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<p>Glycerol carbonate (GC) can be produced from glycerol (GL), a low-value byproduct in the biodiesel industry. In this work, continuous processes of GC production via transesterification from crude GL and diethyl carbonate (DEC) were developed using Aspen Plus. Two cases were considered, and their process performances were compared. In Case I, a conventional design consisted of a continuously stirred tank reactor for the reaction section and a distillation column for the purification section. In Case II, a process intensification design consisted of a reactive distillation column that could accommodate both reaction and purification within a single column. In both cases, the process optimizations were carried out by connecting the process models in Aspen Plus to MATLAB, using the Genetic Algorithm as the optimizer. The results showed that Case II was superior to Case I in terms of energy utilization, CO<sub>2</sub> emissions, and economics with the specific energy consumption of 1.92 kWh/kg of diethyl carbonate, % internal rate of return of 274, payback period of 1.44 years, and CO<sub>2</sub> emissions of 0.26 kg CO<sub>2</sub>/kg DEC. Lastly, the proposed process in Case II was compared with the GC production using dimethyl carbonate (DMC). It was found that using DEC was superior to DMC due to easier separation and glycidol avoidance.</p>

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Comparative study of conventional and process intensification by reactive distillation designs for glycerol carbonate production from glycerol and diethyl carbonate

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年1月12日

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  • Bushra Chalermthai,
  • Chayanin Sriharuethai,
  • Bradley D. Olsen,
  • Kanokwan Ngaosuwan,
  • Apinan Soottitantawat,
  • Suttichai Assabumrungrat,
  • Pongtorn Charoensuppanimit

摘要

Glycerol carbonate (GC) can be produced from glycerol (GL), a low-value byproduct in the biodiesel industry. In this work, continuous processes of GC production via transesterification from crude GL and diethyl carbonate (DEC) were developed using Aspen Plus. Two cases were considered, and their process performances were compared. In Case I, a conventional design consisted of a continuously stirred tank reactor for the reaction section and a distillation column for the purification section. In Case II, a process intensification design consisted of a reactive distillation column that could accommodate both reaction and purification within a single column. In both cases, the process optimizations were carried out by connecting the process models in Aspen Plus to MATLAB, using the Genetic Algorithm as the optimizer. The results showed that Case II was superior to Case I in terms of energy utilization, CO2 emissions, and economics with the specific energy consumption of 1.92 kWh/kg of diethyl carbonate, % internal rate of return of 274, payback period of 1.44 years, and CO2 emissions of 0.26 kg CO2/kg DEC. Lastly, the proposed process in Case II was compared with the GC production using dimethyl carbonate (DMC). It was found that using DEC was superior to DMC due to easier separation and glycidol avoidance.