Smart Technology Based Empirical Mode Decomposition (EMD) Approach for Autonomous Transmission Line Fault Detection Protection

Authors

  • Nasser Ali Hasson Al-Zubaydi Al-Furat Al-Awsat Technical University image/svg+xml

DOI:

https://doi.org/10.4108/ew.v9i38.733

Keywords:

Smart House, Malfunction, Transmission Line, DWT, EMD, Autonomous System

Abstract

Many novel technologies of property energy and cell, solar power, batteries, and high-efficient combustion are widely investigated to conserve energy and reduce emissions. Transmission lines (TLs) play a serious role in transmitting generated electricity to different distribution units in facility engineering. The transmission lines function as a link between shoppers and a Power Station. Faults usually occur within the transmission when positioned in an open field. Quick identification and sick line faults square measures required for the conventional operation of the plant. A way like distinct moving ridge rework (DWT) and (EMD) is used to locate and identify faults to resolve this disruption. DWT is used to break down fault transients, as a result of which the info can be collected at the same time in each time and frequency domain. EMD decomposes the TLs voltage into Intrinsic Mode operation (IMFs). Four varieties of fault signals are square measurements produced by the grid-connected facility. Line faults square measure induced MATLAB/Simulink mistreatment.

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References

Ahmed R. AdlyMahmoud A. ElsaddA novel wavelet packet transform-based fault identification procedures in HV transmission line based on current signals International Journal of Applied Power Engineering, Vol.8, No.1, April 2019. DOI: https://doi.org/10.11591/ijape.v8.i1.pp11-21

Ahmed R. Adlya, Shady H. E. Abdel Aleemb, Mostafa A. Algabalawyc, F. Juradod, Ziad M. Alie,” A novel protection scheme for multi-terminal transmission lines based on wavelet transform Electric Power Systems Research” 183 (2020) 106286. DOI: https://doi.org/10.1016/j.epsr.2020.106286

Q. Jiang, X. Li, B. Wang, and H. Wang, “PMU-Based Fault Location Using Voltage Measurements in Large Transmission Networks,” IEEE Trans. Power Del., vol. 27, no. 3, pp. 1644–1652, 2012. DOI: https://doi.org/10.1109/TPWRD.2012.2199525

Sunil Singh D. N. Vishwakarma “Intelligent Techniques for Fault Diagnosis in Transmission lines -An Overview2015” International Conference on Recent Developments in Control, Automation and Power Engineering (RDCAPE) DOI: https://doi.org/10.1109/RDCAPE.2015.7281410

M. Singh, B. K. Panigrahi and R. P. Maheshwari, "Transmission line fault detection and classification," 2011 International Conference on Emerging Trends in Electrical and Computer Technology, 2011, pp. 15-22. DOI: https://doi.org/10.1109/ICETECT.2011.5760084

B.Ravindranath Reddy, M. Vijaya Kumar, M.Suryakalavathi, Ch. Prasanth Babu “Fault detection, classification and location on transmission lines using wavelet transform “2009 Annual Report Conference on Electrical Insulation and Dielectric Phenomena.

Mohammad Amin Jarrahi, Haidar Samet and Ali Sahebi “An EMD Based Fault Type Identification Scheme in Transmission Line “2016 24th Iranian Conference on Electrical Engineering (ICEE). DOI: https://doi.org/10.1109/IranianCEE.2016.7585558

M. Gowrishankar, 1 2P. Nagaveni and 3P. Balakrishnan “Transmission Line Fault Detection and Classification Using Discrete Wavelet Transform and Artificial Neural Network “Middle-East Journal of Scientific Research 24 (4): 1112-1121, 2016.

