A Combined Investment and Operational Optimization Approach for Power-to-Methanol Plants

Nouman Akram () and Thomas Kienberger
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Nouman Akram: Chair of Energy Network Technology, Montanuniversitaet Leoben, Franz-Josef Straße 18, A-8700 Leoben, Austria
Thomas Kienberger: Chair of Energy Network Technology, Montanuniversitaet Leoben, Franz-Josef Straße 18, A-8700 Leoben, Austria

Energies, 2024, vol. 17, issue 23, 1-24

Abstract: In the global effort for industrial decarbonization, repurposing closed coal-fired power plants into power-to-methanol (PtM) plants offers a promising pathway to reduce CO 2 emissions while leveraging existing infrastructure. This study introduces a novel combined optimization approach using mixed-integer linear programming (MILP) to simultaneously optimize the investment and operation of a PtM plant, assessing its economic viability. The model incorporates the operational flexibility of proton exchange membrane (PEM) electrolyzers in response to fluctuating electricity prices through a piecewise linear representation of its load–efficiency characteristic curve. A case study of a repurposed coal plant in Austria demonstrates the model’s applicability and practical relevance. The results show that larger electrolyzer capacities, i.e., 434 MW, with flexible part-load operation can significantly reduce methanol production costs, i.e., EUR 0.8/kg, achieving competitiveness under high CO 2 pricing scenarios, i.e., EUR 500/ton. A sensitivity analysis is performed to identify the critical factors influencing production costs. This study concludes that the combined investment and operational optimization approach effectively captures the essential elements of PtM systems, enabling faster, better, and operation-informed investment decisions for innovative technologies to support the ongoing energy transition. These findings indicate that PtM technologies can be a viable solution for asset repurposing, grid stabilization, and decarbonizing hard-to-abate sectors.

Keywords: power-to-methanol; mixed-integer linear programming; PEM; piecewise linearization; oemof.solph (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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