Design optimization of a thermal-storage-based electricity storage for nanogrid applications

M. Caliano, G. Graditi, A. Pontecorvo, M. Valenti
{"title":"Design optimization of a thermal-storage-based electricity storage for nanogrid applications","authors":"M. Caliano, G. Graditi, A. Pontecorvo, M. Valenti","doi":"10.23919/AEIT53387.2021.9627022","DOIUrl":null,"url":null,"abstract":"Thermal Energy Storage (TES) systems have shown a high potential for integrating intermittent renewable energy sources into energy systems by assisting with electrification of thermal loads. The aim of this paper is to develop a tool for the simulation and optimal design of a TES-based electricity storage of electricity produced by a photovoltaic system for nanogrid applications. The tool adopts a multi-objective approach with a view to reducing the costs associated with the nanogrid and saving primary energy, while satisfying the end-user multi-energy demand. The simulation/optimization tool is developed by coupling TRNSYS and Matlab softwares with the aim to find the design and operation strategies solutions on the Pareto frontier, and the problem is solved by using genetic algorithms. In the numerical test case, a single-family house of 200 m2 located in Italy is considered as residential end-user, and the winter and summer scenarios are considered for simulations. Results show the functionality of the tool in simulating and optimizing more or less complex energy systems and its effectiveness for providing good balancing solutions for end-users based on economic and energetic priorities.","PeriodicalId":138886,"journal":{"name":"2021 AEIT International Annual Conference (AEIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 AEIT International Annual Conference (AEIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/AEIT53387.2021.9627022","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

Thermal Energy Storage (TES) systems have shown a high potential for integrating intermittent renewable energy sources into energy systems by assisting with electrification of thermal loads. The aim of this paper is to develop a tool for the simulation and optimal design of a TES-based electricity storage of electricity produced by a photovoltaic system for nanogrid applications. The tool adopts a multi-objective approach with a view to reducing the costs associated with the nanogrid and saving primary energy, while satisfying the end-user multi-energy demand. The simulation/optimization tool is developed by coupling TRNSYS and Matlab softwares with the aim to find the design and operation strategies solutions on the Pareto frontier, and the problem is solved by using genetic algorithms. In the numerical test case, a single-family house of 200 m2 located in Italy is considered as residential end-user, and the winter and summer scenarios are considered for simulations. Results show the functionality of the tool in simulating and optimizing more or less complex energy systems and its effectiveness for providing good balancing solutions for end-users based on economic and energetic priorities.
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
纳米电网应用中基于热存储的电力存储的设计优化
热能储存(TES)系统通过协助热负荷电气化,显示出将间歇性可再生能源整合到能源系统中的巨大潜力。本文的目的是开发一种工具,用于模拟和优化设计基于tes的纳米电网应用光伏系统产生的电力存储。该工具采用多目标方法,旨在降低与纳米电网相关的成本,节约一次能源,同时满足最终用户的多种能源需求。结合TRNSYS和Matlab软件开发仿真/优化工具,寻找Pareto边界上的设计和运行策略解,并采用遗传算法求解。在数值测试案例中,将位于意大利的200平方米的单户住宅作为住宅最终用户,并考虑冬季和夏季场景进行模拟。结果表明,该工具在模拟和优化或多或少复杂的能源系统方面的功能,以及为最终用户提供基于经济和能源优先级的良好平衡解决方案的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Wind power forecasting models for very short-term operation of power systems MOSFETs Selection in Front-end Active Bridge Rectifier On Comparing Regressive and Artificial Neural Network Methods for Power System Forecast FExWaveS application for voltage dips origin assessment: optimization of the tool in views of its integration into the QuEEN monitoring system OPF model with dynamic security constraints: a state of the art review
×
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