طراحی و ساخت رله‌ی خطای امپدانس بالا بر اساس تحلیل هارمونیکی برای شبکه‌ی توزیع 33 کیلوولت شهرستان اهواز
محورهای موضوعی : مهندسی برق و کامپیوترمهدي منادي 1 * , سیدقدرت‌اله سیف‌السادات 2 , رضا کیانی‌نژاد 3 , محمد بهاری پور 4
1 - دانشگاه شهید چمران اهواز
2 - دانشگاه شهید چمران اهواز
3 - دانشگاه شهید چمران اهواز
4 - شرکت فولاد خوزستان
کلید واژه: تحلیل هارمونیکی, حفاظت خطای امپدانس بالا, سیستم توزیع,
چکیده مقاله :
وقوع خطاهای امپدانس بالا (HIF) در شبکه‌های توزیع برق، خطرات جانی و مالی عمده‌ای را می‌تواند به همراه داشته باشد. از سوی دیگر، تشخیص این قبیل خطاها معمولاً توسط رله‌های اضافه جریان که معمولاً در سیستم‌های توزیع مورد استفاده قرار می‌گیرند، قابل انجام نیست و لازم است الگوریتم‌های خاصی برای آن طراحی و پیشنهاد گردد. در این مقاله، ابتدا ماهیت این خطاها و روش‌های شبیه‌سازی آنها مورد بررسی قرار گرفته و سپس با بررسی روش‌های قابل استفاده جهت تشخیص آنها، روشی مبتنی بر تحلیل‌های هارمونیکی ارائه شده است. در این روش، رله پیشنهادی پس از وقوع خطا، هارمونیک‌های مورد نیاز را استخراج نموده و با الگوریتمی که از قبل برای آن برنامه‌ریزی شده است، وقوع خطا را تشخیص می‌دهد. در این مقاله، نحوه ساخت رله پیشنهادی و بخش‌های مختلف سخت‌افزار آن توضیح داده شده است. همچنین نرم‌افزار این رله برای حالت‌های گوناگون وقوع خطاهای امپدانس بالا تحت آزمایش قرار گرفته و سخت‌افزار مربوط به آن نیز در آزمون آزمایشگاهی در تشخیص این خطاها موفق بوده است. با توجه به این که سخت‌افزار مورد استفاده در این رله می‌تواند با تغییرات اندکی برای سایر رله‌ها نیز مورد استفاده قرار گیرد، جزئیات مربوط به طراحی سخت‌افزار هم در این مقاله بیان شده است.
Over current relays that are used commonly in distribution system can't detect high impedance fault. Therefore for that purpose it is necessary to design special algorithms. In this paper, a method based on harmonic analysis is presented. In this technique, the proposed relay, after fault occurs, extracts the required harmonic and according designed algorithm, occurrence of fault is reported. Software of this relay for different scenarios of high impedance faults was tested; also its hardware of relay in laboratory tests could correctly identify events.
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