Dynamic Behavior Analysis for Optimally Tuned On-Grid DFIG Systems

S. Soued , H.S. Ramadan , M. Becherif
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引用次数: 10

Abstract

Metaheuristic Optimization Techniques (MOTs) such as the Artificial Bee Colony (ABC) algorithms and Grey Wolf Optimizer (GWO) can be conveniently used for reaching the Maximum Power Point Tracking (MPPT) of Wind Energy Conversion System (WECS). This paper presents an enhanced control strategy for both Rotor Side Converter (RSC) and Grid Side Converter (GSC) of the Doubly Fed Induction Generator (DFIG)-based WECS using the ABC and the GWO algorithms to ensure the MPPT for the WECS. The control strategy for the RSC and GSC are verified via 9 MW DFIG Wind Turbine (WT) using MATLABTM/Simulink. The dynamic performance improvement of the DFIG depends on the appropriate choice of the optimal PI controllers’ gains. The numerical simulation results show the superiority of the proposed GWO-PI and the ABC-PI optimal controllers over the traditional PI regulators towards enhancing the DFIG system dynamic performance.

优化调谐并网DFIG系统的动态行为分析
人工蜂群(Artificial Bee Colony, ABC)算法和灰狼优化器(Grey Wolf Optimizer, GWO)等元启发式优化技术可以方便地实现风能转换系统的最大功率点跟踪(MPPT)。本文提出了一种基于双馈感应发电机(DFIG)的转子侧变换器(RSC)和栅格侧变换器(GSC)的增强控制策略,采用ABC和GWO算法来保证双馈感应发电机(DFIG)的转子侧变换器(RSC)和栅格侧变换器(GSC)的最大功率。利用matlab /Simulink对9mw DFIG风力发电机的RSC和GSC控制策略进行了验证。DFIG的动态性能改进取决于最佳PI控制器增益的适当选择。数值仿真结果表明,与传统的PI调节器相比,所提出的GWO-PI和ABC-PI最优控制器在提高DFIG系统动态性能方面具有优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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