Traveling Wave-Based Fault Localization in FACTS-Compensated Transmission Line via Signal Decomposition Techniques

Saswati Mishra, Shubhrata Gupta, Anamika Yadav and Almoataz Y. Abdelaziz ()
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Saswati Mishra: Department of Electrical Engineering, National Institute of Technology Raipur, G. E. Road, Raipur 492010, CG, India
Shubhrata Gupta: Department of Electrical Engineering, National Institute of Technology Raipur, G. E. Road, Raipur 492010, CG, India
Anamika Yadav: Department of Electrical Engineering, National Institute of Technology Raipur, G. E. Road, Raipur 492010, CG, India
Almoataz Y. Abdelaziz: Faculty of Engineering & Technology, Future University in Egypt, Cairo 11835, Egypt

Energies, 2023, vol. 16, issue 4, 1-18

Abstract: Modern power systems are structurally complex and are vulnerable to undesirable events like faults. In the event of faults in transmission line, accurate fault location improves restoration process, thereby enhancing the reliability of the overall system. Fault location methods (FLMs) are tools which assist in identifying fault locations quickly. However, the accuracy of these FLMs gets affected in the presence of flexible alternating current transmission system (FACTS) devices. Therefore, in this work, the performance of four different signal decomposition techniques aided traveling wave aided FLMs are qualitatively compared in the context of fault localization in FACTS-compensated systems. FLMs based on intrinsic time decomposition (ITD), empirical mode decomposition (EMD), S-transform (ST), and estimation of signal parameters via rotational invariance technique (ESPRIT) are investigated. The accuracy of FLMs is tested for different cases of series, shunt, and series-shunt FACTS-compensated systems. A 500 kV system employed with 100 MVAr FACTS device is used for simulation. The instant of arrival wave at end of transmission line is from all aforementioned FLMs. The obtained ATWs are used in fault localization. Further, the associated percentage errors are calculated. The results suggest that EMD and ESPRIT-based FLMs are more accurate than others.

Keywords: empirical mode decomposition; ESPRIT; FACTS devices; fault localization; intrinsic time decomposition; S-transform (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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