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1 Supervisor: Dr. A.M. Sharaf, SMIEEE Ph.D. Candidate: S.M.A. Saleem Department of Electrical and Computer Engineering University of New Brunswick SMART.

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Presentation on theme: "1 Supervisor: Dr. A.M. Sharaf, SMIEEE Ph.D. Candidate: S.M.A. Saleem Department of Electrical and Computer Engineering University of New Brunswick SMART."— Presentation transcript:

1 1 Supervisor: Dr. A.M. Sharaf, SMIEEE Ph.D. Candidate: S.M.A. Saleem Department of Electrical and Computer Engineering University of New Brunswick SMART SOFT-ENGINEERING BASED DIAGNOSTIC, RELAYING AND PROTECTION SCHEMES FOR ELECTRICAL POWER SYSTEMS.

2 2 Presentation Outline Research Objectives Research Objectives Research Focus Research Focus Background Review Background Review Existing Methods Existing Methods Expected Results Expected Results Research Implications Research Implications Research Plan Research Plan Sample Case Sample Case Sample Results Sample Results Publications / References Publications / References

3 3 Research Objectives Develop new dynamic temporal based relaying algorithms using combination of Time frequency Analysis, Multi-resolution Analysis and Artificial Intelligence tools, such as ANN, Expert systems, Fuzzy logic, Genetic Algorithms and statistical Abduction rules. Develop new dynamic temporal based relaying algorithms using combination of Time frequency Analysis, Multi-resolution Analysis and Artificial Intelligence tools, such as ANN, Expert systems, Fuzzy logic, Genetic Algorithms and statistical Abduction rules.

4 4 Research Focus Conventional power system relaying is mostly based on quasi-steady-state vector/phasor methods which are both slow and inaccurate. Conventional power system relaying is mostly based on quasi-steady-state vector/phasor methods which are both slow and inaccurate. The inaccuracy is most evident in case of MOV protected Series Compensated Transmission Lines. The inaccuracy is most evident in case of MOV protected Series Compensated Transmission Lines. New computer models are now able to model the full time and frequency response of the power system. New computer models are now able to model the full time and frequency response of the power system. Latest developments in Computing power has broken new barriers in Signal Processing and Artificial Intelligence. Latest developments in Computing power has broken new barriers in Signal Processing and Artificial Intelligence.

5 5 Background Review Transient stability of a power system is dependant on the allowable tolerable fault clearing time. Transient stability of a power system is dependant on the allowable tolerable fault clearing time. MOV device operation in Series Compensated lines introduces transients in the transmission system as well as key changes in the Thevenin impedance of the transmission lines. This in turn causes the classical distance based transmission relays to mal-operate. MOV device operation in Series Compensated lines introduces transients in the transmission system as well as key changes in the Thevenin impedance of the transmission lines. This in turn causes the classical distance based transmission relays to mal-operate. Protection of a series compensated transmission line can be best accomplished by a special fast relaying system. Protection of a series compensated transmission line can be best accomplished by a special fast relaying system.

6 6 Existing Methods LFDC relay has serious shortcomings such as the fault detection is difficult for faults occurring near the voltage waveform zero crossing. In this case backup protection is expected to be added. LFDC relay has serious shortcomings such as the fault detection is difficult for faults occurring near the voltage waveform zero crossing. In this case backup protection is expected to be added. Backup type relays owing to their extended protection Operating-Zone isolate a large section of the connected AC power system than just the small limited fault area. Backup type relays owing to their extended protection Operating-Zone isolate a large section of the connected AC power system than just the small limited fault area.

7 7 Existing Methods..cont. Recent research publications in the area of UHS relaying have tried to address the problem mentioned above, but have limitations, applicable to teed power systems only. Recent research publications in the area of UHS relaying have tried to address the problem mentioned above, but have limitations, applicable to teed power systems only. Similarly, another researcher has presented a novel approach to UHS relaying based on directional line protection using travelling waves, it is not able to provide ultimate robust detection for the case of fault inception angles approaching zero. Similarly, another researcher has presented a novel approach to UHS relaying based on directional line protection using travelling waves, it is not able to provide ultimate robust detection for the case of fault inception angles approaching zero.

