Design of Three-phase Photovoltaic Grid Connected Inverter based on RBF Neural Network

被引：0

作者：

He Su-fen ^{[1
]}

Yi Ling-zhi ^{[1
]}

Li Ju-cheng

Yao Zhe-zhi

Peng Han-mei

机构：

[1] Xiangtan Univ, Inst Informat Engn, Xiangtan 411105, Peoples R China

来源：

2009 INTERNATIONAL CONFERENCE ON SUSTAINABLE POWER GENERATION AND SUPPLY, VOLS 1-4 | 2009年

关键词：

photovoltaic system; grid-connected inverter; MPPT; RBF Neural-Network; clustering method; SVPWM; control of predictive current; three-phase half-bridge circuit; voltage space vectors; MATLAB;

D O I：

暂无

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：

A new complete RBF Neural Network SVPWM Controller scheme for a grid-connected inverter is presented in this paper, RBF network architecture and the parameter is determined by using the clustering method, the RBF Neural Network which is simplifies and realize voltage space vector modulate to control the inverter. It was used in three-phase photovoltaic grid-connected inverse system which adopts control of predictive current. A computer simulation program is developed using MATLAB. The simulation results show that the method features simplicity, high efficiency and excellent control effect(1).

引用

页码：1471 / +

页数：2

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