کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
398180 1438718 2016 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Chaos embedded krill herd algorithm for optimal VAR dispatch problem of power system
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Chaos embedded krill herd algorithm for optimal VAR dispatch problem of power system
چکیده انگلیسی


• CKHA algorithm is applied for the solution of optimal VAR dispatch problem.
• CKHA is implemented on standard IEEE 14-bus and IEEE 118-bus test systems.
• Three different objective functions are considered.
• CKHA based results are compared to other algorithms recently reported.
• Effectiveness of CKHA is established for optimal VAR dispatch problem.

Chaotic krill herd algorithm (KHA) (CKHA) is proposed in this paper to solve the optimal VAR dispatch problem of power system considering either minimization of real power loss or that of absolute value of total voltage deviation or improvements of voltage profile as an objective while satisfying all the equality and the inequality constraints of the power system network. Detailed studies of different chaotic maps are illustrated. Among these, Logistic map is considered in the proposed technique to improve the performance of the basic KHA. The performance of the proposed CKHA is implemented, successfully, on standard IEEE 14- and IEEE 118-bus test power systems in which the control of bus voltages, tap position of transformers and reactive power sources are involved. The results offered by the proposed CKHA are compared to other evolutionary optimization based techniques surfaced in the recent state-of-the-art literature. Simulation results indicate that the proposed CKHA approach yields better optimization efficacy over some other recent popular techniques in terms of results offered, effectiveness, quality of solution and convergence speed.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Electrical Power & Energy Systems - Volume 82, November 2016, Pages 37–48
نویسندگان
, ,