8 8 Expected Results Improve the existing UHS relaying using latest transmission DSP methods and abduction rules via key proven nonlinear transformations. Improve the existing UHS relaying using latest transmission DSP methods and abduction rules via key proven nonlinear transformations. Develop special interface protocols and anomaly diagnostics and detection rule-matrix. Develop special interface protocols and anomaly diagnostics and detection rule-matrix. Develop a global multilevel UHS relay prototype. Develop a global multilevel UHS relay prototype. Laboratory Test and Validate the Novel Proposed Relay. Laboratory Test and Validate the Novel Proposed Relay.

9 9 Expected Results Figure 1. General Structure of the Proposed Novel, multilevel High Speed DSP Relay. Figure 1. General Structure of the Proposed Novel, multilevel High Speed DSP Relay.

10 10 Research Implications Reduce Electric Brownouts and Grid Utility system rotating Blackouts. Reduce Electric Brownouts and Grid Utility system rotating Blackouts. Enhance power system security, functionality and reliability. Enhance power system security, functionality and reliability. Reduce severe damage to major power components due to over voltages and over currents. Reduce severe damage to major power components due to over voltages and over currents. Enhance Power system Interconnection security. Enhance Power system Interconnection security. Reduce millions of dollars in economic and social impact losses due to electricity Blackouts. Reduce millions of dollars in economic and social impact losses due to electricity Blackouts.

11 11 Research Plan Explore novel Transformations [T], anomaly diagnostics and detection rule-matrix to accurately detect/improve Power System Transmission line faults. Explore novel Transformations [T], anomaly diagnostics and detection rule-matrix to accurately detect/improve Power System Transmission line faults. Explore novel mathematical techniques, DSP, Time frequency Analysis to detect faults under noise/disturbances. Explore novel mathematical techniques, DSP, Time frequency Analysis to detect faults under noise/disturbances. Explore novel feature vectors XF to classify Power System faults. Explore novel feature vectors XF to classify Power System faults.

12 12 Sample Case Sample results are shown for a mesh system consisting of a 750kV, 250km un-transposed transmission line with a local source of 10GVA and a remote source of 6GVA. The one-line diagram of the transmission line is shown in Figure 2. Sample results are shown for a mesh system consisting of a 750kV, 250km un-transposed transmission line with a local source of 10GVA and a remote source of 6GVA. The one-line diagram of the transmission line is shown in Figure 2. The fault is a linear, single-line-to-ground fault at phase B. The ground resistance Rf = 3 ohms. The fault inception time is t = 1.0285 s. The fault is a linear, single-line-to-ground fault at phase B. The ground resistance Rf = 3 ohms. The fault inception time is t = 1.0285 s. The time domain voltage and current signals measured by the PTs and CTs located near the local AC source for a linear fault at 20km km is shown in Figure 3. The fault distance is measured from the local source G1. The time domain voltage and current signals measured by the PTs and CTs located near the local AC source for a linear fault at 20km km is shown in Figure 3. The fault distance is measured from the local source G1.

13 13 Sample Case Figure 2. One line Diagram of the sample study system Figure 2. One line Diagram of the sample study system

14 14 Sample Results Figure 3. Fault voltages and currents for a SLG linear fault on phase B at 20km from R1. Figure 3. Fault voltages and currents for a SLG linear fault on phase B at 20km from R1.

15 15 Sample Results..cont. Figure 4. Modal Transformed voltages at sending end S1, for a SLG linear fault on phase B at 20km from R1. Figure 4. Modal Transformed voltages at sending end S1, for a SLG linear fault on phase B at 20km from R1.

16 16 Sample Results..cont. Figure 5. Modal Transformed currents at sending end S1, for a SLG linear fault on phase B at 20km from R1. Figure 5. Modal Transformed currents at sending end S1, for a SLG linear fault on phase B at 20km from R1.

