کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6859711 | 1438733 | 2015 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Service restoration for unbalanced distribution networks using a combination two heuristic methods
ترجمه فارسی عنوان
ترمیم سرویس برای شبکه های توزیع نامتعادل با استفاده از دو روش اکتشافی
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
ترمیم خدمات، شبکه توزیع نامتعادل، سوئیچ شاخص، مبتنی بر گرافیک، جریان سه فاز،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
In this paper, two heuristic methods are proposed to find the effective and fast solution for solving service restoration problem in unbalanced three phase distribution networks. Switch selection indices based on analytically approach and practicable heuristic graph-based method are proposed for solving the service restoration problem in unbalanced distribution networks. The problem formulation proposed, consists of three different objective functions: First, minimizing the de-energized customers' load, second, minimizing the number of switching operation, and finally, customer's priority. A suitable assignment of switch indices to all tie switches (ts) in networks are used to find best solution and decrease number of switching operation. New graph-based approach for finding best sectionalizes switch (ss) and minimizing voltage drop's amount is utilized. The validity of these approaches has been tested on the two unbalanced three phase distribution networks. Results have been presented for modified IEEE 13-node and IEEE 37-node test case. The fastness and effectiveness convergence of these approaches helps finding best solution for service restoration problem.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Electrical Power & Energy Systems - Volume 67, May 2015, Pages 222-229
Journal: International Journal of Electrical Power & Energy Systems - Volume 67, May 2015, Pages 222-229
نویسندگان
Meysam Gholami, Jamal Moshtagh, Leila Rashidi,