دانلود مقاله ISI انگلیسی شماره 146723
ترجمه فارسی عنوان مقاله

قرار دادن خازن شونت در شبکه های توزیع شعاعی با توجه به شیوه تصمیم گیری سوئیچینگ گذار

عنوان انگلیسی
Shunt capacitor placement in radial distribution networks considering switching transients decision making approach
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
146723 2017 14 صفحه PDF
منبع

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

Journal : International Journal of Electrical Power & Energy Systems, Volume 92, November 2017, Pages 167-180

ترجمه کلمات کلیدی
خازن شونت، گذارهای سوئیچینگ، بهینه سازی چند هدفه، جریان نیروی جریان، تکنیک جستجوی محلی، الگوریتم ژنتیک مرتب سازی نشده غالب،
کلمات کلیدی انگلیسی
Shunt capacitors; Switching transients; Multi-objective optimization; Iterative power flow; Local search technique; Non-dominated sorting genetic algorithm;
پیش نمایش مقاله
پیش نمایش مقاله  قرار دادن خازن شونت در شبکه های توزیع شعاعی با توجه به شیوه تصمیم گیری سوئیچینگ گذار

چکیده انگلیسی

This paper provides a new approach in decision making process for shunt capacitor placement in distribution networks. The main core of the evaluation process is a multi-objective framework to allocate the capacitor banks. The power loss and the total harmonic distortion (THD) are the objective functions of the system under study in a long-term planning horizon. In order to select the executive plan introduced by using a multi-objective model, transient switching overvoltages have been considered. As the size and location of shunt capacitors may result in unacceptable overvoltages, the proposed technical decision making framework can be applied to avoid corresponding damages. In this paper, an iterative conventional power flow technique is introduced. This technique can be applied to evaluate THD for distribution networks as well as other power flow based objectives, such as power losses calculation and voltage stability assessment. The presented framework is a two stage one where at the first stage, a non-dominated sorting genetic algorithm (NSGA-II) augmented with a local search technique is used in order to solve the addressed multi-objective optimization problem. Then, at the second stage, a decision making support technique is applied to determine the best solution from the obtained Pareto front. In order to evaluate the effectiveness of the proposed method, two benchmarks are addressed in this paper. The first test system is a 9-bus distribution network and the second one is an 85-bus large scale distribution network. The simulation results show that the presented method is satisfactory and consistent with the expectation.