Speed-sensorless vector control of an wind turbine induction generator using artificial neural network

被引：0

作者：

Dumnic, Boris ^{[1
]}

Popadic, Bane ^{[1
]}

Milicevic, Dragan ^{[1
]}

Katic, Vladimir ^{[1
]}

Oros, Djura ^{[1
]}

机构：

[1] Univ Novi Sad, Fac Tech Sci, Dept Power Elect & Commun Engn, Novi Sad 21000, Serbia

来源：

2014 16TH INTERNATIONAL POWER ELECTRONICS AND MOTION CONTROL CONFERENCE AND EXPOSITION (PEMC) | 2014年

关键词：

component; wind energy; induction generator; speed estimation; MRAS observer; artificial neural network;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper present speed-sensorless vector control strategy for a squirrel cage induction generator (SCIG) used in variable speed wind energy conversion systems (WECS). In order to perform maximum power point tracking control (MPPT) of WECS, it is necessary to drive wind turbine at an optimal rotor speed. In this paper, rotational speed of the SCIG is estimated using improved model reference adaptive system (MRAS observer), with adaptive model based on artificial neural network (ANN). Extensive experimentation is conducted in order to verify efficiency and reliability of proposed control technique.

引用

页码：371 / 376

页数：6

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