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Process Configuration Studies of Methanol Production via Carbon Dioxide Hydrogenation: Process Simulation-Based Optimization Using Artificial Neural Networks

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  • Prapatsorn Borisut

    (School of Chemical Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand)

  • Aroonsri Nuchitprasittichai

    (School of Chemical Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand)

Abstract

Methanol production via carbon dioxide (CO 2 ) hydrogenation is a green chemical process, which can reduce CO 2 emission. The operating conditions for minimum methanol production cost of three configurations were investigated in this work. An artificial neural network with Latin hypercube sampling technique was applied to construct model-represented methanol production. Price sensitivity was performed to study the impacts of the raw materials price on methanol production cost. Price sensitivity results showed that the hydrogen price has a large impact on the methanol production cost. In mathematical modeling using feedforward artificial neural networks, four different numbers of nodes were used to train artificial neural networks. The artificial neural network with eight numbers of nodes showed the most suitable configuration, which yielded the lowest percent error between the actual and predicted methanol production cost. The optimization results showed that the recommended process design among the three studied configurations was the process of methanol production with two reactors in series. The minimum methanol production cost obtained from this configuration was $888.85 per ton produced methanol, which was the lowest methanol production cost among all configurations.

Suggested Citation

  • Prapatsorn Borisut & Aroonsri Nuchitprasittichai, 2020. "Process Configuration Studies of Methanol Production via Carbon Dioxide Hydrogenation: Process Simulation-Based Optimization Using Artificial Neural Networks," Energies, MDPI, vol. 13(24), pages 1-13, December.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:24:p:6608-:d:462107
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    References listed on IDEAS

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    1. Pérez-Fortes, Mar & Schöneberger, Jan C. & Boulamanti, Aikaterini & Tzimas, Evangelos, 2016. "Methanol synthesis using captured CO2 as raw material: Techno-economic and environmental assessment," Applied Energy, Elsevier, vol. 161(C), pages 718-732.
    2. Pellegrini, Laura A. & Soave, Giorgio & Gamba, Simone & Langè, Stefano, 2011. "Economic analysis of a combined energy–methanol production plant," Applied Energy, Elsevier, vol. 88(12), pages 4891-4897.
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    Cited by:

    1. Daniel Chuquin-Vasco & Francis Parra & Nelson Chuquin-Vasco & Juan Chuquin-Vasco & Vanesa Lo-Iacono-Ferreira, 2021. "Prediction of Methanol Production in a Carbon Dioxide Hydrogenation Plant Using Neural Networks," Energies, MDPI, vol. 14(13), pages 1-18, July.

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