کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6682451 | 501848 | 2016 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A wolf pack hunting strategy based virtual tribes control for automatic generation control of smart grid
ترجمه فارسی عنوان
یک بسته گرگ شکار بر اساس قبایل مجازی مبتنی بر کنترل خودکار نسل هوشمند شبکه کنترل می شود
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کلمات کلیدی
استقلال برق، قبیله های مجازی کنترل شکار باد بسته چند عامل انتشار کربن،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
مهندسی انرژی و فناوری های برق
چکیده انگلیسی
This paper proposes a novel electric power autonomy to satisfy the requirement of power generation optimization of smart grid and decentralized energy management system. A decentralized virtual tribes control (VTC) is developed which can effectively coordinate the regional dispatch centre and the distributed energy. Then a wolf pack hunting (WPH) strategy based VTC (WPH-VTC) is designed through combining the multi-agent system stochastic game and multi-agent system collaborative consensus, which is called the multi-agent system stochastic consensus game, to achieve the coordination and optimization of the decentralized VTC, such that different types of renewable energy can be effectively integrated into the electric power autonomy. The proposed scheme is implemented on a flexible and dynamic multi-agent stochastic game-based VTC simulation platform, which control performance is evaluated on a typical two-area load-frequency control power system and a practical Guangdong power grid model in southern China. Simulation results verify that it can improve the closed-loop system performances, increase the utilization rate of the renewable energy, reduce the carbon emissions, and achieve a fast convergence rate with significant robustness compared with those of existing schemes.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Energy - Volume 178, 15 September 2016, Pages 198-211
Journal: Applied Energy - Volume 178, 15 September 2016, Pages 198-211
نویسندگان
Lei Xi, Tao Yu, Bo Yang, Xiaoshun Zhang, Xuanyu Qiu,