24 تیر 1403
رحمن دشتي

رحمن دشتی

مرتبه علمی: دانشیار
نشانی: دانشکده مهندسی سیستم های هوشمند و علوم داده - گروه مهندسی برق
تحصیلات: دکترای تخصصی / مهندسی برق
تلفن: +98-7731222752
دانشکده: دانشکده مهندسی سیستم های هوشمند و علوم داده

مشخصات پژوهش

عنوان A Parameter-Free Approach for Fault Section Detection on Distribution Networks Employing Gated Recurrent Unit
نوع پژوهش مقالات در نشریات
کلیدواژه‌ها
fault section; deep learning; GRU; smart feeder meter; distribution network; real time
مجله Energies
شناسه DOI https://doi.org/10.3390/en14196361
پژوهشگران محمدرضا شادی (نفر اول) ، حمید میرشکالی (نفر دوم) ، رحمن دشتی (نفر سوم) ، محمد تقی آملی (نفر چهارم) ، حمید رضا شاکر (نفر پنجم)

چکیده

Faults in distribution networks can result in severe transients, equipment failure, and power outages. The quick and accurate detection of the faulty section enables the operator to avoid prolonged power outages and economic losses by quickly retrieving the network. However, the occurrence of diverse fault types with various resistances and locations and the highly non-linear nature of distribution networks make fault section detection challenging for numerous conventional techniques. This study presents a cutting-edge deep learning-based algorithm to distinguish fault sections in distribution networks to address these issues. The proposed gated recurrent unit model utilizes only two samples of the angle between the voltage and current on either side of the feeders, which record by smart feeder meters, to detect faulty sections in real time. When a network fault occurs, the protection relays trigger the trip command for the breakers. Immediately, the angle data are obtained from all smart feeder meters of the network, which comprises a pre-fault sample and a post-fault sample. The data are then employed as an input to the pre-trained gated recurrent unit model to determine the faulted line. The performance of this novel algorithm was validated through simulations of various fault types in the IEEE-33 bus system. The model recognizes the faulty section with competitive performance in terms of accuracy.