Application of Probabilistic Neural Networks Using High-Frequency Components’ Differential Current for Transformer Protection Schemes to Discriminate between External Faults and Internal Winding Faults in Power Transformers

Internal and external faults in a power transformer are discriminated in this paper using an algorithm based on a combination of a discrete wavelet transform (DWT) and a probabilistic neural network (PNN). DWT decomposes high-frequency fault components using the maximum coefficients of a ¼ cycle DWT as input patterns for the training process in a decision algorithm. A division algorithm between a zero sequence of post-fault differential current waveforms and the differential current coefficient in the ¼ cycle DWT is used to detect the maximum ratio and faults. The simulation system uses various study cases based on Thailand’s electricity transmission and distribution systems. The simulation results demonstrated that the PNN and BPNN are effectively implemented and perform fault detection with satisfactory accuracy. However, the PNN method is most suitable for detecting internal and external faults, and the maximum coefficient algorithm is the most effective in detecting the fault. This study will be useful in differential protection for power transformers.

Detection of internal and external faults of single-phase induction motor using current signature

<span>The main aim of this work is to analyze the input current waveform for a single-phase induction capacitor-run motor (SIMCR) to detect the faults. Internal and external faults were applied to the SIMCR and the current was measured. An armature (broken rotor bar) and bearing faults were applied to the SIMCR. A microcontroller was used to record the motor current signal and MATLAB software was used to analyze it with the different types of fault with varying load operations. Various values of the running capacitor were used to investigate the effect of these values on the wave-current shape. Total harmonic distortion (THD) for the voltage and current was measured. A deep demonstration of the experimental results was also provided for a better understanding of the mechanisms of bearing and armature faults (broken rotor bars) and the vibration was recorded. Spectral and power analyses revealed the difference in total harmonic distortion. The proposed method in this paper can be used in various industrial applications and this technique is quite cheap and helps most of the researchers and very effectual.</span>

Differential positive sequence power angle-based microgrid feeder protection

Integration of distribution generation (DG) makes the growth of the microgrid protection scheme very challenging issues. Researchers from all over the world continuously are doing hard work for developing the microgrid protection schemes. A differential positive sequence power angle (DPSPA) based microgrid protection scheme is proposed in this paper using positive sequence (PS) components of voltages and currents. The DPSPA for the feeder is calculated considering both ends of voltage and current signal information, when it is more than threshold, internal fault is reported otherwise, it is an external fault. Taking into consideration the varying operational modes of the microgrid, variations in DG penetration, and variations in fault variables namely fault types, and fault locations, the proposed protection scheme is verified on a modified IEEE-13 bus feeder. Moreover, to test the robustness and efficacy of the suggested scheme, various non-faulty events including induction motor starting, non-linear loading, load switching, capacitor switching, and section cutoff have been conducted. The proposed scheme is also verified for external faults and it is found that it continues to be stable for the external faults. The findings exhibit this proposed scheme, which is based on DPSPA, can successfully protect the microgrid under changing operating conditions.

The study on the Mal-operation of the transformer current differential protection during external faults cause by CT saturation

This paper analyses the unusual mal-operation of the differential protection for transformer current differential protection during the external fault. The mal-operation reason is researched in detail, based on the mathematical analysis, the simulation, and the field recorded fault data analysis. It is disclosed that the CT saturation leads to the maloperation. Based on this, this paper analyses the improvement for the CT saturation identification method, and discusses the CT selection principles. This paper is aimed at attracting the attention on the problem of the CT saturation and proposing the reference of the analysis method the countermeasure for this problem.

A Wavelet Based Differential Algorithm for Busbar Protection

Busbar protection is an essential component in power system design, protecting the most important system node for network stability and security. When faults occurs on busbar itself, it takes much time to isolate the bus from source which may cause much damage in the bus system. Faults in power system are classified as internal and external faults. Faults within the zone are termed as internal faults whereas, the faults outside the Zone are called as external faults. Ideally, a relay looking after the protection of a zone should operate only for internal faults. It should restrain from operating for external faults or through faults. In this paper the busbar protection using differential protection scheme has been investigated for internal and external faults. An algorithm has been developed to improve the selectivity of the relay and the same has been tested in IEEE9 bus system for internal and external faults. Separation of De-noised signal from fault signal is made using wavelet transform so that the nature of fault occurs on the system can be identified. In this study Daubechies 4 at level 3 is used to separate original signal and de-noised signal. The entire simulation has been done using MATLAB R2017a.