文献类型：期刊文献

中文题名：基于模糊神经网络控制方法的光伏发电系统并网设计

英文题名：GRID CONNECTION DESIGN OF PV POWER GENERATION SYSTEM BASED ON FUZZY NEURAL NETWORK CONTROL METHOD

作者：陈宇能[1];陈景贤[1];廖钧濠[1];陈秀雯[2]

机构：[1]广东海洋大学电子与信息工程学院,湛江524088;[2]广东南方职业学院管理学院,江门529000

年份：2023

期号：11

起止页码：48

中文期刊名：太阳能

外文期刊名：Solar Energy

基金：国家级大学生创新创业训练计划项目资助(201910566026)。

语种：中文

中文关键词：光伏发电系统;最大功率点追踪;神经网络;模糊控制算法;并网

外文关键词：PV power generation system;MPPT;neural network;fuzzy control algorithm;grid connection

中文摘要：针对光伏发电系统运行过程中极易受到环境温度、太阳辐照度等外部条件干扰,从而导致其输出功率存在间歇性、随机性问题的情况,提出一种基于模糊控制算法及前馈(BP)神经网络的智能控制方法(下文简称为“模糊神经网络控制方法”)来进行光伏发电系统并网设计,并搭建并网电路模型进行仿真分析。分析结果显示:相较于扰动观察法、模糊控制算法,采用模糊神经网络控制方法的并网光伏发电系统的泛化能力和鲁棒性更强,能更好地提高系统的稳态性和可靠性,可有效解决光伏发电输出功率存在的间歇性和随机性问题。

外文摘要：In response to the fact that PV power generation systems are highly susceptible to external conditions such as environmental temperature and solar irradiance during operation,resulting in intermittent and random issues with its output power,this paper proposes an intelligent control method based on fuzzy control algorithm and BP neural network(hereinafter referred to as“fuzzy neural network control method”)for grid connection design of PV power generation systems,and builds a grid connection circuit model for simulation analysis.The analysis results show that compared to the disturbance observation method and fuzzy control algorithm,the fuzzy neural network control method used in the grid connected PV power generation system has stronger generalization ability and robustness,which can better improve the steady-state and reliability of the system,and effectively solve the intermittent and random problems in the output power of PV power generation.