دانلود مقاله ISI انگلیسی شماره 56319
ترجمه فارسی عنوان مقاله

تکامل تفاضلی شبه اپوزیسیون برای توزیع بهینه توان راکتیو

عنوان انگلیسی
Quasi-oppositional differential evolution for optimal reactive power dispatch
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
56319 2016 12 صفحه PDF
منبع

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

Journal : International Journal of Electrical Power & Energy Systems, Volume 78, June 2016, Pages 29–40

ترجمه کلمات کلیدی
تکامل تفاضلی شبه تقابلی؛ تکامل تفاضلی؛ توزیع توان راکتیو؛ تلفات توان اکتیو ؛ مشخصات ولتاژ؛ پایداری ولتاژ
کلمات کلیدی انگلیسی
Quasi-oppositional differential evolution; Differential evolution; Reactive power dispatch; Active power loss; Voltage profile; Voltage stability
پیش نمایش مقاله
پیش نمایش مقاله  تکامل تفاضلی شبه اپوزیسیون برای توزیع بهینه توان راکتیو

چکیده انگلیسی

This paper presents quasi-oppositional differential evolution to solve reactive power dispatch problem of a power system. Differential evolution (DE) is a population-based stochastic parallel search evolutionary algorithm. Quasi-oppositional differential evolution has been used here to improve the effectiveness and quality of the solution. The proposed quasi-oppositional differential evolution (QODE) employs quasi-oppositional based learning (QOBL) for population initialization and also for generation jumping. Reactive power dispatch is an optimization problem that reduces grid congestion with more than one objective. The proposed method is used to find the settings of control variables such as generator terminal voltages, transformer tap settings and reactive power output of shunt VAR compensators in order to achieve minimum active power loss, improved voltage profile and enhanced voltage stability. In this study, QODE has been tested on IEEE 30-bus, 57-bus and 118-bus test systems. Test results of the proposed QODE approach have been compared with those obtained by other evolutionary methods reported in the literature. It is found that the proposed QODE based approach is able to provide better solution.