کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
381125 1437475 2011 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Evolving ant direction differential evolution for OPF with non-smooth cost functions
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Evolving ant direction differential evolution for OPF with non-smooth cost functions
چکیده انگلیسی

In this paper, an effective and reliable algorithm, termed as evolving ant direction differential evolution (EADDE) algorithm, for solving the optimal power flow problem with non-smooth and non-convex generator fuel cost characteristics is presented. In this method, suitable mutation operator for differential evolution (DE) is found by ant colony search. The genetic algorithm evolves the ant colony parameters and the Newton–Raphson method solves the power flow problem. The proposed algorithm has been examined on the standard IEEE 30-bus and IEEE 57-bus systems with three different objective functions. Different cases were considered to investigate the robustness of the proposed method in finding the global solution. The EADDE provides better results compared to classical DE and other methods recently reported in the literature as demonstrated by simulation results.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Applications of Artificial Intelligence - Volume 24, Issue 3, April 2011, Pages 426–436
نویسندگان
, ,