人工神经网络辅助下的带余热回收的甲烷供气DIR-SOFC系统多目标优化

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Unsal Aybek, Lutfu Namli, Mustafa Ozbey, Bekir Dogan
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引用次数: 0

摘要

本研究的主要目的是提高固体氧化物燃料电池系统的性能。为此,在工程方程求解程序中,设计了具有余热回收的直接内重整(DIR)甲烷燃料电池系统的数学模型。我们使用遗传算法和TOPSIS技术优化了固体氧化物燃料电池的性能,同时考虑了能源、功率和环境分析。在matlab程序中设计了一个与Levenberg-Marquardt训练函数一起工作的人工神经网络,以创建将应用TOPSIS方法的决策矩阵。根据功率优化计算,系统净功率为786 kW。在火用优化中,其火用效率为57.6%。在环境优化方面,确定了环境影响为330.6 kgCO2/MWh。根据多目标优化结果,固体氧化物燃料电池系统的能效、净功率和环境影响分别为504.1 kW、40.08%和475.4 kgCO2/MWh。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial neural network assisted multi-objective optimization of a methane-fed DIR-SOFC system with waste heat recovery
The main purpose of this study is to enhance the performance of solid oxide fuel cell systems. For this purpose, a mathematical model of a direct internal reforming (DIR) methane-fed solid oxide fuel cell system with waste heat recovery was designed in the engineering equation solver program. We optimised the performance of the solid oxide fuel cell using a genetic algorithm and TOPSIS technique considering exergy, power, and environmental analyzes. An ANN working with the Levenberg-Marquardt training function was designed in the MATLprogram to create the decision matrix to which the TOPSIS method will be applied. According to the power optimization, 786 kW net power was obtained from the system. In exergetic optimization, the exergy efficiency was found to be 57.6%. In environmental optimization, the environmental impact was determined as 330.6 kgCO2/MWh. According to the multi-objective optimization results, the exergy efficiency, the net power of the solid oxide fuel cell system, and the environmental impact were 504.1 kW, 40.08%, and 475.4 kgCO2/MWh.
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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