FisPro based interpretable fuzzy inference system for dual circuit extra high voltage transmission line fault classification and fault distance estimation

سال انتشار: 1404
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 42

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شناسه ملی سند علمی:

JR_JFEA-6-3_009

تاریخ نمایه سازی: 7 دی 1404

چکیده مقاله:

Accurate fault classification and precise fault distance estimation play a critical role in reliable, stable and optimal operation of electrical power systems. Especially Dual Circuit Extra High Voltage Transmission Line (DCEHVTL) fault diagnosis is a challenging task using conventional algorithms. Early fault recognition is crucial for DCEHVTL performance. Due to its effectiveness in classification and forecasting, the interpretable Mamdani Fuzzy Inference System (MFIS) is more suitable. Haar wavelet is efficient in any signal behavior evaluation. Therefore, this paper proposed a robust and intelligent Fuzzy Inference System Professional (FisPro) based interpretable MFIS with Haar wavelets transform for fault classification and fault distance estimation in DCEHVTL using single-side data. The dual circuit three-phase currents of two cycles are recorded from DCEHVTL. Haar wavelet transforms are utilized to estimate the behaviour and characteristics of the current signals in terms of high-frequency components. The captured fault currents from the DCEHVTL single side are used as inputs for the hierarchical MFIS framework. Here, the fault classification is followed by the faulty distance estimation in MFIS. The test results support the MFIS consistency under extensive changes in fault factors. Moreover, the extensive performance comparison study with the state of art fault diagnosis methods reiterates the FisPro based MFIS effectiveness in successful fault diagnosis. The obtained results indicate that MFIS has a fast processing time (in ۱ms), high accuracy (above ۹۹.۸%), less fault location error (Within ۰.۰۰۲۴%) and is useful for studying the system stability in the electricity field. The MFIS is proven to be successful for the fault diagnosis without any communication channel between the source and receiving end.

کلیدواژه ها:

Fuzzy inference system professional ، Faults ، Dual Circuit ، accuracy

نویسندگان

A Naresh Kumar

Department of Electrical and Electronics Engineering, Institute of Aeronautical Engineering, Hyderabad, India.

Sajja Suneel

Department of CSE (Data Science), Institute of Aeronautical Engineering, Hyderabad, India.

Bharathi Gururaj

Department of Electronics and Communication Engineering, KS Institute of Technology, Bengaluru, India.

Muktevi Chakravarthy

Department of Electrical and Electronics Engineering, Vasavi College of Engineering, Hyderabad, India.

Mortha Suresh Kumar

Department of Space Engineering, Ajeenkya DY Patil University, Pune, India.

Muniyappa Ramesha

Department of Electrical, Electronics and Communication Engineering, GITAM, Bengaluru, India.

Elemasetty Uday Kiran

Department of Aerospace Engineering, Toronto Metropolitan University, Toronto, Canada.

Malleboina Nagaraju

Department of Information Technology, University of the Cumberlands, Williamsburg, USA.

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