提高发电量:采用综合分析和人工智能优化标准的新型氢基方案

Energy Storage Pub Date : 2024-08-22 DOI:10.1002/est2.70013
Vahid Mohammadzadeh, Zoheir Saboohi, Fathollah Ommi, Ehsan Gholamian
{"title":"提高发电量:采用综合分析和人工智能优化标准的新型氢基方案","authors":"Vahid Mohammadzadeh,&nbsp;Zoheir Saboohi,&nbsp;Fathollah Ommi,&nbsp;Ehsan Gholamian","doi":"10.1002/est2.70013","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>Despite being a cutting-edge technology, the proton exchange membrane fuel cell (PEMFC) generates a lot of heat as it works, which makes it wasteful with energy. In order to enhance energy efficiency via waste heat recovery, we provide and analyze a novel integrated energy system that utilizes PEMFC and ORC technology. There are a lot of ways to put the waste heat from fuel cells (FCs) to good use, but the most efficient one is the organic Rankine cycle (ORC) with the right working fluid. This research aims to find the optimal way to use the waste heat of the FC by testing several working fluids. The optimal solution is derived using a genetic algorithm by monitoring the objective functions that characterize the system's overall performance as they vary across different system parameters. The results show that the proposed efficient integration achieves high energy and exergy efficiency levels and achieves rates of total cost and environmental impact that are within acceptable limits. Since the fuel usage element's content significantly affects the system indicators in several ways, the results also demonstrate that it is quite relevant. Since the exergo-environmental metric and the exergy efficiency meter are always moving in different directions, choosing a design condition that meets several requirements is crucial. According to the results, fuel cells had the highest irreversibility rate at 12.2, making them the most energy-conserving piece of machinery.</p>\n </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhancing Power Production: A Novel Hydrogen-Based Scheme With Comprehensive Analysis and AI-Optimized Criteria\",\"authors\":\"Vahid Mohammadzadeh,&nbsp;Zoheir Saboohi,&nbsp;Fathollah Ommi,&nbsp;Ehsan Gholamian\",\"doi\":\"10.1002/est2.70013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>Despite being a cutting-edge technology, the proton exchange membrane fuel cell (PEMFC) generates a lot of heat as it works, which makes it wasteful with energy. In order to enhance energy efficiency via waste heat recovery, we provide and analyze a novel integrated energy system that utilizes PEMFC and ORC technology. There are a lot of ways to put the waste heat from fuel cells (FCs) to good use, but the most efficient one is the organic Rankine cycle (ORC) with the right working fluid. This research aims to find the optimal way to use the waste heat of the FC by testing several working fluids. The optimal solution is derived using a genetic algorithm by monitoring the objective functions that characterize the system's overall performance as they vary across different system parameters. The results show that the proposed efficient integration achieves high energy and exergy efficiency levels and achieves rates of total cost and environmental impact that are within acceptable limits. Since the fuel usage element's content significantly affects the system indicators in several ways, the results also demonstrate that it is quite relevant. Since the exergo-environmental metric and the exergy efficiency meter are always moving in different directions, choosing a design condition that meets several requirements is crucial. According to the results, fuel cells had the highest irreversibility rate at 12.2, making them the most energy-conserving piece of machinery.</p>\\n </div>\",\"PeriodicalId\":11765,\"journal\":{\"name\":\"Energy Storage\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Storage\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/est2.70013\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Storage","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/est2.70013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

尽管质子交换膜燃料电池(PEMFC)是一项尖端技术,但它在工作时会产生大量热量,从而造成能源浪费。为了通过余热回收提高能源效率,我们提供并分析了一种利用 PEMFC 和 ORC 技术的新型集成能源系统。将燃料电池(FC)产生的废热加以充分利用的方法有很多,但最有效的方法是采用合适工作流体的有机朗肯循环(ORC)。这项研究旨在通过测试几种工作流体,找到利用燃料电池余热的最佳方法。通过监测表征系统整体性能的目标函数在不同系统参数下的变化情况,利用遗传算法得出最佳解决方案。结果表明,所建议的高效集成实现了较高的能效和放能效水平,并将总成本和环境影响控制在可接受的范围内。由于燃料使用要素的内容会在多个方面对系统指标产生重大影响,因此结果也证明了它的相关性。由于能量环境指标和能量效率指标总是朝着不同的方向发展,因此选择一个满足多项要求的设计条件至关重要。结果显示,燃料电池的不可逆率最高,为 12.2,是最节能的设备。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Enhancing Power Production: A Novel Hydrogen-Based Scheme With Comprehensive Analysis and AI-Optimized Criteria

Despite being a cutting-edge technology, the proton exchange membrane fuel cell (PEMFC) generates a lot of heat as it works, which makes it wasteful with energy. In order to enhance energy efficiency via waste heat recovery, we provide and analyze a novel integrated energy system that utilizes PEMFC and ORC technology. There are a lot of ways to put the waste heat from fuel cells (FCs) to good use, but the most efficient one is the organic Rankine cycle (ORC) with the right working fluid. This research aims to find the optimal way to use the waste heat of the FC by testing several working fluids. The optimal solution is derived using a genetic algorithm by monitoring the objective functions that characterize the system's overall performance as they vary across different system parameters. The results show that the proposed efficient integration achieves high energy and exergy efficiency levels and achieves rates of total cost and environmental impact that are within acceptable limits. Since the fuel usage element's content significantly affects the system indicators in several ways, the results also demonstrate that it is quite relevant. Since the exergo-environmental metric and the exergy efficiency meter are always moving in different directions, choosing a design condition that meets several requirements is crucial. According to the results, fuel cells had the highest irreversibility rate at 12.2, making them the most energy-conserving piece of machinery.

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
CiteScore
2.90
自引率
0.00%
发文量
0
期刊最新文献
An Innovative Energy Storage System Based on Phase Change Material and Solar Energy Integrated With an Air Handling Unit to Produce Heating and Cooling Performance Analysis of a Renewable-Powered Multi-Gas Floating Storage and Regasification Facility for Ammonia Vessels With Reconversion to Hydrogen The Solid-State Battery Applicational Technology: Material Characteristics and Charge–Discharge Mechanisms of Iron Chloride Electrodes Hydrogen Storage Studies of Nanocomposites Derived From O-Ethyl-S-((5-Methoxy-1H-Benzo[d]Imidazol-2-Yl)Carbonothioate (OESMBIC) With ZnO and TiO2 Nanoparticles Performance Enhancement of Solar Still Couples With Solar Water Heater by Using Different PCM's and Nanoparticle Combinations
×
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