کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
493924 723156 2016 17 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Evolutionary optimization technique for comparative analysis of different classical controllers for an isolated wind–diesel hybrid power system
ترجمه فارسی عنوان
روش بهینه سازی تکاملی برای تجزیه و تحلیل مقایسه ای از کنترل کلاسیک مختلف برای یک باد دیزلی سیستم قدرت هیبریدی جدا شده
کلمات کلیدی
کنترل کلاسیک؛ فرکانس؛ الگوریتم جستجوی هارمونی؛ جدا شده سیستم قدرت دیزل باد هیبرید؛ قدرت و کنترل کننده PID
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
چکیده انگلیسی


• Modeling of an IHWDPS to supply more reliable power in rural areas.
• Obtaining optimized tunable parameters of the studied models by QOHS.
• Comparison of controllers on frequency and power deviation for the studied model.
• Robustness study of the most effective controller under wide change in load demand.

In this paper, the considered hybrid power system (HPS) is having a wind turbine generator, a diesel engine generator (DEG) and a storage device (such as capacitive energy storage). This paper presents a comparative study of frequency and power control for the studied isolated wind–diesel HPS with four different classical controllers for the pitch control of wind turbines and the speed governor control of DEG The classical controllers considered are integral, proportional-integral, integral-derivative and proportional-integral-derivative (PID) controller. A quasi-oppositional harmony search (QOHS) algorithm is proposed for the tuning of the controller gains. The comparative dynamic simulation response results indicate that better performance may be achieved with choosing PID controller among the considered classical controllers, when subjected to different perturbation. Stability and sensitivity analysis, presented in this paper, reveals that the optimized PID controller gains offered by the proposed QOHS algorithm are quite robust and need not be reset for wide changes in system perturbations.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Swarm and Evolutionary Computation - Volume 26, February 2016, Pages 120–136
نویسندگان
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