(320e) Optimal Flexible Power-to-Methanol Processes: With or without Storage?

Methanol is an important platform chemical widely used for the synthesis of several products, e.g., formaldehyde and plastics, and has high potential as an alternative or drop-in fuel [1]. Its production is responsible for about 10 % of the CO₂ emissions of the chemical sector [1], which motivates the investigation of sustainable production pathways. A promising alternative is represented by electricity-based methanol (Power-to-Methanol), synthesized from captured carbon dioxide and green hydrogen from electrolysis [2-4]. In this pathway, the high electricity demand for hydrogen production via electrolysis has a high impact on the methanol production cost, thus motivating flexible operation when considering time-variable electricity cost or renewables availability. Additionally, storage technologies, e.g., hydrogen storage, could contribute to addressing these time-variable inputs [5-6]. However, it is unclear if each unit of the Power-to-Methanol plant should be operated flexibly, and which storage technology should be considered to minimize the production cost.

To answer these questions, we implement an algebraic model of a Power-to-Methanol plant composed of the low-temperature water electrolysis, hydrogen compression, and methanol synthesis units, with battery and hydrogen storage in GAMS. We then use the optimizer BARON [7] to solve a combined design and scheduling optimization MINLP problem, which provides the optimal size of the units of the plant when simultaneously considering their optimal operational schedule. Quasi-stationarity at the operating points is assumed due to the relatively high load-change rates of the plant units [2,8] and the hourly time discretization that is considered for the scheduling in the investigated electricity cost and availability scenarios. The combined design and scheduling optimization is performed for a grid-connected and a stand-alone Power-to-Methanol case study by minimizing the annualized cost of methanol.

The optimization results show that flexible operation of both the electrolysis and the methanol synthesis units always reduces the production cost of methanol. Nevertheless, the relative cost reduction between the flexible and non-flexible Power-to-Methanol plants is highly scenario-dependent. Storage, especially hydrogen storage, significantly reduces the methanol production cost in the grid-connected case study when the electricity price is high and highly fluctuating, while the investment cost for storage is not repaid by the savings in the operating costs when the electricity price profile has low fluctuations. In the stand-alone case study, optimally sized storages grant continuous operation of the Power-to-Methanol plant even in case of renewable generation shortage. Also, flexible operation of the whole Power-to-Methanol plant leads to a larger optimal size of the plant units while reducing the need for storage, thus increasing the utilization of the electricity generated by the renewable power plant and the amount of produced methanol.

Acknowledgments

The authors gratefully acknowledge the financial support by the German Federal Ministry of Education and Research (BMBF) within the H2Giga project DERIEL (grant number 03HY122D).

References

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