دانلود مقاله ISI انگلیسی شماره 8267
عنوان فارسی مقاله

کنترل نسل های اندازه گیری سیستم قدرت چند منطقه با استفاده از مرتب سازی چند هدفه بدون تسلط الگوریتم ژنتیک

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
8267 2013 10 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Automatic generation control of multi-area power system using multi-objective non-dominated sorting genetic algorithm-II
منبع

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

Journal : International Journal of Electrical Power & Energy Systems, Volume 53, December 2013, Pages 54–63

کلمات کلیدی
کنترل تولید خودکار - سیستم قدرت چند منطقه ای - مشتق انتگرال متناسب
پیش نمایش مقاله
پیش نمایش مقاله کنترل نسل های اندازه گیری  سیستم قدرت چند منطقه  با استفاده از مرتب سازی چند هدفه بدون تسلط الگوریتم ژنتیک

چکیده انگلیسی

Controllers design problems are multi objective optimization problems as the controller must satisfy several performance measures that are often conflicting and competing with each other. In multi-objective approach a set of solutions can be generated from which the designer can select a final solution according to his requirement and need. This paper presents the design and analysis Proportional Integral (PI) and Proportional Integral Derivative (PID) controller employing multi-objective Non-Dominated Shorting Genetic Algorithm-II (NSGA-II) technique for Automatic Generation Control (AGC) of an interconnected system. To minimize the effect of noise in the input signal, a filter is employed with the derivative term. Integral Time multiply Absolute Error (ITAE), minimum damping ratio of dominant eigenvalues and settling times in frequency and tie-line power deviations are considered as multiple objectives and NSGA-II is employed to generate Pareto optimal set. Further, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set. The proposed approach is first applied to a linear two-area power system model and then extended to a non-linear power system model by considering the effect of governor dead band non-linearity. The superiority of the proposed NSGA-II optimized PI/PID controllers has been shown by comparing the results with some recently published modern heuristic optimization approaches such as Bacteria Foraging Optimization Algorithm (BFOA), Genetic Algorithm (GA) and Craziness based Particle Swarm Optimization (CPSO) based controllers for the similar interconnected power systems.

خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.