# Energy Optimization in Hotels: Strategies for Efficiency in Hot Water Systems
## 4 Results and Discussion
### Results of the Thermodynamic Evaluation
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline \multirow{2}{*}{**Parameters**} & \multirow{2}{*}{**Unit**} & \multicolumn{2}{c}{**Chiller 1**} & \multicolumn{2}{c}{**Chiller 2**} \\ \cline{3-6}  & & **Part-Load** & **Nominal** & **Part-Load** & **Nominal** \\ \hline Suction pressure & bar & 1.5 & 1.7 & 1.5 & 2.00 \\ \hline Discharge pressure & bar & 10 & 12.2 & 11 & 12.2 \\ \hline Superheating & \({}^{\circ}\)C & 8 & 8 & 3 & 8 \\ \hline Subcooling & \({}^{\circ}\)C & 3 & 3 & 3 & 3 \\ \hline Compression work & kJ/kg & 40.96 & 42.65 & 39.12 & 43.07 \\ \hline Compressor outlet temperature & \({}^{\circ}\)C & 59.18 & 68.01 & 60.67 & 69.26 \\ \hline Condensation temperature & \({}^{\circ}\)C & 40 & 46.32 & 43 & 46.97 \\ \hline Refrigerant flow rate & kg/s & 1.6 & 1.69 & 1.33 & 1.81 \\ \hline Compressor power & kW & 65.54 & 72.08 & 52.03 & 77.96 \\ \hline Cooling capacity & kW & 125.67 & 234.89 & 216.84 & 416.72 \\ \hline Primary circuit water flow & kg/s & 2.91 & 2.91 & 2.91 & 2.91 \\ \hline Recovery heat & kW & 27.61 & 95 & 39.83 & 158.3 \\ \hline Recovery temperature & \({}^{\circ}\)C & 55.11 & 60 & 56.11 & 64.99 \\ \hline Heat recovery percentage & \% & 8.09 & 21 & 17.86 & 25 \\ \hline COP & - & 2.21 & 4.58 & 3.62 & 4.87 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Operating parameters of the chillers under nominal and part-load conditions. In this new scenario, a balance is achieved between the heat recovery from the chillers and the temperature of the hot water in the primary circuit, aiming to maintain stability around 60 \({}^{\circ}\)C in the primary and 55 \({}^{\circ}\)C in the supply circuit (Figure 9a). With the optimized system, the new mass flow values allow the maximum possible heat to be recovered from the chillers in a stable manner, minimizing the use of the backup device. This results in significant fuel savings for the hot water system, with minimal auxiliary heating consumption, reducing fuel usage by up to 50%, as shown in Figure 9b. The above clearly demonstrates that, under conditions of maximum DHW demand, the use of backup systems is essential to meet the technical requirements established for these types of comfort service systems, whose parameters are regulated by international standards. However, in a context where reducing energy consumption is a priority, the implementation of effective and rational alternatives becomes necessary. For this reason, decisions are made to establish rule-based operation strategies, which are common in systems exposed to fluctuating demand throughout the day. This is the case of DHW systems due to their operational dynamics, which exhibit marked variability both daily and seasonally. Figure 8: GA convergence. Figure 7: Recovery temperature with flow variation in the DHW circuit at partial load. The first strategy evaluated in this study considers the variation of flow rates in the primary and secondary DHW circuits with 100% use of auxiliary heating. The second strategy is to implement a rule-based operation, activating the backup device during the periods from 6:30 am to 8:30 am and from 4:00 pm to 8:00 pm. This second approach corresponds to only 25% use of auxiliary heating over 24 h of continuous ACS system operation. The advantage of having a model that can predict the operational behavior profile of the system throughout the day is that it enables the definition of an effective and applicable strategy for any typical facility in tropical regions, with similar climatic conditions and guest consumption profiles. The proposed methodology allows complete modeling of the facility, which includes the centralized air conditioning system with heat recovery. It enables an evaluation of its operational behavior over a 24-h period, assessing the system's response to variations in operating conditions and the extent to which it meets the hot water demand required by the hotel installation. The system's operational behavior is evaluated in the case study hotel.