In the present paper new detailed kinetic model for the methanol synthesis from H 2 , CO 2 and/or CO using a Cu/ZnO/Al 2 O 3 catalyst is proposed. In contrast to most established models different active surface species for CO and CO 2 hydrogenation are taken into account. It is shown that changes in the relative amounts of these different surface species, which are related to changes in catalyst morphology, play an important role for the dynamic transient behavior. The model is therefore suitable for evaluating new applications in chemical energy storage, where strongly varying ratios of CO and CO 2 are of relevance. The model parameters were fitted to steady state and dynamic experimental data for varying CO/CO 2 feed ratios using global optimization. Identifiability is studied using the Profile-Likelihood method giving rise to a reduced kinetic model.

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Traditionally, methanol is produced in large amounts from synthesis gas with heterogeneous Cu/ZnO/Al2O3 catalysts under steady state conditions. In this paper, the potential of alternative forced periodic operation modes is studied using numerical optimization. The focus is a well-mixed isothermal reactor with two periodic inputs, namely, CO concentration in the feed and total feed flow rate. Exploiting a detailed kinetic model which also describes the dynamics of the catalyst, a sequential NLP optimization approach is applied to compare optimal steady state solutions with optimal periodic regimes. Periodic solutions are calculated using dynamic optimization with a periodicity constraint. The NLP optimization is embedded in a multi-objective optimization framework to optimize the process with respect to two objective functions and generate the corresponding Pareto fronts. The first objective is the methanol outlet flow rate. The second objective is the methanol yield based on the total carbon in the feed. Additional constraints arising from the complex methanol reaction and the practical limitations are introduced step by step. The results show that significant improvements for both objective functions are possible through periodic forcing of the two inputs considered here.

The analysis of the potential to improve performance of a methanol synthesis reactor through forced periodical operations by Nonlinear Frequency Response method is presented. The methanol synthesis in an isothermal and isobaric lab-scale CSTR is considered. First, the analysis was performed for single input modulations (in Part I), which showed that significant improvements can't be achieved. Here, the study is extended to analysis of simultaneous modulations of two inputs. All possible input combinations (6 cases) are analysed and the optimal forcing parameters, maximizing the time-average methanol production, were determined. For all combinations the improvement is possible, but for some cases it is not significant. The highest improvement is predicted for simultaneous modulation of the inlet partial pressure of CO and the inlet volumetric flow rate. This case, for which it is possible to achieve up to 33.51 % of methanol production, is analysed it detail and optimized using multiobjective optimization.