Stochastic optimization of Power‐to‐Methanol: Production cost sensitivity to process design vs. scheduling

Under time‐varying electricity prices, the production costs of Power‐to‐X processes with intermediate storage can be reduced by simultaneously optimizing the process unit design and size with their scheduling and operation. However, the production cost sensitivity to optimal process design or scheduling is unclear, especially when several scheduling scenarios are considered to address uncertainty. To answer this question, we consider a grid‐connected Power‐to‐Methanol process with intermediate storage and compare: (i) optimal process design under steady‐state operation, (ii) optimal scheduling for several randomly generated process designs, and (iii) combined design and scheduling optimization. We show that optimal scheduling is, on average, more important than optimal design (within the considered variable bounds), since it can mitigate the effects of poor design choices. As a consequence, very different process designs, especially with oversized electrolysis and methanol synthesis units, can lead to similar objective function values when flexible operation is enabled and scheduling is optimized.