Sliding mode extremum seeking control based on improved invasive weed optimization for MPPT in wind energy conversion system

被引：46

作者：

Hu, Lu ^{[1
]}

Xue, Fei ^{[2
]}

Qin, Zijian ^{[3
]}

Shi, Jiying ^{[4
]}

Qiao, Wen ^{[4
]}

Yang, Wenjing ^{[4
]}

Yang, Ting ^{[4
]}

机构：

[1] Yongchuan Power Supply Co, State Grid Chongqing Elect Power Co, Chongqing 402160, Peoples R China

[2] Ningxia Elect Power Co, Elect Power Res Inst, Yinchuan 750001, Ningxia Hui Aut, Peoples R China

[3] Laiwu Power Supply Co, State Grid Shandong Elect Power Co, Laiwu 271100, Shandong, Peoples R China

[4] Tianjin Univ, Smart Grid Key Lab, Minist Educ, Tianjin 300072, Peoples R China

来源：

APPLIED ENERGY | 2019年 / 248卷 / 567-575期

基金：

国家重点研发计划; 中国国家自然科学基金;

关键词：

Wind energy conversion system (WECS); Maximum power point tracking; Sliding mode extremum seeking control; Improved invasive weed optimization; POWER POINT TRACKING; PARTICLE SWARM OPTIMIZATION; TURBINES; PERFORMANCE; EXTRACTION; SIMULATION;

D O I：

10.1016/j.apenergy.2019.04.073

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：

The sliding mode extremum seeking control (SMESC) could track the maximum power point (MPP) of wind energy conversion system (WECS) without wind speed or wind turbine parameters. Inappropriate SMESC parameters would cause steady-state oscillation and increase tracking time. This paper proposed an improved invasive weed optimization (IIWO) to optimize the SMESC parameters. The algorithm developed a new stochastic reproductive strategy to enhance its robustness and simplify the coding. Meanwhile, IIWO optimized double parameters coordinately to replace traditional parameter setting methods of SMESC, which could make the parameters meet the different requirements simultaneously for high efficiency. Simulation results showed that proposed IIWO-SMESC method yielded a better transient response, steady-state stability, and robustness than traditional hill-climbing search (HCS) and SMESC method.

引用

页码：567 / 575

页数：9

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