دانلود مقاله ISI انگلیسی شماره 55624
ترجمه فارسی عنوان مقاله

بهینه سازی چندهدفه با استفاده از الگوریتم زنبور مصنوعی کلونی جمع وزنی برای کنترل فرکانس بار

عنوان انگلیسی
Multiobjective optimization using weighted sum Artificial Bee Colony algorithm for Load Frequency Control
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
55624 2014 11 صفحه PDF
منبع

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

Journal : International Journal of Electrical Power & Energy Systems, Volume 55, February 2014, Pages 657–667

ترجمه کلمات کلیدی
بهینه سازی چندهدفه؛ روش جمع وزنی؛ کنترل بار فرکانس (LFC)؛ PID؛ کلونی زنبور مصنوعی (ABC) الگوریتم
کلمات کلیدی انگلیسی
Multiobjective optimization; Weighted sum approach; Load Frequency Control (LFC); PID; Artificial Bee Colony (ABC) algorithm
پیش نمایش مقاله
پیش نمایش مقاله  بهینه سازی چندهدفه با استفاده از الگوریتم زنبور مصنوعی کلونی جمع وزنی برای کنترل فرکانس بار

چکیده انگلیسی

This paper presents the implementation of multiobjective based optimization of Artificial Bee Colony (ABC) algorithm for Load Frequency Control (LFC) on a two area interconnected reheat thermal power system. The ABC algorithm is currently being applied in many research works due to the local and global search capability of the algorithm. This paper uses the weighted sum approach of the ABC to optimize the PID controller’s gains to provide a compromise between the frequency response’s settling time and maximum overshoot. The composite objective function comprising both objectives is characterized by the performance criterions – Integral of Time Multiplied Absolute Error (ITAE) and Integral of Time Weighted Squared Error (ITSE). Analysis is carried out to determine the best weightage set for this investigation. A performance index based on Least Average Error (LAE) is formulated to calculate the index of each weightage set. In order to ensure effective compensation in the system output, the PID controllers for both areas are tuned simultaneously. The tuning performance of the algorithm is evaluated by comparing the performance of the proposed controller with conventional PI and PID controller. The robustness of the proposed algorithm is further investigated by evaluating the response of the system under simultaneous step load perturbation (SLP), changing load demand and collectively varying system parameters in the range of ±50%. The simulation result shows the dynamic response of the controller emphasizes on the compromise between the settling time and maximum overshoot of the frequency response. Furthermore, the proposed algorithm is robust enough to operate under different operating conditions and system parameter variations.