Conceptual Design of Digital Twin for Bio-methanol Production from Microalgae
Moretta, Federico
Fedeli, Matteo
Manenti, Flavio
Bozzano, Giulia Luisa

How to Cite

Moretta F., Fedeli M., Manenti F., Bozzano G.L., 2022, Conceptual Design of Digital Twin for Bio-methanol Production from Microalgae, Chemical Engineering Transactions, 92, 253-258.


In the last decades, microalgae have gained a lot of interest in the energy and chemical industry thanks to their higher biofuel productivity potential rather than other land plants. To better exploit their green nature and renewable power, anaerobic digestion (AD) fits perfectly for the scope. AD is a metabolic process that generates a methane-rich gas, the biogas, which can then be used for clean electricity and chemicals production. High interest has arisen in the field of AD in industrial practice, and a lot of experiments were done to produce biogas from different types of feedstocks. In this manner, microalgae represent a promising opportunity to produce biogas from renewable and self-sustainable organisms. Biogas is mostly used to produce electrical energy and heat through cogeneration cycles or is upgraded to biomethane through the removal of CO2 and impurities, reaching a CH4 purity above 95-97% vol. On the other hand, an interesting perspective of biogas exploitation is its conversion in biofuels such as methanol or dimethyl-ether. This new concept of bio-refining lays the ground for two aspects: The economical valorisation of the biomass with a more valuable product as bio-methanol and the conversion of biogas to biofuel to fix part of the carbon in a chemical molecule, avoiding the re-emission in the atmosphere of CO2. The scope of this work is to present and technically analyse a conceptual design of a circular bio-refinery based on microalgae biomass feedstock with the final output of methanol production. Biogas production from microalgae is modelled with PythonTM (v3.9) while process simulations are computed using state of the art industrial simulation packages like Aspen HYSIS® v11. Interesting factors to analyse are carbon emission, the field of use for functional production, the global process yield and preliminary feasibility analysis.