Bilal Masood, Umar Saleem, Nadeem Anjum “Faults Detection and Diagnosis of Transmission Lines using wavelet Transformed based Technique “2017 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT). DOI: https://doi.org/10.1109/AEECT.2017.8257776

M. J. Reddy and D. K. Mohanta, “A wavelet-fuzzy combined approach for classification and location of transmission line faults,” Electrical Power and Energy Systems, Elsevier, vol. 29, pp. 669–678,2007. DOI: https://doi.org/10.1016/j.ijepes.2007.05.001

P. S. Bhowmik, P. Purkait, and K. Bhattacharya, “Electrical Power and Energy Systems A novel wavelet transform aided neural network-based transmission line fault analysis method,” Electrical Power and Energy Systems, Elsevier, vol. 31, pp. 213–219, 2009. DOI: https://doi.org/10.1016/j.ijepes.2009.01.005

S. Ekici, “Energy and entropy-based feature extraction for locating fault on transmission lines by using neural network and wavelet packet decomposition,” Expert Systems with Applications, Elsevier, vol. 34, pp. 2937–2944, 2008. DOI: https://doi.org/10.1016/j.eswa.2007.05.011

E. Koley, K. Verma, and S. Ghosh, “An improved fault detection classification and location scheme based on wavelet transform and artificial neural network for six phase transmission line using single end data only,” Springer plus, vol. 4, no. 1, p. 551, 2015. DOI: https://doi.org/10.1186/s40064-015-1342-7

Balvinder Singh Om Prakash Mahela Tanuj Manglani “Detection and Classification of Transmission Line Faults Using Empirical Mode Decomposition and Rule Based Decision Tree-Based Algorithm” 978-1-5386-7339-3/18/$31.00 ©2018 IEEE.

M. Jamil, S. K. Sharma, and R. Singh, “Fault detection and classification in an electrical power transmission system using artificial neural network,” Springer plus, vol. 4, no. 1, p. 334, 2015. DOI: https://doi.org/10.1186/s40064-015-1080-x

U. B. Parikh, B. Das, and R. Maheshwari, “Fault classification technique for series compensated transmission line using support vector machine,” Int. J. Electr. Power Energy Syst. Elsevier, vol. 32, no. 6, pp. 629–636, 2010. DOI: https://doi.org/10.1016/j.ijepes.2009.11.020

S. Ekici, “Support Vector Machines for classification and locating faults on transmission lines,” Applied Soft Computing, Elsevier, vol.12, pp. 1650–1658, 2012. DOI: https://doi.org/10.1016/j.asoc.2012.02.011

Mahanty, R.N. and P.B. Dutta Gupta, “A fuzzy logic-based fault classification approach using current samples only, Electric Power Systems Research, 2007 77: 501-507. DOI: https://doi.org/10.1016/j.epsr.2006.04.009

Das, B. and J.V. Reddy, “Fuzzy-logic based classification scheme for digital distance protection, IEEE Trans. Power Del,2008 20(2): 609-616. DOI: https://doi.org/10.1109/TPWRD.2004.834294

Ben Hessine, M., H. Jouini and S. Chebbi, “Fault detection and classification approaches using artificial neural networks, Mediterranean Electrotechnical Conference (MELECON), Beirut,2016 pp: 515-519.

Seethalakshmi, K., S.N. Singh, and S.C. Srivastava, “A classification approach using support vector machines to prevent distance relay maloperation under power swing and voltage instability,” IEEE 2014 Trans. Power Del., 27(3): 1124-1133. DOI: https://doi.org/10.1109/TPWRD.2011.2174808

Jafarian, P. and M. Sanaye-Pasand, “High- Frequency Transients-Based Protection of Multiterminal Transmission Lines Using the SVM Technique” IEEE 2013 Trans. DOI: https://doi.org/10.1109/TPWRD.2012.2215925

B. J. Mampilly and S. V. S, "Transmission Lines Fault Detection using Empirical Mode Decomposition in a Grid-Connected Power System," 2020 International Conference on Power Electronics and Renewable Energy Applications (PEREA), 2020, pp. 1-6. DOI: https://doi.org/10.1109/PEREA51218.2020.9339814

Youssef OAS “Combined fuzzy-logic wavelet-based fault classification technique for power system relaying” IEEE Trans Power Delivery 2004;19(2):582–9. DOI: https://doi.org/10.1109/TPWRD.2004.826386

Youssef OAS. “An optimized fault classification technique based on support-vector-machines “IEEE/PES Power Syst Conf Expos 2009:1–8. DOI: https://doi.org/10.1109/PSCE.2009.4839949

