matter. Meanwhile, proper techniques must be used to prevent undesirable relay operations due to transient current and harmonics of current in the power system. This paper uses the concept of symmetrical components to discriminate fault from nonfault events. For this purpose, a criterion function is proposed using the above-mentioned components. The advantage of the proposed algorithm is shown by simulation of some typical transient currents due to transformer energizing and induction motor starting using EMTDC/PSCAD software