دانلود مقاله ISI انگلیسی شماره 146246
کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
146246 2017 51 صفحه PDF سفارش دهید 14854 کلمه
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عنوان انگلیسی
Quasi-oppositional symbiotic organism search algorithm applied to load frequency control
منبع

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

Journal : Swarm and Evolutionary Computation, Volume 33, April 2017, Pages 46-67

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چکیده انگلیسی

The present work approaches a relatively new optimization scheme called “quasi-oppositional symbiotic organism search (QOSOS) algorithm”, for the first time, to find an optimal and effective solution for load frequency control (LFC) problem of the power system. The symbiotic organism search (SOS) algorithm works on the effect of symbiotic interaction strategies adopted by an organism to survive and propagate in the ecosystem. To avoid the suboptimal solution and to accelerate the convergence speed, the theory of quasi-oppositional based learning (Q-OBL) is integrated with original SOS and used to solve the LFC problem. To demonstrate the effectiveness of QOSOS algorithm, two-area interconnected power system with nonlinearity effect of governor dead band and generation rate constraint is considered at the first instant, followed by the four-area power system showing the consequence of load perturbation. The structural simplicity, robust performance and acceptability of well-popular proportional-integral-derivative (PID) controller enforce to implement it as a secondary controller for the present analysis. The success of QOSOS algorithm is established by comparing the dynamic performances of concerned power system with those obtained by some recently published algorithms available in the literature. Furthermore, the robustness and sensitivity are analyzed for the concerned power system to judge the efficacy of the proposed QOSOS approach.

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