# Techno-Economic Potential of Plasma-Based CO\({}_{2}\) Splitting in Power-to-Liquid Plants
## 4 Results
### Sensitivity Analysis  
In addition to the parameter variations within the scope of the scenarios shown, the parameters were varied around the scenario parameters to see the influence on the technoeconomic results. Special focus is set on the component parameters of the plasma process. In addition, it is to be found out how large the influence of the GDE is. In the scenarios, a significant reduction in area and thus costs can already be observed by optimizing the characteristic maps. In the cases shown in Figure 11, some parameters of the plasma reactor and electrolysis are varied around the scenario values. The percentage deviations of the \(NPC\) and the process efficiency \(\eta_{process}\) from the scenario value are shown. It can be clearly seen that \begin{table}
\begin{tabular}{c c c c} \hline \hline
**CAPEX in Mio EUR** & **S2018/20** & **S2030** & **S2050** \\ \hline \(\Sigma\) & **1350** & **650** & **560** \\ GDE & 970 & 350 & 230 \\ DBD & 70 & 50 & 60 \\ EL & 80 & 60 & 70 \\ FTS & 150 & 100 & 100 \\ Others (e.g., Comp, & 80 & 90 & 100 \\ HEX) & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 8: CAPEX of the different scenarios S2018/20, S2030, and S2050 (DBD-Plant) consisting of investments for the gas diffusion electrode (GDE), dielectric barrier discharge plasma reactor (DBD), electrolysis system (EL), Fischer–Tropsch synthesis reactor (FTS), and other components, e.g., compressors (Comp) and heat exchangers (HEX). Figure 9: Distribution of net production costs (NPC) of scenario 2018/20 by dielectric barrier discharge (DBD)-plant. at low scenario values, i.e., at the plasma-specific values, an increase or decrease has a significantly greater influence on the result. From the percentage deviations of \(NPC\) and process efficiency shown in the figure, it is evident that the variation of plasma conversion and efficiency by the values chosen in the scenarios exert significant influence. In contrast, further optimization of electrolysis does not result in a large change. Figure 11: Sensitivity analysis of the plasma reactor and electrolysis parameter. The dotted line describes the process efficiency, the solid line the net production costs (\(NPC\)). Figure 10: Net production costs (NPC) of scenarios for dielectric barrier discharge (DBD)-plant and gliding arc (GA)-plant. Figure 12 shows the power distribution among plasma generation, electrolysis, GDE, and all other components, such as compressors and pumps. The power ratio \(\left(P_{Plasm}+P_{Electolysis}\right)/P_{tot}\) decreases significantly with higher efficiencies in syngas generation. It results from more gases being transported by the GDE and the compressors, etc. This can be used to justify the decreasing slope of the process efficiency at higher component efficiencies. As a conclusion from this observation, it can be found that for high-efficiency electrolysis and plasma processes, holistic optimization is necessary. Better compressor efficiencies and more energy-efficient GDE must be investigated to get the maximum potential out of the process. The process can also be optimized by adjusting FTS parameters. By changing the process by adjusting temperature and catalysts, the chain growth probability can be influenced. If higher values can be achieved there, the product yield increases significantly. However, product preparation becomes more difficult due to the higher proportion of waves. Another optimization option is to increase the CO turnover of the FTS. If this is increased by 5% in the different scenarios, the \(NPC\) will decrease by EUR 0.2/L at S2018/20 and by EUR 0.1/L at S2050. However, the increase in revenue allows the high recycling rate around the FTS reactor to be eliminated. This also reduces the energy cost of compressing residual gas and the capital cost. As part of the sensitivity analysis, the characteristic maps of the GDE were also varied.