فصلنامه علمی کارافن

فصلنامه علمی کارافن

تشخیص خطای امپدانس بالا در شبکۀ توزیع مبتنی بر گرادیان مورفولوژیکی

نوع مقاله : مقاله پژوهشی (کاربردی)

نویسندگان
1 عضو هیئت علمی، گروه مهندسی برق، دانشگاه فنی و حرفه‌ای، تهران، ایران.
2 دکترای تخصصی، گروه مهندسی برق، دانشگاه امیرکبیر، تهران، ایران.
چکیده
تشخیص خطای امپدانس بالا (HIF) یکی از بزرگترین چالش­ها در شبکۀ توزیع برق است. HIF معمولاً زمانی رخ می­دهد که هادی­ها در شبکۀ توزیع شکسته و سطح زمین یا شاخۀ درخت را لمس کنند. جریان این خطا، نزدیک به سطح جریان بار است و توسط رله­های جریان زیاد، قابل تشخیص نیست. در این مقاله، یک روش جدید برای تشخیص HIF از سایر پدیده­های مشابه در شبکۀ توزیع مانند کلیدزنی خازنی، کلیدزنی بار، جریان هجومی و اشباع CT ارائه شده است. روش پیشنهادی از گرادیان مورفولوژیکی تشخیص لبه (MGED) برای پردازش سیگنال­های ولتاژ استفاده می­کند. با استفاده از MGED، لبه­ها یا تغییرات ایجاد شده در سیگنال و ویژگی­های آن بعد از دو سیکل از شروع خطا، استخراج می‌شوند. بر اساس این ویژگی­ها، یک شاخص تشخیص خطا (FDI) برای تمایز و طبقه­بندی HIF، کلیدزنی خازنی، کلیدزنی بار، جریان هجومی و اشباع CT معرفی می­شود. نتایج حاصل از شبیه­سازی­ برای شرایط مختلف خطای HIF و پدیده­های مشابه در یک فیدر نمونه kV 20  و شبکۀ توزیع 34 شینه  IEEEدر محیط نرم افزار EMTP، عملکرد سریع و دقیق روش پیشنهادی را تأیید می‌کنند.
کلیدواژه‌ها
موضوعات

عنوان مقاله English

High Impedance Fault Detection in Distribution Networks based on Morphological gradient

نویسندگان English

Moslem Salehi 1
Mahdi Zolfaghari 2
1 Faculty Member, Department of Electrical Engineering, Technical and Vocational University, (TVU), Tehran, Iran.
2 Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran.
چکیده English

High impedance fault (HIF) detection is one of the major challenges in power distribution networks. HIF usually occurs when conductors in the distribution network are broken and touch the ground or a tree branch. The current of this fault is close to the load current level and cannot be detected by over-current relays. In the present paper, a new method for detecting HIF from other similar phenomena in the distribution network such as capacitor switching, load switching, inrush current and CT saturation is presented. The proposed method uses morphological gradient edge detection (MGED) to process voltage signals. Using MGED, the edges or transient changes in the signal and its features after two cycles from the beginning of the fault were extracted. Based on these features, a fault detection index (FDI) was introduced for distinguishing and classifying HIF, capacitor switching, load switching, inrush current and CT saturation. The simulation results for different HIF fault conditions and similar phenomena in a 20 kV sample feeder and IEEE 34 bus distribution system in EMTP software environment confirmed the fast and accurate performance of the proposed method.

کلیدواژه‌ها English

High Impedance Fault
Mathematical Morphology
Distribution Network
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دوره 21، شماره 1 - شماره پیاپی 66
فنی و مهندسی
بهار 1403
صفحه 241-267

  • تاریخ دریافت 22 فروردین 1402
  • تاریخ بازنگری 08 خرداد 1402
  • تاریخ پذیرش 11 تیر 1402