Radiofrequency Induction Heating for Green Chemicals Manufacture: A Systematic Model of Energy Losses and a Scale-Up Case-Study

IF 4.3 Q2 ENGINEERING, CHEMICAL ACS Engineering Au Pub Date : 2024-07-25 DOI:10.1021/acsengineeringau.4c00009
Jonathan P. P. Noble, Simon J. Bending, Alfred K. Hill
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Abstract

Radiofrequency (RF) induction heating has generated much interest for the abatement of carbon emissions from the chemicals sector as a direct electrification technology. Three challenges have held back its deployment at scale: reactors must be built from nonconductive materials which eliminates steel as a design choice; the viability of scale-up is uncertain; and to date the reported energy efficiency has been too low. This paper presents a model that for the first time makes a comprehensive analysis of energy losses that arise from RF induction heating. The maximum energy efficiency for radio frequency induction heating was previously reported to be 23% with a typical frequency range of 200–400 kHz. The results from the model show that an energy efficiency of 65–82% is achieved at a much lower frequency of 10 kHz and a reactor diameter of 0.2 m. Energy efficiency above 90% with reactor diameters above 1 m in diameter are predicted if higher voltage radio frequency sources can be developed. A new location of the work coil inside of the reactor wall is shown to be highly effective. Losses arising from heating a steel reactor wall in this configuration are shown to be insignificant, even when the wall is immediately adjacent to the work coil. This analysis demonstrates that RF induction heating can be a highly efficient and effective industrial technology for coupling high energy demand chemicals manufacture electricity from zero carbon renewables.

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用于绿色化学品生产的射频感应加热:能量损耗系统模型和规模化案例研究
射频感应加热作为一种直接电气化技术,在减少化工行业碳排放方面引起了广泛关注。但有三项挑战阻碍了该技术的大规模应用:反应器必须由不导电材料制成,这就排除了钢材作为设计选择的可能性;扩大规模的可行性尚不确定;迄今为止,所报告的能源效率太低。本文提出了一个模型,首次对射频感应加热产生的能量损失进行了全面分析。据报道,射频感应加热的最大能效为 23%,典型频率范围为 200-400 kHz。该模型的结果表明,在频率更低的 10 kHz 和反应器直径为 0.2 m 的情况下,能量效率可达 65%-82%。如果能开发出电压更高的射频源,预计反应器直径超过 1 m 的能量效率将超过 90%。工作线圈在反应器壁内的新位置被证明非常有效。在这种配置下加热钢制反应器壁产生的损耗微乎其微,即使反应器壁紧邻工作线圈也是如此。这项分析表明,射频感应加热是一种高效的工业技术,可以将高能耗化学品与零碳可再生能源发电结合起来。
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ACS Engineering Au
ACS Engineering Au 化学工程技术-
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期刊介绍: )ACS Engineering Au is an open access journal that reports significant advances in chemical engineering applied chemistry and energy covering fundamentals processes and products. The journal's broad scope includes experimental theoretical mathematical computational chemical and physical research from academic and industrial settings. Short letters comprehensive articles reviews and perspectives are welcome on topics that include:Fundamental research in such areas as thermodynamics transport phenomena (flow mixing mass & heat transfer) chemical reaction kinetics and engineering catalysis separations interfacial phenomena and materialsProcess design development and intensification (e.g. process technologies for chemicals and materials synthesis and design methods process intensification multiphase reactors scale-up systems analysis process control data correlation schemes modeling machine learning Artificial Intelligence)Product research and development involving chemical and engineering aspects (e.g. catalysts plastics elastomers fibers adhesives coatings paper membranes lubricants ceramics aerosols fluidic devices intensified process equipment)Energy and fuels (e.g. pre-treatment processing and utilization of renewable energy resources; processing and utilization of fuels; properties and structure or molecular composition of both raw fuels and refined products; fuel cells hydrogen batteries; photochemical fuel and energy production; decarbonization; electrification; microwave; cavitation)Measurement techniques computational models and data on thermo-physical thermodynamic and transport properties of materials and phase equilibrium behaviorNew methods models and tools (e.g. real-time data analytics multi-scale models physics informed machine learning models machine learning enhanced physics-based models soft sensors high-performance computing)
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