Robustness Analysis of Dynamic Equivalent Model of DFIG Wind Farm for Stability Study

被引:81
|
作者
Zhou, Yuhao [1 ]
Zhao, Long [1 ]
Lee, Wei-Jen [1 ]
机构
[1] Univ Texas Arlington, Energy Syst Res Ctr, Arlington, TX 76019 USA
关键词
Doubly fed induction generators (DFIG) wind farm; dynamic equivalent model; hybrid improved-particle swarm optimization genetic algorithm (PSO-GA); parameters identification; robustness analysis; PARAMETER-IDENTIFICATION; SYSTEMS; ALGORITHM;
D O I
10.1109/TIA.2018.2858738
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
With the wind power energy largely interconnected with power grid, it is necessary to develop a robust dynamic equivalent model of the wind farm for the system stability analysis and control. In this paper, a detailed wind farm model with doubly fed induction generators is established according to Western Electricity Coordinating Council benchmark test system. Then, the parameters identification process based on aggregation technique consisting of a hybrid algorithm combined improved-particle swarm optimization with improved-genetic algorithm is proposed for dynamic equivalent model development by using the measurement data from phasor measurement unit at the point of interconnection. Additionally, the robustness of the developed equivalent model is analyzed. The simulation results of the benchmark test system and IEEE-9 bus system demonstrate the effectiveness and robustness of the proposed equivalent modeling and identification methodology.
引用
收藏
页码:5682 / 5690
页数:9
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