利用人工神经网络和物联网实现太阳能系统最大功率点跟踪的自动化

K. Sujatha, R. S. Ponmagal, T. Godhavari, K. Kumar
{"title":"利用人工神经网络和物联网实现太阳能系统最大功率点跟踪的自动化","authors":"K. Sujatha, R. S. Ponmagal, T. Godhavari, K. Kumar","doi":"10.1109/UPCON.2016.7894625","DOIUrl":null,"url":null,"abstract":"The importance of this project focuses on the efficiency of the solar panel which can be increased by incorporating indigenous solar tracking systems in order to increase solar panel efficiency. However, implementation of this technology requires accurate control which is crucial to develop a refined tracking system. In this work, a solar tracking system using Artificial Neural Network (ANN) based Image Processing (IPT) Techniques to estimate the azimuth angle of the sun from Global Positioning System (GPS) and image sensor is proposed here. The features extracted using IP algorithms with a decision making AI process is adopted to differentiate whether the present weather condition is sunny or cloudy. With reference to the results obtained, the solar tracking system establishes the usage of astronomical calculations approximately. The proposed hi-tech arrangement is evaluated and validated through experimentation results which are made available on the cloud service for coordination.","PeriodicalId":151809,"journal":{"name":"2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering (UPCON)","volume":"161 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Automation of solar system for Maximum Power Point tracking using Artificial Neural Networks and IoT\",\"authors\":\"K. Sujatha, R. S. Ponmagal, T. Godhavari, K. Kumar\",\"doi\":\"10.1109/UPCON.2016.7894625\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The importance of this project focuses on the efficiency of the solar panel which can be increased by incorporating indigenous solar tracking systems in order to increase solar panel efficiency. However, implementation of this technology requires accurate control which is crucial to develop a refined tracking system. In this work, a solar tracking system using Artificial Neural Network (ANN) based Image Processing (IPT) Techniques to estimate the azimuth angle of the sun from Global Positioning System (GPS) and image sensor is proposed here. The features extracted using IP algorithms with a decision making AI process is adopted to differentiate whether the present weather condition is sunny or cloudy. With reference to the results obtained, the solar tracking system establishes the usage of astronomical calculations approximately. The proposed hi-tech arrangement is evaluated and validated through experimentation results which are made available on the cloud service for coordination.\",\"PeriodicalId\":151809,\"journal\":{\"name\":\"2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering (UPCON)\",\"volume\":\"161 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering (UPCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UPCON.2016.7894625\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering (UPCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UPCON.2016.7894625","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

摘要

这个项目的重要性集中在太阳能电池板的效率上,可以通过结合本土的太阳能跟踪系统来提高太阳能电池板的效率。然而,这项技术的实施需要精确的控制,这对于开发一个完善的跟踪系统至关重要。本文提出了一种利用基于人工神经网络(ANN)的图像处理(IPT)技术从全球定位系统(GPS)和图像传感器中估计太阳方位角的太阳跟踪系统。采用IP算法提取的特征,结合人工智能决策过程,区分当前天气状况是晴天还是多云。根据所得到的结果,太阳跟踪系统近似地确立了天文计算的用途。通过实验结果对提出的高科技安排进行了评估和验证,实验结果在云服务上提供,以便进行协调。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automation of solar system for Maximum Power Point tracking using Artificial Neural Networks and IoT
The importance of this project focuses on the efficiency of the solar panel which can be increased by incorporating indigenous solar tracking systems in order to increase solar panel efficiency. However, implementation of this technology requires accurate control which is crucial to develop a refined tracking system. In this work, a solar tracking system using Artificial Neural Network (ANN) based Image Processing (IPT) Techniques to estimate the azimuth angle of the sun from Global Positioning System (GPS) and image sensor is proposed here. The features extracted using IP algorithms with a decision making AI process is adopted to differentiate whether the present weather condition is sunny or cloudy. With reference to the results obtained, the solar tracking system establishes the usage of astronomical calculations approximately. The proposed hi-tech arrangement is evaluated and validated through experimentation results which are made available on the cloud service for coordination.
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:604180095
Book学术官方微信