Neural Network Based Transformer Differential Protection
NEURAL NETWORK BASED TRANSFORMER DIFFERENTIAL PROTECTION
Abstract: The role of a differential relay for power transformer is to trip during fault condition and blocks the tripping during inrush, overexcitation, CT saturation conditions of the power transformer. Conventional harmonic restrained relay may mal operate due to the presence of the second and fifth harmonic during internal faults because of non-linear loads and capacitance in the transmission lines. This project presents a technique for classifying transient phenomena in power transformers for differential protection. Discrimination among different operating conditions (i.e., normal, inrush, overexcitation, CT saturation) and internal faults of the power transformer is achieved by differential relay using the algorithm based on wavelet transform with Neural Network. The wavelet transform is a powerful tool in the analysis of the power transformer transient phenomena because of its ability to extract information from the transient signals simultaneously in both the time and frequency domain. Neural network is used because of its self-learning and highly nonlinear mapping capability. Keywords – Wavelet Transform, back propagation neural netwok, transformer differential protection. I.Introduction Differential protection is the primary protection for larger power transformers. It contains the operation by all types of internal faults, and blocks the operations of the transformer by inrush, overexcitation and external faults. Since a magnetizing inrush current generally contains a large second harmonic component in comparison to an internal fault, conventional transformer protection systems are designed to restrain during inrush transient phenomenon by sensing this large second harmonic. However, the second harmonic component may also be generated during internal faults in the power transformer, due to CT saturation or the presence of a shunt capacitor or the distributive capacitance in a long EHV
Abstract: The role of a differential relay for power transformer is to trip during fault condition and blocks the tripping during inrush, overexcitation, CT saturation conditions of the power transformer. Conventional harmonic restrained relay may mal operate due to the presence of the second and fifth harmonic during internal faults because of non-linear loads and capacitance in the transmission lines. This project presents a technique for classifying transient phenomena in power transformers for differential protection. Discrimination among different operating conditions (i.e., normal, inrush, overexcitation, CT saturation) and internal faults of the power transformer is achieved by differential relay using the algorithm based on wavelet transform with Neural Network. The wavelet transform is a powerful tool in the analysis of the power transformer transient phenomena because of its ability to extract information from the transient signals simultaneously in both the time and frequency domain. Neural network is used because of its self-learning and highly nonlinear mapping capability. Keywords – Wavelet Transform, back propagation neural netwok, transformer differential protection. I.Introduction Differential protection is the primary protection for larger power transformers. It contains the operation by all types of internal faults, and blocks the operations of the transformer by inrush, overexcitation and external faults. Since a magnetizing inrush current generally contains a large second harmonic component in comparison to an internal fault, conventional transformer protection systems are designed to restrain during inrush transient phenomenon by sensing this large second harmonic. However, the second harmonic component may also be generated during internal faults in the power transformer, due to CT saturation or the presence of a shunt capacitor or the distributive capacitance in a long EHV
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