# Techno-Economic Potential of Plasma-Based CO\({}_{2}\) Splitting in Power-to-Liquid Plants
## 4 Results
### Scenarios  
The defined scenarios investigated in the analysis differ in the technical parameters of the plasma reactors (conversion and efficiency) and electrolysis (efficiency). Table 7 contains the resulting process efficiencies of the individual scenarios based on the annual product (marine diesel) produced. The projected improvement in component efficiency and conversion increases the amount of product produced by the plant across the scenarios.  
As mentioned in the introduction, a container ship requires a certain amount of energy for typical long-distance transports. Using a lower heating value of \(LHV=43\frac{\text{M}}{\text{kg}}\), a fuel mass of 233 tons of marine diesel is required for each ship. Thus, the 300 MW large-scale plant considered in the scenarios can supply over 200 ships/transport route.  
In relation to the above-mentioned technical results of the simulation, the cost of capital for the dielectric barrier discharge (DBD)-plant is shown in Table 8.  
A \(CAPEX\) of over 1 billion emerge from the modeling of scenario 2018/20. This results, to a large extent, from the oxygen separation via the GDE. Based on the current density curve used in the scenario, an area of \(A_{GDE}\approx 142,000\) m\({}^{2}\) is required. By optimizing the current density curve, a significant decrease in costs can be observed in the scenarios 2030 and 2050. The FTS reactor also requires comparatively high capital costs because, as mentioned in the methodology, a high rate of recycle stream is applied. Due to the increased product yield, these \(CAPEX\) increases are negligible.  
In the diagrams shown in Figure 9, the net production costs (\(NPC\)) of scenario 2018/20 of the DBD plant are broken down. It is clearly visible that both the electricity costs and the \(CAPEX\) of the GDE make up a significant share of the costs. The data of the GA-plant, as well as the \(NPC\) of the scenarios 2030 and 2050 for each plant, are presented in Figure 10.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Factor \(F_{OPEX,ind}\)** & **Reference Value** & **Value** \\ \hline \(F_{OPEX,ind,1}\) & \(ALC\) & 0.15 \\ \(F_{OPEX,ind,2}\) & \(FCI\) & 0.1 \\ \(F_{OPEX,ind,3}\) & \(FCI\) & 0.1 \\ \(F_{OPEX,ind,4}\) & \(\sum_{k=2}^{3}{\it OPEX,ind,k}\) & 0.15 \\ \(F_{OPEX,ind,5}\) & \(ALC\) & 0.2 \\ \(F_{OPEX,ind,6}\) & \(ALC+\sum_{k=1}^{2}{\it OPEX,ind,k}\) & 0.6 \\ \(F_{OPEX,ind,7}\) & \(OPEX,ind,6\) & 0.25 \\ \(F_{OPEX,ind,8}\) & \(FCI\) & 0.02 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Factors for calculation of indirect OPEX.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Plant** & **Scenario** &
\begin{tabular}{c} **Process Efficiency in** \\ **\%** \\ \end{tabular} & **Product in (t/Year)** \\ \hline \multirow{3}{*}{DBD plasma} & 2018/20 & 16.5 & 32,000 \\  & 2030 & 19.6 & 39,000 \\  & 2050 & 24.4 & 48,000 \\ \hline \multirow{3}{*}{GA plasma} & 2018/20 & 22.7 & 45,000 \\  & 2030 & 24.6 & 49,000 \\  & 2050 & 27.5 & 54,000 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Process efficiencies of the different scenarios for dielectric barrier discharge (DBD) and gliding Arc (GA) plant.  
Due to higher capital costs, the part of \(NPC_{ACC}\) increases in the case of the gliding arc discharge (GA)-plant. However, since we receive more process heat and can use it to generate steam, which is sold as revenue, \(NPC_{OPEXdir}\) decreases by about the same amount as \(NPC_{ACC}\) increases.