## 3 Simulation Results  
The effectiveness of the proposed optimization model was evaluated in a real aquaculture industry at the Port of Hirtshals in Denmark. The facility features three cooling systems. Saltwater is drawn in through a water tank that is regularly refilled by another facility. One of the newly installed cooling systems is responsible for pre-cooling of the water prior to discharge into the breeding pools. Additionally, each breeding pool is equipped with a primary cooling system that lowers the water temperature and keeps it within acceptable bounds. Technical and economic information regarding this industry can be found in Table 1.  
Figure 2 illustrates the hourly heatmap of the saltwater temperature intake from the water tank in 2023. As expected, as summer approaches, the temperature of the water rises; closer to winter, the colder water reduces the need for operation of the cooling systems. In the industry under study, two cooling systems are responsible for reducing the water temperature, while the third system is used for pre-cooling. The power consumption of these systems was measured in different hours from the year 2023. Figure 3 demonstra \begin{table}
\begin{tabular}{l l} \hline \hline
**Item** & **Value** \\ \hline Primary Ammonia plant & Capacity: 2.5 MW; COP: 3 \\ Primary CO\({}_{2}\) plant & Capacity: 3 MW; COP: 2.5 \\ Precooling CO\({}_{2}\) plant & Capacity: 2.5 MW; COP: 2.5 \\ Threshold temperature: & 12 \({}^{\circ}\)C \\ Mass flow rate from tank & 150 m\({}^{3}\)/h \\ Mass flow rate discharging to pools & 75 m\({}^{3}\)/h \\ Electricity Price & Dynamic for 2023 \({}^{1}\) \\ \hline \hline \end{tabular} \({}^{\dagger}\) Source: www.energidataservice.dk/tso-electricity/Elspotrices, accessed on 29 May 2025.  
\end{table} 
Table 1: Technical and economic characteristics considered in this study. decomposition of the power consumption of the ammonia cooling system using the Loess method for two seasons, namely, spring and summer. According to this technique, the observed data were decomposed into three components: trend, daily cycle, and residual. The trend component graph illustrates the long-term progression of power consumption by eliminating short-term fluctuations. As shown in the spring graph, power consumption increases as summer approaches, likely due to higher saltwater temperatures. However, fluctuations in the trend during summer can be attributed to variations in water temperature throughout the season, and the maximum power consumption reaches nearly 900 kW. The daily cycle component extracts the portion of the power consumption data that repeats every 24 h, helping to identify the hours when peaks and valleys occur. Finally, the residual component captures what remains after removing both the trend and daily cycle from the observed data, highlighting potential outliers, measurement errors, or unexpected events impacting the cooling system. It is noteworthy to mention that significant residual values during certain hours suggest that these periods warrant further investigation. A similar decomposition analysis was applied to the power consumption of this unit in autumn and winter, with the results shown in Figure 4.  
Figure 3: Seasonal-trend decomposition of the power consumption of the ammonia cooling system for spring and summer. Figure 2: Hourly water temperature heatmap for year 2023. In contrast to the summer trend, the autumn trend component shows a reduction in the cooling system's power consumption as winter approaches. Moreover, the residual values are insignificant for most hours, which improves the prediction of power consumption based on the trend and daily cycle patterns. Furthermore, when examining the decomposition results for winter, we observe that for most hours the power consumption is zero, indicating that during those periods the water temperature is below a specific threshold and the cooling system does not need to operate.