## 3 Optimization of Annual Costs
#### Sensitivity Analysis  
Due to the influence of some key variables on the final results, the next sub-section provides a sensitivity analysis regarding variations in the price of electricity and operational hours for the optimised scenarios shown before. Firstly, the price of electricity considering both was modified--an increase and decrease of 15% in the cost of energy. This has been performed for the optimal scenario for each gas. The results are summarized in Table 10. The variations in electricity price directly affect the OPEX. As these costs have a lower weight than CAPEX, the results in TAC are not as high as it could be expected in the first instance. On the one hand, the results using carbon dioxide show how a decrease of 20% in the COE implies a decrease in TAC of 1.5%, and an increase of 20% in the COE implies an increase in TAC of 1.5% as well. On the other hand, the results using hydrogen show how a decrease of 20% in the COE implies a decrease in TAC of 2.87%, and an increase of 20% in the COE implies an increase in TAC of 2.84%. Additionally, using hydrogen it must be noted that a decrease of 20% in COE implies a compressor ratio over than the maximum limit considered. In that case, the optimal configuration would be the one with four intercooling compression stages. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**K**} & \multirow{2}{*}{**P (bar)**} & \multirow{2}{*}{**V (m3)**} & \multirow{2}{*}{**Cr**} & **TAC** & **CC** & **HEC** & **TC** & **E** & **CAPEX** & **a** & **OPEX** \\  & & & & **(f/Year)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c/Year)** & **(c/Year)** \\ \hline
1 & 72.40 & - & 72.40 & - & - & - & - & - & - & - & - \\
2 & 72.45 & - & 8.51 & - & - & - & - & - & - & - & - \\
3 & 72.46 & - & 4.17 & - & - & - & - & - & - & - & - \\
4-SC & 72.47 & 15.49 & 2.92 & 60,068 & 46,114 & 13,378 & 93,749 & 385,231 & 847,505 & 56,966 & 3102 \\
5 & 72.48 & 15.49 & 2.36 & 70,397 & 45,640 & 13,265 & 93,749 & 454,597 & 1,000,000 & 67,223 & 3174 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Optimization results for the different scenarios, CO\({}_{2}\). \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**K**} & \multirow{2}{*}{**P (bar)**} & \multirow{2}{*}{**V (m3)**} & \multirow{2}{*}{**Cr**} & **TAC** & **CC** & **HEC** & **TC** & **E** & **CAPEX** & **a** & **OPEX** \\  & & & & **(f/Year)** & **(f)** & **(c)** & **(c)** & **(c)** & **(c)** & **(c)** & **(f/Year)** & **(f/Year)** \\ \hline
1 & 57.27 & - & 57.27 & - & - & - & - & - & - & - & - \\
2 & 65.41 & - & 8.09 & - & - & - & - & - & - & - & - \\
3 & 67.64 & 193.70 & 4.00 & 83,734 & 51,446 & 13,958 & 271,669 & 509,756 & 1,121,000 & 75,380 & 8354 \\
4-SC & 68.66 & 191 & 2.88 & 93,677 & 49,325 & 13,641 & 271,332 & 577,765 & 1,271,000 & 85,437 & 8240 \\
5 & 69.24 & 189.5 & 2.33 & 103,879 & 48,140 & 13,465 & 271,156 & 646,506 & 1,422,000 & 95,602 & 8278 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Optimization results for the different scenarios, H\({}_{2}\). Secondly, we considered variations in the operational hours for the discrete values of 96 and 168 h/week (Table 11). This operation time was considered as the time when the compressors are actively compressing and storing the gas. The results of these variations in the operation time indicates that this parameter has more influence in TAC than fluctuations in the electricity price. On the one hand, duplicating operational hours using carbon dioxide implies an increase in TAC of 5.16%. Moreover, considering the compressors are fully working all week, the TAC increased by 12.91%. On the other hand, duplicating the hour of operation using hydrogen implies an increase in TAC of 9.84%. Finally, the increase in TAC is 24.12% considering the compressors working full-time.