دانلود مقاله ISI انگلیسی شماره 139234
ترجمه فارسی عنوان مقاله

بهینه سازی آب شیرین برای حل مسئله اعزام نیروی واکنشی بهینه در سیستم های قدرت

عنوان انگلیسی
Ant lion optimizer for solving optimal reactive power dispatch problem in power systems
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
139234 2017 11 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Engineering Science and Technology, an International Journal, Volume 20, Issue 3, June 2017, Pages 885-895

ترجمه کلمات کلیدی
بهینه سازی شیرین یخی، اعزام قدرت راکتیو مطلوب، تلفات واقعی قدرت، شاخص ثبات ولتاژ، سیستم قدرت در مقیاس بزرگ،
کلمات کلیدی انگلیسی
The ant lion optimization; Optimal reactive power dispatch; Real power losses; Voltage stability index; Large-scale power system;
پیش نمایش مقاله
پیش نمایش مقاله  بهینه سازی آب شیرین برای حل مسئله اعزام نیروی واکنشی بهینه در سیستم های قدرت

چکیده انگلیسی

This paper presents the use of a recent developed algorithm inspired by the hunting mechanism of antlions in nature, called ant lion optimizer (ALO) algorithm for solving optimal reactive power dispatch (ORPD) problem considering a large-scale power system. The ORPD is formulated as a complex combinatorial optimization problem with nonlinear characteristic. The ALO algorithm is inspired from the hunting mechanism of antlions. One of the most interesting things in antlions is that they have a unique hunting behaviour and exhibit high capability of escaping the local optima stagnation. The ALO is used to find the set of optimal control variables of ORPD problem, such as generators terminal voltage, position of tap changers of transformers, and number of switchable capacitor banks. The performance and feasibility of the proposed algorithm are demonstrated through several simulation cases on IEEE 30-bus, IEEE 118-bus power systems and large-scale power system IEEE 300-bus power system. Comparison of obtained results with those reported in the literature shows clearly the superiority of ALO algorithm over other recently published algorithms in regards to real power losses and computational time, and hence confirmation of the efficiency of ALO algorithm in providing near-optimal solution.