Renewable methanol production: Optimization-based design, scheduling and waste-heat utilization with the FluxMax approach

Tibor Svitnič and Kai Sundmacher

Applied Energy, 2022, vol. 326, issue C, No S0306261922012740

Abstract: Renewable methanol production is an important part of the energy transition of the chemical industry from fossil to renewable resources. This work presents the design of a methanol production from renewable energy only, using an extended optimization-based FluxMax approach. This linear programming design approach considers waste-heat utilization in parallel with the solution of the design and scheduling problems, allowing to identify energy efficient process configurations. The subsystems of the methanol production (energy generation, utility, storage and chemical processes) were represented with an extensive process network. Solar and wind energy generation processes were modeled based on yearly renewable resource data with an hourly resolution for the chosen location of Port Arthur, Texas, USA. The most cost-effective design had a levelized cost of methanol of 1392 $/t for reference year 2019 and expected future costs of 799 $/t (year 2030). In this design, the process configuration included parabolic troughs, thermal energy storage, a steam turbine and a heat pump operating in synchrony with a direct air capture process and a solid-oxide electrolyzer. By comparing several designs differing in their initial process networks, we analyzed the influences of: waste-heat utilization, complementarity of the generation processes, solar-tracking models and the flexibility of the methanol process. This analysis demonstrated the importance of considering a large process network spanning across all subsystems for the design of a cost-effective renewable methanol production.

Keywords: Power-to-methanol; Energy storage; Heat integration; Process flexibility; Conceptual design (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)

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DOI: 10.1016/j.apenergy.2022.120017

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