Renewable Energy System Using Weather Data for Optimal Scheduling*

Duy T. Nguyen, D. Nguyễn
{"title":"Renewable Energy System Using Weather Data for Optimal Scheduling*","authors":"Duy T. Nguyen, D. Nguyễn","doi":"10.1109/GTSD.2018.8595622","DOIUrl":null,"url":null,"abstract":"There is no doubt that renewable energy (RE) is now playing a key role in our daily life and has become more popular thanks to many advantages such as environment friendly, unlimited sources and so on, variable of applications. Obviously, the only one obstacle we must face is the dependence upon weather conditions which have been, so far, the unpredictable variants of most RE systems. Hence, in this paper, we propose a new algorithm using weather forecast and historical weather data in order to optimize performance of RE systems. Basically, this algorithm is not only making full use of weather data base but also helping us decide whether to discharge the load or have it operates on high performance at least in the next three hours [1]. We have already embedded it into our RE system combining with Darius wind turbine and photovoltaic (PV) system, the result is showed below.","PeriodicalId":344653,"journal":{"name":"2018 4th International Conference on Green Technology and Sustainable Development (GTSD)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 4th International Conference on Green Technology and Sustainable Development (GTSD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GTSD.2018.8595622","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

There is no doubt that renewable energy (RE) is now playing a key role in our daily life and has become more popular thanks to many advantages such as environment friendly, unlimited sources and so on, variable of applications. Obviously, the only one obstacle we must face is the dependence upon weather conditions which have been, so far, the unpredictable variants of most RE systems. Hence, in this paper, we propose a new algorithm using weather forecast and historical weather data in order to optimize performance of RE systems. Basically, this algorithm is not only making full use of weather data base but also helping us decide whether to discharge the load or have it operates on high performance at least in the next three hours [1]. We have already embedded it into our RE system combining with Darius wind turbine and photovoltaic (PV) system, the result is showed below.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
利用天气数据优化调度的可再生能源系统*
毫无疑问,可再生能源(RE)现在在我们的日常生活中发挥着关键作用,由于许多优点,如环境友好,资源无限量等,应用的多样性,它已经变得越来越受欢迎。显然,我们必须面对的唯一障碍是对天气条件的依赖,到目前为止,大多数RE系统都是不可预测的变化。因此,在本文中,我们提出了一种利用天气预报和历史天气数据来优化RE系统性能的新算法。基本上,该算法不仅充分利用了气象数据库,而且可以帮助我们决定是卸载负载还是至少在未来三小时内保持高性能运行[1]。我们已经将其嵌入到我们的可再生能源系统中,并与Darius风力涡轮机和光伏(PV)系统相结合,结果如下所示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Study on the Applicability of Influence Coefficient Method Combined with Vector Analysis in Dynamic Balancing Rigid Rotor Using Flexible Supports Program for Designing Planar Cam Mechanisms" Enantio-selective Crystallization via a Kinetic and Thermodynamic Hybrid Process A Study on Change of the Shape and Size of the Minichannel Evaporators to Enhance the Cooling Capacity of the CO&underscore;2 Air Conditioning Cycle Comparative Structural and Non-structural Properties of Ultra High-performance Steel-fiber-reinforced Concretes and High-Performance Steel-fiber-reinforced Concretes*
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1