基于人工神经网络的光伏系统升压变换器PID控制器设计

S. Gupta, J. K. Mohanta
{"title":"基于人工神经网络的光伏系统升压变换器PID控制器设计","authors":"S. Gupta, J. K. Mohanta","doi":"10.1109/PIECON56912.2023.10085911","DOIUrl":null,"url":null,"abstract":"The most attractive renewable energy resource that provides clean electricity via solar PV panels is solar irradiation received from the Sun. Solar energy is available mainly during the daytime, but solar photovoltaic (PV) panels can produce maximum power due to low efficiency. Hence, maximum power point tracking (MPPT) methods are used with solar PV systems. The interface required between solar PV panels and the load is a DC-DC converter, a power electronics device. This paper proposes a neural network-based PID controller for the boost converter. The well-known back prorogation neural network algorithm is used with PID structure to design a controller for the boost converter. The study is carried out with the help of MATLAB/Simulink software to show the test results. The simulations’ outcome shows the proposed controller’s efficacy when used with solar PV systems.","PeriodicalId":182428,"journal":{"name":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Design of PID Controller using Artificial Neural Network for Step-up Power Converter in Photovoltaic Systems\",\"authors\":\"S. Gupta, J. K. Mohanta\",\"doi\":\"10.1109/PIECON56912.2023.10085911\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The most attractive renewable energy resource that provides clean electricity via solar PV panels is solar irradiation received from the Sun. Solar energy is available mainly during the daytime, but solar photovoltaic (PV) panels can produce maximum power due to low efficiency. Hence, maximum power point tracking (MPPT) methods are used with solar PV systems. The interface required between solar PV panels and the load is a DC-DC converter, a power electronics device. This paper proposes a neural network-based PID controller for the boost converter. The well-known back prorogation neural network algorithm is used with PID structure to design a controller for the boost converter. The study is carried out with the help of MATLAB/Simulink software to show the test results. The simulations’ outcome shows the proposed controller’s efficacy when used with solar PV systems.\",\"PeriodicalId\":182428,\"journal\":{\"name\":\"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PIECON56912.2023.10085911\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIECON56912.2023.10085911","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

通过太阳能光伏板提供清洁电力的最具吸引力的可再生能源是来自太阳的太阳辐射。太阳能主要在白天可用,但太阳能光伏(PV)板由于效率低,可以产生最大的功率。因此,最大功率点跟踪(MPPT)方法被用于太阳能光伏系统。太阳能光伏板和负载之间所需的接口是一个DC-DC转换器,一个电力电子设备。本文提出了一种基于神经网络的升压变换器PID控制器。将著名的逆延神经网络算法与PID结构相结合,设计升压变换器的控制器。在MATLAB/Simulink软件的帮助下进行了研究,展示了测试结果。仿真结果表明了该控制器在太阳能光伏系统中的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of PID Controller using Artificial Neural Network for Step-up Power Converter in Photovoltaic Systems
The most attractive renewable energy resource that provides clean electricity via solar PV panels is solar irradiation received from the Sun. Solar energy is available mainly during the daytime, but solar photovoltaic (PV) panels can produce maximum power due to low efficiency. Hence, maximum power point tracking (MPPT) methods are used with solar PV systems. The interface required between solar PV panels and the load is a DC-DC converter, a power electronics device. This paper proposes a neural network-based PID controller for the boost converter. The well-known back prorogation neural network algorithm is used with PID structure to design a controller for the boost converter. The study is carried out with the help of MATLAB/Simulink software to show the test results. The simulations’ outcome shows the proposed controller’s efficacy when used with solar PV systems.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信