现代电子技术2018，Vol.41Issue(3)：132-135,140,5.DOI:10.16652/j.issn.1004-373x.2018.03.031
基于神经网络的光伏系统MPPT控制算法设计
Design of neural network based MPPT control algorithm for photovoltaic system
摘要
Abstract
A maximum power point tracking (MPPT) control algorithm based on artificial neural network (ANN) is pro-posed. The algorithm can obtain the parameters needed by the ANN model by means of perturbation and observation (P&O) method. It includes the offline mode and online mode. The former mode can find the optimal network structure,activation func-tion and training algorithm by testing the neural network parameters. The latter mode can optimize the ANN,and apply it to the PV system. The input variables of the ANN are taken as the parameters of the output power and voltage,and the output variable is normalized as the increased or decreased duty ratio(+1 or -1). The performance of the proposed tracking algorithm is tested with Matlab/Simulink model for verification. The results show that the algorithm has perfect dynamic response speed and high steady-state control accuracy.关键词
人工神经网络/扰动与观测算法/光伏电池模型/MPPT控制/离线模式/在线模式Key words
artificial neural network/perturbation and observation algorithm/photovoltaic cell model/maximum power point tracking control/offline mode/online mode分类
信息技术与安全科学引用本文复制引用
吕晨旭..基于神经网络的光伏系统MPPT控制算法设计[J].现代电子技术,2018,41(3):132-135,140,5.基金项目
供电电压质量精益化治理及提升关键技术研究 （）
国网山西省电力公司项目(5205H016000B) Project Supported by The Study on Governance Refinement and Key Technique Improvement of Quality of Supplied Voltage,State Grid Shanxi Power Supply Company(5205H016000B) （5205H016000B）
