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Figure from:POWER SWING PROTECTION OF SERIES COMPENSATED TRANSMISSION LINE WITH NOVEL FAULT DETECTION TECHNIQUE

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A test system shown in Fig. | is considered [1]. Both Line- 1 and Line-2 are 40% compensated and the capacitors are placed [3] .The system details are provided in Appendix A. The system with the distributed line model is simulated using SIMULINK/PSCAD. The traditional fault detection techniques, like the sample-to-sample or cycle-to-cycle comparison of current (or voltage) signals cannot be reliable during the power swing [2].
A test system shown in Fig. | is considered [1]. Both Line- 1 and Line-2 are 40% compensated and the capacitors are placed [3] .The system details are provided in Appendix A. The system with the distributed line model is simulated using SIMULINK/PSCAD. The traditional fault detection techniques, like the sample-to-sample or cycle-to-cycle comparison of current (or voltage) signals cannot be reliable during the power swing [2].
Series compensation imposes protection problems .The use of series capacitors in transmission lines results voltage/current inversion, sub harmonic oscillations, transients, sub-synchronous oscillations [11].
Series compensation imposes protection problems .The use of series capacitors in transmission lines results voltage/current inversion, sub harmonic oscillations, transients, sub-synchronous oscillations [11].
Fig3: Voltage Waveforms during Power Swing
Fig3: Voltage Waveforms during Power Swing
A .Line-to-Ground Fault in the Series-Compensated Line Fig4 : Implementation of SMIB- Test System Using PSCAD The algorithm for is tested for different conditions including balanced and unbalanced faults etc. Using SIMULINK/PSCAD with distributed parameter line model data was generated. The data-sampling rate was maintained at 4 kHz for the 50-Hz power system. Algorithm is tested for a line to ground fault of ag -type with a fault resistance of 0.1 ohm initiated at 0.34 sec for 0.04 sec duration at a distance 240KM from bus!1.
A .Line-to-Ground Fault in the Series-Compensated Line Fig4 : Implementation of SMIB- Test System Using PSCAD The algorithm for is tested for different conditions including balanced and unbalanced faults etc. Using SIMULINK/PSCAD with distributed parameter line model data was generated. The data-sampling rate was maintained at 4 kHz for the 50-Hz power system. Algorithm is tested for a line to ground fault of ag -type with a fault resistance of 0.1 ohm initiated at 0.34 sec for 0.04 sec duration at a distance 240KM from bus!1.
The fault is detected after 4.75 ms of fault initiation. At the time of fault inception the fault index g glows enormously high. Output shows | after inception of the fault and 0 before inception. Initially phase-a of Line-1 is out of service following an ag- fault occurring during normal operation. It introduced swing into the system. A line-to-ground fault of bg-type with a fault resistance 100 Ohm is created at 0.2s at a distance of 160 km from the relay location toward bus N during swing. For this case, and the fault detection is possible after 0.6-ms fault inception.
The fault is detected after 4.75 ms of fault initiation. At the time of fault inception the fault index g glows enormously high. Output shows | after inception of the fault and 0 before inception. Initially phase-a of Line-1 is out of service following an ag- fault occurring during normal operation. It introduced swing into the system. A line-to-ground fault of bg-type with a fault resistance 100 Ohm is created at 0.2s at a distance of 160 km from the relay location toward bus N during swing. For this case, and the fault detection is possible after 0.6-ms fault inception.
From the variation of g itself, we can segregate an LG fault from a non-LG fault. The variation of g in case of a LG fault is very less with compared to other case. The Classification or type of detected fault can be detected by tracking the absolute variation of fault index g and the variation of variation of fault index g (fine tuning of g).
From the variation of g itself, we can segregate an LG fault from a non-LG fault. The variation of g in case of a LG fault is very less with compared to other case. The Classification or type of detected fault can be detected by tracking the absolute variation of fault index g and the variation of variation of fault index g (fine tuning of g).
The variation of (Variatiion of) g gradually diminishes to zero towards the end of fault duration and this tendency of variation declining towards zero rapidly increases w.rt if any additional Line or ground involved in the fault. IDENTIFIATION OF GROUND FAULTs : The trick of the detection is the nature of the (variation of(Variation of g)) -t plot. The variation of (Variation of) g gradually diminishes to zero towards the end of fault duration and this tendency of variation declining towards zero rapidly increases, if any additional Line or ground involved in the fault.
The variation of (Variatiion of) g gradually diminishes to zero towards the end of fault duration and this tendency of variation declining towards zero rapidly increases w.rt if any additional Line or ground involved in the fault. IDENTIFIATION OF GROUND FAULTs : The trick of the detection is the nature of the (variation of(Variation of g)) -t plot. The variation of (Variation of) g gradually diminishes to zero towards the end of fault duration and this tendency of variation declining towards zero rapidly increases, if any additional Line or ground involved in the fault.
Figl4:Current and Voltage Waveforms of relay bus during the power swing A three-phase fault 1s created in line 5—7 at 0.1 s. The fault is cleared at 0.3 s by opening breaker B3 and B4. The removal of the line causes a swing condition. Different faults are simulated on line 7—8 to test the algorithm.
Figl4:Current and Voltage Waveforms of relay bus during the power swing A three-phase fault 1s created in line 5—7 at 0.1 s. The fault is cleared at 0.3 s by opening breaker B3 and B4. The removal of the line causes a swing condition. Different faults are simulated on line 7—8 to test the algorithm.
The system details are given in Appendix B.
The system details are given in Appendix B.
VI. PREDICTION OF ZONE AND LOCATION OF THE DETECTED FAULT:
VI. PREDICTION OF ZONE AND LOCATION OF THE DETECTED FAULT:
Fig: 12: LLG fault detection -time delay percentage length Plot for the SMIB System Trick to find zone is to analysis the time delay sensed by the system to detect the fault. It is a function of fault distance. By this way we can predict the Zone of the fault.
Fig: 12: LLG fault detection -time delay percentage length Plot for the SMIB System Trick to find zone is to analysis the time delay sensed by the system to detect the fault. It is a function of fault distance. By this way we can predict the Zone of the fault.
a) [2 vs t Plot During Single Pole Tripping Condition
a) [2 vs t Plot During Single Pole Tripping Condition
An ag- fault with a fault resistance of 0.1 is created during the power swing on line 7-8 ata distance of 160 km from the relay location at 0.3 s. The index increases to a higher value at the inception of the fault. The technique is able to detect the fault within half-a-cycle of its inception. The performance of the algorithm for a double-line-to- ground fault of with a ground fault resistance of 0.1 is created on a and b-phases at 0.3 s on line 7—8 during the power swing at a distance of 160 km from the relay location. Accuracy:
An ag- fault with a fault resistance of 0.1 is created during the power swing on line 7-8 ata distance of 160 km from the relay location at 0.3 s. The index increases to a higher value at the inception of the fault. The technique is able to detect the fault within half-a-cycle of its inception. The performance of the algorithm for a double-line-to- ground fault of with a ground fault resistance of 0.1 is created on a and b-phases at 0.3 s on line 7—8 during the power swing at a distance of 160 km from the relay location. Accuracy:
Fig16: Single-Line Diagram of the Modified WSCC 9-bus System
Fig16: Single-Line Diagram of the Modified WSCC 9-bus System
In this paper a novel fault detection technique for detecting the classification and location of the fault is proposed. LLG fault is created at 240 KM distance during power swing condition. After analysing it we got below waveform.
In this paper a novel fault detection technique for detecting the classification and location of the fault is proposed. LLG fault is created at 240 KM distance during power swing condition. After analysing it we got below waveform.