Sevakula RK, Verma NK. “Wavelet transforms for fault detection using SVM in power systems” IEEE Int Conf Power Electron Drives Energy Syst, Bengaluru, India; December 2012. DOI: https://doi.org/10.1109/PEDES.2012.6484324

Livani H, Evrenosoglu CY. “A fault classification method in power systems using DWT and SVM classifier” IEEE/PES Trans Distrib Conf Expo 2012:1–5. DOI: https://doi.org/10.1109/TDC.2012.6281686

Shukla S, Mishra S, Singh B.” Empirical-mode decomposition with Hilbert transform for power-quality assessment. IEEE Trans Power Delivery 2009;24:2159–65 DOI: https://doi.org/10.1109/TPWRD.2009.2028792

Manjula M, Sarma AVRS, Mishra S.” Empirical mode decomposition based probabilistic neural network for faults classification. Int Conf Power Energy Syst 2011:1–5. DOI: https://doi.org/10.1109/ICPES.2011.6156670

Manjula M, Sarma AVRS, Mishra S. Detection and classification of voltage sag causes based on empirical mode decomposition. “Annual IEEE India Conf. 2011:1–5. DOI: https://doi.org/10.1109/INDCON.2011.6139581

Martin, F., Aguado, J.A, “Wavelet-based ANN approach for Transmission line protection,” IEEE transaction on Power Delivery 18(4), 1572–1574 (2003).

Martin, F. and J.A. Aguado. Wavelet-based ANN approach for transmission line protection, IEEE Transactions on Power Delivery, 18: 1572-1574, 2003. DOI: https://doi.org/10.1109/TPWRD.2003.817523

D. Das, N. Singh, and A. Sinha, ‘A Comparison of Fourier Transform and Wavelet Transform Methods for Detection and Classification of Faults on Transmission Lines,’ 2006 IEEE Power India Conference, 2006. DOI: https://doi.org/10.1109/POWERI.2006.1632580

Sunil Singh, D. N. Vishwakarma, Amit Kumar & Shashank “To A novel methodology for fault detection, classification and location in transmission system based on DWT & ANFIS Journal of Information and Optimization Sciences Oct 16, 2017. DOI: https://doi.org/10.1080/02522667.2017.1372129

B. Prabhu Kavin, S. Ganapathy,” A New Digital Signature Algorithm for Ensuring the Data Integrity in Cloud using Elliptic Curves,” The International Arab Journal of Information Technology, vol. 18, no. 2, pp. 180-190, 2021. DOI: https://doi.org/10.34028/iajit/18/2/6

A.K. Gupta, Y. K. Chauhan, and T Maity, “Experimental investigations and comparison of various MPPT techniques for photovoltaic system,” Sādhanā, Vol. 43, no. 8, pp.1-15, 2018. DOI: https://doi.org/10.1007/s12046-018-0815-0

Nageswara Rao A, Vijaya Priya P, Kowsalya M, Gnanadass R. Wide-area monitoring for energy system: a review. International Journal of Ambient Energy. 2019 Jul 4;40(5):537-53. DOI: https://doi.org/10.1080/01430750.2017.1399458

Jain, A., & Kumar, A. Desmogging of still smoggy images using a novel channel prior. Journal of Ambient Intelligence and Humanized Computing, 12(1), 1161-1177, 2021. DOI: https://doi.org/10.1007/s12652-020-02161-1

Ghai, D., Gianey, H. K., Jain, A., & Uppal, R. S. Quantum and dual-tree complex wavelet transform-based image watermarking. International Journal of Modern Physics B, 34(04), 2050009, 2020. DOI: https://doi.org/10.1142/S0217979220500095

V. Mohan, H. Chhabra, A. Rani, and V. Singh, “Robust self-tuning fractional order PID controller dedicated to a non-linear dynamic system,” Journal of Intelligent & Fuzzy Systems, vol. 34, no. 3, pp. 1467-1478, 2018. DOI: https://doi.org/10.3233/JIFS-169442

