کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
398282 1438720 2016 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Ultra high speed deterministic algorithm for transmission lines disturbance identification based on principal component analysis and Euclidean norm
ترجمه فارسی عنوان
الگوریتم قطعی فوق العاده با سرعت بالا برای شناسایی اختلالات خطوط انتقال بر اساس تجزیه و تحلیل مولفه اصلی و هنجار اقلیدس
کلمات کلیدی
الگوریتم تعیین کننده، شرایط نامطلوب، الگو الیپسیوئید، هنجار اقلیدس
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• Transient signals detection and identification is presented.
• Principal Component Analysis, Ellipsoidal Pattern and Euclidean Norm are used.
• The most important parameters of switching operations and lightning strokes are considered.
• Different patterns and criteria are determined.
• Ultra-high speed novel protection relay algorithms are proposed.

Protection devices are designed to provide high sensitivity to transients produced by undesirable conditions like lightning stroke, avoiding their operation under all tolerable events like switching operations. The problem of incorrect operation due to transient phenomena can be handled by two means, one is to allow the transients and provide additional logics in the relay, other means is to damp the oscillation from source side. Protection relays’ not always must trip or send a trip signal and sometimes, only an alarm is necessary. In this context, this research presents a fast and reliable formulation for transmission lines (TLs) switching operations and lightning strokes detection and identification.The proposed methodology is based on Principal Component Analysis (PCA) and Euclidean Norm (EN); by using PCA it is possible to determine that normal operation signals describe a very well defined Ellipsoidal Pattern (EP). In this manner, by calculating the Euclidean Norm (EN) among Principal Components (PCs) for each sample and the origin of the reference Ellipsoidal Pattern, switching operations and lightning strokes are detected and identified. Test results show that the proposed algorithm presents high success on phenomena detection and identification, presenting a high potential for online applications.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Electrical Power & Energy Systems - Volume 80, September 2016, Pages 312–324
نویسندگان
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