17 17 Sample Results..cont. Figure 6. Modal Transformed voltages at sending end S1, for a SLG linear fault on phase B at 200km from R1. Figure 6. Modal Transformed voltages at sending end S1, for a SLG linear fault on phase B at 200km from R1.

18 18 Sample Results..cont. Figure 7. Modal Transformed currents at sending end S1, for a SLG linear fault on phase B at 200km from R1. Figure 7. Modal Transformed currents at sending end S1, for a SLG linear fault on phase B at 200km from R1.

19 19 Sample Results..cont. Figure 8. Wavelet transform of aerial mode ‘a’ voltage at sending end S1, for a SLG linear fault on phase B at 20km from R1. Figure 8. Wavelet transform of aerial mode ‘a’ voltage at sending end S1, for a SLG linear fault on phase B at 20km from R1.

20 20 Sample Results..cont. Figure 9. Wavelet transform of aerial mode 'β' voltage at sending end S1, for SLG linear fault on phase B at 20km from R1. Figure 9. Wavelet transform of aerial mode 'β' voltage at sending end S1, for SLG linear fault on phase B at 20km from R1.

21 21 Sample Results..cont. Figure 10. Wavelet transform of ground mode voltage at sending end S1, for SLG linear fault on phase B at 20km from R1. Figure 10. Wavelet transform of ground mode voltage at sending end S1, for SLG linear fault on phase B at 20km from R1.

22 22 Sample Results..cont. Figure 11. Wavelet transform of aerial mode 'α' voltage at sending end S1, for a SLG linear fault on phase B at 200km from R1. Figure 11. Wavelet transform of aerial mode 'α' voltage at sending end S1, for a SLG linear fault on phase B at 200km from R1.

23 23 Sample Results..cont. Figure 12. Wavelet transform of aerial mode 'β' voltage at sending end S1, for a SLG linear fault on phase B at 200km from R1. Figure 12. Wavelet transform of aerial mode 'β' voltage at sending end S1, for a SLG linear fault on phase B at 200km from R1.

24 24 Sample Results..cont. Figure 13. Wavelet transform of ground mode voltage at sending end S1, for a SLG linear fault on phase B at 200km from R1. Figure 13. Wavelet transform of ground mode voltage at sending end S1, for a SLG linear fault on phase B at 200km from R1.

25 25 Publications [1]A.M.Sharaf and S.M.A.Saleem, “UHS Transient Protection of Series Compensated Lines Using Wavelet Transforms”, in Proc. CCECE-CCGEI 2006, Ottawa, May 7-10, 2006. (submitted) [1]A.M.Sharaf and S.M.A.Saleem, “UHS Transient Protection of Series Compensated Lines Using Wavelet Transforms”, in Proc. CCECE-CCGEI 2006, Ottawa, May 7-10, 2006. (submitted) [2]A.M.Sharaf and S.M.A.Saleem, “Application of Neural Networks and Wavelet Transforms in High Impedance Fault Detection in Electrical Systems”, in Proc. MEPCON-2005, Suez Canal University, Port Said, Egypt, Dec. 13-15, 2005. (accepted) [2]A.M.Sharaf and S.M.A.Saleem, “Application of Neural Networks and Wavelet Transforms in High Impedance Fault Detection in Electrical Systems”, in Proc. MEPCON-2005, Suez Canal University, Port Said, Egypt, Dec. 13-15, 2005. (accepted) [3]A.M.Sharaf and S.M.A.Saleem, “High impedance fault detection using a neural network based relaying scheme”, in Proc. MEPCON-2003, Shebin El-Kom, Egypt, Dec. 18-25, 2003. [3]A.M.Sharaf and S.M.A.Saleem, “High impedance fault detection using a neural network based relaying scheme”, in Proc. MEPCON-2003, Shebin El-Kom, Egypt, Dec. 18-25, 2003.