A.K. Gupta, “Sun Irradiance Trappers for Solar PV Module to Operate on Maximum Power: An Experimental Study,” Turkish Journal of Computer and Mathematics Education, Vol. 12, no.5, pp.1112-1121, 2021. DOI: https://doi.org/10.17762/turcomat.v12i5.1759

Rao AN, Vijayapriya P. A robust neural network model for monitoring online voltage stability. International Journal of Computers and Applications. 2019 Sep 17:1-10. DOI: https://doi.org/10.1080/1206212X.2019.1666224

H. Chhabra, V. Mohan, A. Rani, and V. Singh, “Multi objective PSO tuned fractional order PID control of robotic manipulator,” in the international symposium on intelligent systems technologies and applications, 2016, pp. 567-572: Springer. DOI: https://doi.org/10.1007/978-3-319-47952-1_45

A.K. Gupta, Y.K Chauhan, and T Maity, “A new gamma scaling maximum power point tracking method for solar photovoltaic panel Feeding energy storage system,” IETE Journal of Research, vol.67, no.1, pp.1-21, 2018. DOI: https://doi.org/10.1080/03772063.2018.1530617

P. Rajesh, C. Naveen, Anantha Krishan Venkatesan, and Francis H. Shajin, “An optimization technique for battery energy storage with wind turbine generator integration in unbalanced radial distribution network”, Journal of Energy Storage, Vo. 43, pp 1-12, 2021. DOI: https://doi.org/10.1016/j.est.2021.103160

F. Arslan, B. Singh, D. K. Sharma, R. Regin, R. Steffi, and S. Suman Rajest, “Optimization Technique Approach to Resolve Food Sustainability Problems,” 2021 International Conference on Computational Intelligence and Knowledge Economy, 2021, pp. 25-30. DOI: https://doi.org/10.1109/ICCIKE51210.2021.9410735

Jain, A., Dwivedi, R. K., Alshazly, H., Kumar, A., Bourouis, S., & Kaur, M. Design and Simulation of Ring Network-on-Chip for Different Configured Nodes Computers, Materials, & Continua; Henderson Vol. 71, Iss. 2, (2022): 4085-4100. DOI: https://doi.org/10.32604/cmc.2022.023017

Kumar, A., & Jain, A. Image smog restoration using oblique gradient profile prior and energy minimization. Frontiers of Computer Science, 15(6), 1-7, 2021. DOI: https://doi.org/10.1007/s11704-020-9305-8

Anantha Krishnan. V and N. Senthil Kumar, “Real-Time Simulation Analysis of LM Algorithm-Based NN For The Control of VSC In Grid Connected PV-Diesel Microgrid Using OP4500 RT-Lab Simulator”, International Journal of Power and Energy Systems, Acta Press, Vol. 42, No. 10, pp. 1-10, 2022. DOI: https://doi.org/10.2316/J.2022.203-0419

Gupta, N., Vaisla, K. S., Jain, A., Kumar, A., & Kumar, R. Performance Analysis of AODV Routing for Wireless Sensor Network in FPGA Hardware. Computer Systems Science and Engineering, 39(2), 1-12, 2021.

Gupta, N., Jain, A., Vaisla, K. S., Kumar, A., & Kumar, R. Performance analysis of DSDV and OLSR wireless sensor network routing protocols using FPGA hardware and machine learning. Multimedia Tools and Applications, 80(14), 22301-22319, 2021. DOI: https://doi.org/10.1007/s11042-021-10820-4

Agrawal, N., Jain, A., & Agarwal, A. Simulation of Network on Chip for 3D Router Architecture. International Journal of Recent Technology and Engineering, 8, 58-62, 2019.

