دانلود مقاله ISI انگلیسی شماره 55516
ترجمه فارسی عنوان مقاله

کنترل بار - فرکانس مبتنی بر مد لغزشی در سیستم های قدرت

عنوان انگلیسی
Sliding mode based load-frequency control in power systems
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
55516 2010 14 صفحه PDF
منبع

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

Journal : Electric Power Systems Research, Volume 80, Issue 5, May 2010, Pages 514–527

ترجمه کلمات کلیدی
کنترل مد لغزشی؛ کنترل بار فرکانس؛ نمونه خروجی سریع؛ الگوریتم ژنتیک؛ عدم قطعیت
کلمات کلیدی انگلیسی
Sliding mode control; Load-frequency control; Fast output sampling; Genetic algorithm; Uncertainties
پیش نمایش مقاله
پیش نمایش مقاله  کنترل بار - فرکانس مبتنی بر مد لغزشی در سیستم های قدرت

چکیده انگلیسی

The paper presents a new discrete-time sliding mode controller for load-frequency control (LFC) in control areas (CAs) of a power system. As it uses full-state feedback it can be applied for LFC not only in CAs with thermal power plants but also in CAs with hydro power plants, in spite of their non-minimum phase behaviors. To enable full-state feedback we have proposed a state estimation method based on fast sampling of measured output variables, which are frequency, active power flow interchange and generated power from power plants engaged in LFC in the CA. The same estimation method is also used for the estimation of external disturbances in the CA, what additionally improves the overall system behavior. Design of the discrete-time sliding mode controller for LFC with desired behavior is accomplished by using a genetic algorithm. To the best of our knowledge, proposed controller outperforms any of the existing controllers in fulfilling the requirements of LFC. It was thoroughly compared to the commonly used PI controller by extensive simulation experiments on a power system with four interconnected CAs. These experiments show that the proposed controller ensures better disturbance rejection, maintains required control quality in the wider operating range, shortens the frequency’s transient response avoiding the overshoot and is more robust to uncertainties in the system.