دانلود مقاله ISI انگلیسی شماره 46774
عنوان فارسی مقاله

بهینه سازی چندهدفه توربین های جزر و مدی با محور افقی با استفاده از الگوریتم متاهیوریستیک

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
46774 2015 12 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Multi objective optimization of horizontal axis tidal current turbines, using Meta heuristics algorithms
منبع

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

Journal : Energy Conversion and Management, Volume 103, October 2015, Pages 487–498

کلمات کلیدی
بهینه سازی چند هدفه - الگوریتم های متاهیوریستیک -
پیش نمایش مقاله
پیش نمایش مقاله بهینه سازی چندهدفه توربین های جزر و مدی با محور افقی با استفاده از الگوریتم متاهیوریستیک

چکیده انگلیسی

The performance of horizontal axis tidal current turbines (HATCT) strongly depends on their geometry. According to this fact, the optimum performance will be achieved by optimized geometry. In this research study, the multi objective optimization of the HATCT is carried out by using four different multi objective optimization algorithms and their performance is evaluated in combination with blade element momentum theory (BEM). The second version of non-dominated sorting genetic algorithm (NSGA-II), multi objective particle swarm optimization algorithm (MOPSO), multi objective cuckoo search algorithm (MOCS) and multi objective flower pollination algorithm (MOFPA) are the selected algorithms. The power coefficient and the produced torque on stationary blade are selected as objective functions and chord and twist distributions along the blade span are selected as decision variables. These algorithms are combined with the blade element momentum (BEM) theory for the purpose of achieving the best Pareto front. The obtained Pareto fronts are compared with each other. Different sets of experiments are carried out by considering different numbers of iterations, population size and tip speed ratios. The Pareto fronts which are achieved by MOFPA and NSGA-II have better quality in comparison to MOCS and MOPSO, but on the other hand a detail comparison between the first fronts of MOFPA and NSGA-II indicated that MOFPA algorithm can obtain the best Pareto front and can maximize the power coefficient up to 4.3% and the produced torque on stationary blade up to 57.9%. The geometries of the first and last members of the Pareto front of MOFPA are compared to each other. These members which produce the maximum power coefficient and the maximum produced torque on stationary blade have hyperbolic and constant chord distributions, respectively.

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