|本期目录/Table of Contents|

[1]王新生,吴吟箫,何川.基于风速预测的最大风能追踪控制系统仿真[J].电机与控制学报,2010,(02):20-24.
 WANG Xin-sheng,WU Yin-xiao,HE Chuan.Simulation of wind speed estimation for MPPT control[J].,2010,(02):20-24.
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基于风速预测的最大风能追踪控制系统仿真(PDF)
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《电机与控制学报》[ISSN:1007-449X/CN:23-1 408/TM]

卷:
期数:
2010年02
页码:
20-24
栏目:
出版日期:
2010-02-28

文章信息/Info

Title:
Simulation of wind speed estimation for MPPT control
作者:
王新生; 吴吟箫; 何川
哈尔滨工业大学(威海)控制科学与工程系
Author(s):
WANG Xin-sheng; WU Yin-xiao; HE Chuan
Department of Control Science and Engineering; Harbin Institute of Technology; Weihai 264209; China
关键词:
风力发电 风速预测 最大风能跟踪 径向基神经网络
Keywords:
wind power generation wind speed estimation maximum output power point RBF neural network
分类号:
TM614
DOI:
-
文献标志码:
A
摘要:
为了使交流励磁变速恒频风力发电系统在无需设置风速计的情况下,双馈电机实现最大风能跟踪的目的,提出了一种新的基于神经网络的无风速检测方案。通过利用高斯径向基神经网络预测为最大风能追踪提供了一个准确的风速数据,从而准确获取最大功率点下对应的电机转子转速,以减少系统的损耗和成本,提高系统的可靠性。本文针对3.6MW风力发电系统的数学模型,建立了基于定子磁链定向矢量控制的系统仿真模型。结合风速预估和有功功率、无功功率的解耦控制实现了最大风能跟踪。
Abstract:
To provide adequate wind speed information in variable speed constant frequency(VSCF)wind power generation without anemometers,a novel sensorless wind speed estimation through neural network is presented to track maximum wind energy or maximum output power point(MPPT)with doubly fed induction generator(DFIG).The wind speed is estimated by Gaussian radial basis functions(RBF)Neural Network and the rotor speed is decided accordingly to complete the MPPT.This kind of control systems is less costly and more rel...

参考文献/References:

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备注/Memo

备注/Memo:
山东省科技攻关项目(2007GG10007006)
更新日期/Last Update: 2010-06-03