26 26 References [4]A.M.Sharaf and S.I.Abu-Azab, “A smart relaying scheme for high impedance faults in distribution and utilization networks”, in Proc. of Canadian Conference on Electrical and Computer Engineering, Halifax, NS Canada, March 2000. [4]A.M.Sharaf and S.I.Abu-Azab, “A smart relaying scheme for high impedance faults in distribution and utilization networks”, in Proc. of Canadian Conference on Electrical and Computer Engineering, Halifax, NS Canada, March 2000. [5]A.M.Sharaf, L.A.Snider and K.Debnath, “Harmonic based detection of HIF - Arc faults in distribution networks using neural networks”, in Proc. IASTED Conf., Pittsburg, PA, 1993. [5]A.M.Sharaf, L.A.Snider and K.Debnath, “Harmonic based detection of HIF - Arc faults in distribution networks using neural networks”, in Proc. IASTED Conf., Pittsburg, PA, 1993. [6]A.M.Sharaf, L.A.Snider and K.Debnath, "A neuro-fuzzy based relay for global ground fault detection in radial electrical distribution networks", in Proc.International Conference of Electrical Engineering, Tehran, May 1993. [6]A.M.Sharaf, L.A.Snider and K.Debnath, "A neuro-fuzzy based relay for global ground fault detection in radial electrical distribution networks", in Proc.International Conference of Electrical Engineering, Tehran, May 1993.

27 27 References [7]A.M.Sharaf, L.A.Snider and K.Debnath, "A neural network based back error propagation relay algorithm for distribution system HIF - Arc fault detection", in Proc. APSCOM-93, Hong Kong, Dec. 1993. [7]A.M.Sharaf, L.A.Snider and K.Debnath, "A neural network based back error propagation relay algorithm for distribution system HIF - Arc fault detection", in Proc. APSCOM-93, Hong Kong, Dec. 1993. [8]A.M.Sharaf, L.A. Snider and K.Debnath, "Harmonic based detection of HIF - Arc faults in distribution networks using artificial neural networks", in Proc. IASTED, Pittsburgh, PA, May 10-12, 1993. [8]A.M.Sharaf, L.A. Snider and K.Debnath, "Harmonic based detection of HIF - Arc faults in distribution networks using artificial neural networks", in Proc. IASTED, Pittsburgh, PA, May 10-12, 1993. [9]A.M.Sharaf, L.A.Snider and K.Debnath, "Residual third harmonic detection of HIF - Arc faults in distribution systems using perception neural networks", in Proc. ISEDEM 1993, Singapore, Oct. 1993. [9]A.M.Sharaf, L.A.Snider and K.Debnath, "Residual third harmonic detection of HIF - Arc faults in distribution systems using perception neural networks", in Proc. ISEDEM 1993, Singapore, Oct. 1993. [10]“Type LFDC Digital Directional Comparison Protection Relay”, Areva Transmission and Distribution Ltd. [10]“Type LFDC Digital Directional Comparison Protection Relay”, Areva Transmission and Distribution Ltd.

28 28 References [11]C.Y.Evrenosoglu and A.Abur, “Travelling Wave Based Fault Location for Teed Circuits”, IEEE Trans. PWD, pp. 1115- 1121, vol. 20, no. 2, April 2005. [11]C.Y.Evrenosoglu and A.Abur, “Travelling Wave Based Fault Location for Teed Circuits”, IEEE Trans. PWD, pp. 1115- 1121, vol. 20, no. 2, April 2005. [12]X.Dong, Y.Ge and J.He, “Surge Impedance Relay”, IEEE Trans. PWD, pp. 1247- 1256, vol. 20, no. 2, April 2005. [12]X.Dong, Y.Ge and J.He, “Surge Impedance Relay”, IEEE Trans. PWD, pp. 1247- 1256, vol. 20, no. 2, April 2005. [13]G.Phadke, J.S.Thorpe, “Computer Relaying for Power Systems”, John Wiley and Sons. [13]G.Phadke, J.S.Thorpe, “Computer Relaying for Power Systems”, John Wiley and Sons. [14]J.G.Proakis, D.G.Manolakis, “Digital Signal Processing, 3rd Edition”, Prentice Hall. [14]J.G.Proakis, D.G.Manolakis, “Digital Signal Processing, 3rd Edition”, Prentice Hall.

29 29 Thank you Questions Please


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