Design and Study on Sliding Mode Extremum Seeking Control of the Chaos Embedded Particle Swarm Optimization for Maximum Power Point Tracking in Wind Power Systems

被引：24

作者：

Chen, Jui-Ho ^{[1
]}

Yau, Her-Terng ^{[1
]}

Hung, Weir ^{[1
]}

机构：

[1] Natl Chin Yi Univ Technol, Dept Elect Engn, Taichung 41170, Taiwan

来源：

ENERGIES | 2014年 / 7卷 / 03期

关键词：

extremum seeking control (ESC); sliding mode extremum seeking control (SMESC); maximum power point tracking (MPPT); particle swarm optimization (PSO); chaos; wind power;

D O I：

10.3390/en7031706

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

This paper proposes a sliding mode extremum seeking control (SMESC) of chaos embedded particle swarm optimization (CEPSO) Algorithm, applied to the design of maximum power point tracking in wind power systems. Its features are that the control parameters in SMESC are optimized by CEPSO, making it unnecessary to change the output power of different wind turbines, the designed in-repetition rate is reduced, and the system control efficiency is increased. The wind power system control is designed by simulation, in comparison with the traditional wind power control method, and the simulated dynamic response obtained by the SMESC algorithm proposed in this paper is better than the traditional hill-climbing search (HCS) and extremum seeking control (ESC) algorithms in the transient or steady states, validating the advantages and practicability of the method proposed in this paper.

引用

页码：1706 / 1720

页数：15

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