Sharma, S. K., Jain, A., Gupta, K., Prasad, D., & Singh, V. An internal schematic view and simulation of major diagonal mesh network-on-chip. Journal of Computational and Theoretical Nanoscience, 16(10), 4412-4417, 2019. DOI: https://doi.org/10.1166/jctn.2019.8534

Misra, N. R., Kumar, S., & Jain, A. A Review on E-waste: Fostering the Need for Green Electronics. In 2021 International Conference on Computing, Communication, and Intelligent Systems, (pp.1032-1036). IEEE, 2021. DOI: https://doi.org/10.1109/ICCCIS51004.2021.9397191

Kumar, S., Jain, A., Kumar Agarwal, A., Rani, S., & Ghimire, A. Object-Based Image Retrieval Using the U-Net-Based Neural Network. Computational Intelligence and Neuroscience, 2021. DOI: https://doi.org/10.1155/2021/4395646

G. A. Ogunmola, B. Singh, D. K. Sharma, R. Regin, S. S. Rajest and N. Singh, “Involvement of Distance Measure in Assessing and Resolving Efficiency Environmental Obstacles,” 2021 International Conference on Computational Intelligence and Knowledge Economy, 2021, pp. 13-18. DOI: https://doi.org/10.1109/ICCIKE51210.2021.9410765

D. Kumar, D.Mehrotra, and R. Bansal, “Metaheuristic Policies for Discovery Task Programming Matters in Cloud Computing.” Proceedings of the 4th International Conference on Computing Communication and Automation (ICCCA) 2018, pp. 1-5, 2018. DOI: https://doi.org/10.1109/CCAA.2018.8777579

Jain, A., Gahlot, A. K., Dwivedi, R., Kumar, A., & Sharma, S. K. Fat Tree NoC Design and Synthesis. In Intelligent Communication, Control and Devices (pp. 1749-1756). Springer, Singapore, 2018. DOI: https://doi.org/10.1007/978-981-10-5903-2_180

Jain, A., Dwivedi, R., Kumar, A., & Sharma, S. Scalable design and synthesis of 3D mesh network on chip. In Proceeding of International Conference on Intelligent Communication, Control and Devices (pp. 661-666). Springer, Singapore, 2017. DOI: https://doi.org/10.1007/978-981-10-1708-7_75

D. K. Sharma, B. Singh, M. Raja, R. Regin, and S. S. Rajest, “An Efficient Python Approach for Simulation of Poisson Distribution,” 2021 7th International Conference on Advanced Computing and Communication Systems, 2021, pp. 2011-2014. DOI: https://doi.org/10.1109/ICACCS51430.2021.9441895

D. Kumar, S. Kumar, and R. Bansal. “Multi-objective multi-join query optimisation using modified grey wolf optimisation.” International Journal of Advanced Intelligence Paradigms, vol.17, no.1-2, pp. 67-79, 2020. DOI: https://doi.org/10.1504/IJAIP.2020.108760

D. K. Sharma, B. Singh, E. Herman, R. Regine, S. S. Rajest and V. P. Mishra, “Maximum Information Measure Policies in Reinforcement Learning with Deep Energy-Based Model,” 2021 International Conference on Computational Intelligence and Knowledge Economy, 2021, pp. 19-24. DOI: https://doi.org/10.1109/ICCIKE51210.2021.9410756

D. Kumar, S. Kumar, R. Bansal and P.Singla. “A Survey to Nature Inspired Soft Computing.” International Journal of Information System Modeling and Design, vol. 8, no. 2, pp.112-133, 2017. DOI: https://doi.org/10.4018/IJISMD.2017040107

Nageswa Rao AR, Vijaya P, Kowsalya M. Voltage stability indices for stability assessment: a review. International Journal of Ambient Energy. 2021 May 19;42(7):829-45. DOI: https://doi.org/10.1080/01430750.2018.1525585

A.K. Gupta, T. Maity, H. Anandakumar, and Y.K Chauhan, “An electromagnetic strategy to improve the performance of PV panel under partial shading,” Computers & Electrical Engineering, Vol. 90, pp.106896. 2021. DOI: https://doi.org/10.1016/j.compeleceng.2020.106896

A.K. Gupta, Y.K Chauhan, and T Maity and R Nanda, “Study of Solar PV Panel Under Partial Vacuum Conditions: A Step Towards Performance Improvement,” IETE Journal of Research, pp.1-8, 2020. DOI: https://doi.org/10.1080/03772063.2020.1749145

