CONTROL OF DOUBLY-FED INDUCTION GENERATOR USING ARTIFICIAL NEURAL NETWORK CONTROLLER

被引：0
|
作者：
Yaichi, I [1 ,2 ]
Semmah, A. [2 ]
Wira, P. [3 ]
机构：
[1] Ahmed Draya Univ, Lab Dev Durable & Informat LDDI, Adrar 01000, Algeria
[2] Univ Djillali Liabes Sidi Bel Abbes, Fac Elect Engn, Dept Elect Engn, Sidi Bel Abbes, Algeria
[3] Univ Haute Alsace, Inst Rech Informat Math Automatique & Signal IRIMA, F-68093 Mulhouse, France
来源：
REVUE ROUMAINE DES SCIENCES TECHNIQUES-SERIE ELECTROTECHNIQUE ET ENERGETIQUE | 2023年 / 68卷 / 01期
关键词：
Variable speed wind turbine; Doubly fed induction generator; Field oriented control; Conventional direct power control; Total harmonic distortion; Maximum power point tracking; Artificial neural network; PROPORTIONAL-INTEGRAL CONTROLLER; DIRECT TORQUE CONTROL; DIRECT POWER-CONTROL; WIND; DFIG;
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：
In this paper, we propose a direct power control (DPC) based on an artificial neural network (ANN-DPC) for the doubly-fed induction generator (DFIG), which is applied to the wind turbine system. The main objective of this intelligent technique is to replace the switching table and the hysteresis comparators with a neural control to reduce the ripple to the level of current and power. Field-oriented control (FOC) is traditionally achieved using a conventional proportional-integral controller (PI). The power ripples are reduced, and a reasonable total harmonic distortion rate is ensured by using an ANN-DPC.
引用
收藏
页码：46 / 51
页数：6
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