间歇式生物反应器中沼气生产的建模与优化

Q4 Energy
Tina Kegl, E. Torres-Jiménez
{"title":"间歇式生物反应器中沼气生产的建模与优化","authors":"Tina Kegl, E. Torres-Jiménez","doi":"10.24084/repqj21.319","DOIUrl":null,"url":null,"abstract":"Ever increasing demands for renewable energy sources are the driving force for the development of waste management technologies such as anaerobic digestion (AD) technology. For AD process understanding and optimization the numerical simulations provide a useful tool. Therefore, in this work, the main attention is focused on the development of an efficient and stable optimization approach. The optimization procedure is coupled with a suitable mechanistically inspired selfdeveloped BioModel. For BioModel calibration, a special procedure was developed which incorporates the used BioModel, a sensitivity analysis, and a gradient-based optimization algorithm. The results of numerical simulation, obtained by the AD of various animal manures in a batch lab-scale bioreactor, confirm the reliability of BioModel and the efficiency of the presented calibration procedure. Furthermore, the results of AD process optimization show that the biogas quantity and quality as well as energy used up for bioreactor heating can be improved essentially when amount of added bacteria, temperature and pH values are optimized properly.","PeriodicalId":21076,"journal":{"name":"Renewable Energy and Power Quality Journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling and optimization of biogas production in a batch bioreactor\",\"authors\":\"Tina Kegl, E. Torres-Jiménez\",\"doi\":\"10.24084/repqj21.319\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ever increasing demands for renewable energy sources are the driving force for the development of waste management technologies such as anaerobic digestion (AD) technology. For AD process understanding and optimization the numerical simulations provide a useful tool. Therefore, in this work, the main attention is focused on the development of an efficient and stable optimization approach. The optimization procedure is coupled with a suitable mechanistically inspired selfdeveloped BioModel. For BioModel calibration, a special procedure was developed which incorporates the used BioModel, a sensitivity analysis, and a gradient-based optimization algorithm. The results of numerical simulation, obtained by the AD of various animal manures in a batch lab-scale bioreactor, confirm the reliability of BioModel and the efficiency of the presented calibration procedure. Furthermore, the results of AD process optimization show that the biogas quantity and quality as well as energy used up for bioreactor heating can be improved essentially when amount of added bacteria, temperature and pH values are optimized properly.\",\"PeriodicalId\":21076,\"journal\":{\"name\":\"Renewable Energy and Power Quality Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Renewable Energy and Power Quality Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24084/repqj21.319\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Energy\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Renewable Energy and Power Quality Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24084/repqj21.319","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Energy","Score":null,"Total":0}
引用次数: 0

摘要

对可再生能源日益增长的需求推动了厌氧消化(AD)技术等废物管理技术的发展。数值模拟为AD工艺的理解和优化提供了有用的工具。因此,在本工作中,主要关注的是开发一种高效、稳定的优化方法。优化过程与合适的机械启发自行开发的生物模型相结合。对于生物模型的校准,开发了一个特殊的程序,该程序结合了使用的生物模型,灵敏度分析和基于梯度的优化算法。通过在实验室规模的间歇式生物反应器中对各种动物粪便进行AD的数值模拟,验证了biommodel的可靠性和所提出的校准程序的有效性。此外,AD工艺优化结果表明,适当优化细菌添加量、温度和pH值,可以显著提高生物反应器的沼气数量和质量,以及生物反应器加热消耗的能量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling and optimization of biogas production in a batch bioreactor
Ever increasing demands for renewable energy sources are the driving force for the development of waste management technologies such as anaerobic digestion (AD) technology. For AD process understanding and optimization the numerical simulations provide a useful tool. Therefore, in this work, the main attention is focused on the development of an efficient and stable optimization approach. The optimization procedure is coupled with a suitable mechanistically inspired selfdeveloped BioModel. For BioModel calibration, a special procedure was developed which incorporates the used BioModel, a sensitivity analysis, and a gradient-based optimization algorithm. The results of numerical simulation, obtained by the AD of various animal manures in a batch lab-scale bioreactor, confirm the reliability of BioModel and the efficiency of the presented calibration procedure. Furthermore, the results of AD process optimization show that the biogas quantity and quality as well as energy used up for bioreactor heating can be improved essentially when amount of added bacteria, temperature and pH values are optimized properly.
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
Renewable Energy and Power Quality Journal
Renewable Energy and Power Quality Journal Energy-Energy Engineering and Power Technology
CiteScore
0.70
自引率
0.00%
发文量
147
×
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