Numerical analysis

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A reduction in the size of the neural network improves the performance of the same and this can be achieved by performing feature extraction using wavelet transformation of the input signal. By doing this, all of the important and relevant information present in the waveforms of the voltage and current signals can be used effectively. The fault currents and voltages have been generated from the model of Figure 3.3 after simulation using Matlab as shown in Figures 3.6 – 3.15for fault condition of L-G, L-L, L-L-G and L-L-L. Moreover, the sampling time taken for the analysis is 100us, which relates to a sampling frequency of 10 kHz.

Figure 3.6 is the waveform of the current of the single line to ground fault on phase A measured at 140km away from source A during occurrence of fault on the line. The red, blue and green curves represent fault conditions of phases A, B and C respectively. From the graph it can be seen that the fault occurred at 50ms after which the magnitude of fault current on phase A rose reasonably while the other two phases almost remained stable which is clear from the Figure 3.6.

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Fig. 3.6: Current waveform of LG Fault on phase A at a distance of 140kM from the source

Figure 3.7 is the corresponding waveform of the voltage of the single line to ground fault on phase A measured at 140km away from source A during occurrence of a transient fault on the line. As aforementioned, the red, blue and green curves represent fault conditions of phases A, B and C respectively. The fault has caused a voltage drop on phase A when the fault occurred after 50ms. The other two phases almost remained stable.

Fig. 3.7: Voltage waveform of LG Fault on phase A at a distance of 140kM from the source

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Fig. 3.8: Current waveform of LL-G Fault on phase A & B at a distance of 140km from the source

In Figure 3.8, the red, blue and green curves represent fault conditions of phases A, B and C respectively. Figure 3.8 is the waveform of the current of the double line to ground fault on phase A and B measured at 140km away from source A during occurrence of a transient fault on the line. From the graph it can be seen that the fault occurred at 50ms after which the magnitude of fault current on phases A and B rose reasonably high (enough to cause flow disruption) while the other phase almost remained stable which is clear from the Figure 3.8.

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Fig. 3.9: Voltage waveform of LL-G Fault on phase A & B at a distance of 140km from the source

Figure 3.9 is the corresponding waveform of the voltage of the double line to ground fault on phase A measured at 140km away from source A during occurrence of a transient fault on the line. The red, blue and green curves represent fault conditions of phases A, B and C respectively. The fault has caused voltage drops on phases A and B after the fault occurred at 50ms. Phase C almost remained stable.

Figure 3.10 shows the current waveform of the double line (without ground) fault on phase A and B measured at 140km away from source A during occurrence of a transient fault on the line. The red, blue and green curves represent fault conditions of phases A, B and C respectively. From the graph it can be seen that the fault occurred at 50ms after which the

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magnitude of fault current on phases A and B increased leading to instability in the system.

The phase C almost remained stable as shown in the Figure 3.10.

Fig. 3.10: Current waveform of LL Fault on phases A & B at a distance of 140km from the source

Figure 3.11 shows the corresponding voltage waveform of the double line fault on phase A and B measured at 140km away from source A during occurrence of a transient fault on the line. As aforementioned, the red, blue and green curves represent fault conditions of phases A, B and C respectively. The fault has caused significant voltage drops on phases A and Bwhen the fault occurred at 50ms. Phase C almost remained stable.

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Fig. 3.11: Voltage waveform of LL Fault on phase A & B at a distance of 140km from the source

In Figure 3.12, the red, blue and green curves represent fault conditions of phases A, B and C respectively. Figure 3.12 depicts the current waveforms of three phase fault (with or without ground) on phase A, B and C measured at 140km away from source A during occurrence of a fault on the line. From the graph it can be seen that the fault occurred at 50ms after which the magnitude of fault current on the three phases rose reasonably high, enough to cause flow disruption.

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Fig. 3.12: Current waveform of LLL Fault on all the phases at a distance of 140km from the source

Fig. 3.13: Voltage waveform of LLL Fault on all the phases at a distance of 140km from the source

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Figure 3.13 depicts the corresponding voltage waveforms of three phase fault (with or without ground) measured at 140km away from source A during occurrence of a transient fault on the line. As said above, the red, blue and green curves represent fault conditions of phases A, B and C respectively. The fault has caused simultaneousvoltage drops on phases A, B and C after the fault occurred at 50ms.

Fig. 3.14: Current waveform of No Fault condition on all the phases at a distance of 140km from the source

In Figure 3.14, the red, green and blue curves represent fault conditions of phases A, B and C respectively. Figure 3.14 depicts the current waveforms of No fault on phase A, B and C captured at 140km away from source A. From the graph it can be seen that the magnitude of currents on the three phases remained unchanged.

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Fig. 3.15: Voltage waveform of No Fault condition on all the phases at a distance of 140km from the source

Figure 3.15 depicts the corresponding voltage waveforms of No fault condition measured at 140km away from source A at no fault condition. As aforementioned, the red, green and blue curves represent fault conditions of phases A, B and C respectively. The voltage of the three phases (phases A, B and C) has remained unchanged.

These results for each simulation are captured and stored in Matlab with the help of the „„To Workspace blocks‟‟ tool as shown in Figure 3.5. Then to perform wavelet decomposition, these captured results or data are imported into the Matlab wavelet toolbox where they are decomposed into detail coefficients and coarse approximations using the multi-resolution analysis tool as presented.

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