کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9652056 | 1438829 | 2005 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A neural space vector fault location for parallel double-circuit distribution lines
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
A new approach to fault location for parallel double-circuit distribution power lines is presented. This approach uses the Clarke-Concordia transformation and an artificial neural network based learning algorithm. The α, β, 0 components of double line currents resulting from the Clarke-Concordia transformation are used to characterize different states of the system. The neural network is trained to map the non-linear relationship existing between fault location and characteristic eigenvalue. The proposed approach is able to identify and to locate different types of faults such as: phase-to-earth, phase-to-phase, two-phase-to-earth and three-phase. Using the eigenvalue as neural network inputs the proposed algorithm locates the fault distance. Results are presented which shows the effectiveness of the proposed algorithm for a correct fault location on a parallel double-circuit distribution line.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Electrical Power & Energy Systems - Volume 27, Issue 3, March 2005, Pages 225-231
Journal: International Journal of Electrical Power & Energy Systems - Volume 27, Issue 3, March 2005, Pages 225-231
نویسندگان
L. Sousa Martins, J.F. Martins, V. Fernão Pires, C.M. Alegria,