Rao AN, Vijayapriya P, Kowsalya M, Rajest SS. Computer Tools for Energy Systems. International Conference on Communication, Computing and Electronics Systems 2020, pp. 475-484. Springer, Singapore. DOI: https://doi.org/10.1007/978-981-15-2612-1_46

D. Chauhan, A. Kumar, P. Bedi, V. A. Athavale, D. Veeraiah, and B. R. Pratap, “An effective face recognition system based on Cloud based IoT with a deep learning model,” Microprocessors and Microsystems, vol. 81, p. 103726, Mar. 2021. DOI: https://doi.org/10.1016/j.micpro.2020.103726

V. A. Athavale, A. Bansal, S. Nalajala, and S. Aurelia, “Integration of blockchain and IoT for data storage and management,” Materials Today: Proceedings, Oct. 2020, doi: 10.1016/j.matpr.2020.09.643. DOI: https://doi.org/10.1016/j.matpr.2020.09.643

S. C. Gupta, D. Kumar, and V. Athavale, “A Review on Human Action Recognition Approaches,” 2021 10th IEEE International Conference on Communication Systems and Network Technologies, Jun. 2021, doi: 10.1109/csnt51715.2021.9509646. DOI: https://doi.org/10.1109/CSNT51715.2021.9509646

D. Kumar, D.Mehrotra, and R. Bansal. “Query Optimization in Crowd-Sourcing Using Multi-Objective Ant Lion Optimizer.” International Journal of Information Technology and Web Engineering, vol. 14, no. 4, pp. 50-63, 2019. DOI: https://doi.org/10.4018/IJITWE.2019100103

S. Nagpal, V. A. Athavale, A. K. Saini, and R. Sharma, “Indian Health Care System is Ready to Fight Against COVID-19 A Machine Learning Tool for Forecast the Number of Beds,” 2020 Sixth International Conference on Parallel, Distributed and Grid Computing, Nov. 2020, doi: 10.1109/pdgc50313.2020.9315825. DOI: https://doi.org/10.1109/PDGC50313.2020.9315825

P. Sharma, V. Athavale, and A. Sinha, “Development of delay controller system modelin MANET,” 2019. Accessed: Mar 19, 2022. [Online]. Available: https://www.ijitee.org/wpcontent/uploads/papers/v8i5/E2883038519.pdf.

V. A. Athavale, “Digital Twin - A Key Technology driver in Industry 4.0,” Engineering Technology Open Access Journal, vol. 4, no. 1, Aug. 2021. DOI: https://doi.org/10.19080/ETOAJ.2021.04.555628

Aakanksha Singhal and D.K. Sharma, “New Generalized ‘Useful’ Entropies using Weighted Quasi-Linear Mean for Efficient Networking,” Mobile Networks and Applications, https://doi.org/10.1007/s11036-021-01858, pp. 1–11, 2022. DOI: https://doi.org/10.1007/s11036-021-01858-7

Kumar, S., Jain, A., Shukla, A. P., Singh, S., Raja, R., Rani, S., ... & Masud, M. A Comparative Analysis of Machine Learning Algorithms for Detection of Organic and Nonorganic Cotton Diseases. Mathematical Problems in Engineering, 2021. DOI: https://doi.org/10.1155/2021/1790171

Agarwal, A. K., & Jain, A. Synthesis of 2D and 3D NoC mesh router architecture in HDL environment. Journal of Advanced Research in Dynamical and Control Systems, 11(4), 2573-2581, 2019.

Jain, A., Kumar, A., & Sharma, S. (2015). Comparative Design and Analysis of Mesh, Torus and Ring NoC. Procedia Computer Science, 48, 330-337, 2015. DOI: https://doi.org/10.1016/j.procs.2015.04.190

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Published

03-05-2022

How to Cite

1.
Al-Zubaydi NAH. Smart Technology Based Empirical Mode Decomposition (EMD) Approach for Autonomous Transmission Line Fault Detection Protection. EAI Endorsed Trans Energy Web [Internet]. 2022 May 3 [cited 2024 Nov. 16];9(38):e7. Available from: https://publications.eai.eu/index.php/ew/article/view/733