## 3 Performance Results  
In this section, the load profiles for CSGTs are analyzed. They incorporate data from public datasets [7, 8] and assumptions about typical residential load usage patterns. The electricity, gas, and water loads for each townhouse type (1-Bd, 2-Bd, 3-Bd, and 4-Bd) were calculated separately, and the optimization algorithms ML, PSO, and MOPSO were used to generate load profiles. The results were then aggregated to provide combined load usage for the CSGTs. The normalized total load \(L_{\text{total}}(t)\) at time \(t\) is given by  
\[L_{\text{total}}(t)=\sum_{i=1}^{N}w_{i}L_{\text{normalized},i}(t), \tag{16}\]  
where \(N=4\) is the number of townhouse types, \(L_{\text{normalized},i}(t)\) is the normalized load for the \(i\)-Bd townhouse at time \(t\), and \(w_{i}\) is the corresponding weight. The weights are \(w_{1}=0.20\), \(w_{2}=0.30\), \(w_{3}=0.25\), and \(w_{4}=0.25\) and reflect the relative contributions of the townhouses based on their size and occupancy. They were determined using energy consumption patterns derived from publicly available datasets [7, 8] and occupancy assumptions. The normalization for load type \(j\) (e.g., electricity, gas, or water) and townhouse type \(i\) is  
\[L_{\text{normalized},i,j}(t)=\frac{L_{i,j}(t)-L_{\text{min},i,j}}{L_{\text{max },i,j}-L_{\text{min},i,j}}, \tag{17}\]  
where \(L_{ij}(t)\) is the load for townhouse type \(i\) and load type \(j\) at time \(t\), \(L_{\text{max},i,j}\) is the maximum load for townhouse type \(i\) and load type \(j\) across the dataset, and \(L_{\text{min},i,j}\) is the corresponding minimum load. This is performed independently for each load and townhouse type to maintain consistency and ensure comparability across electricity, gas, and water loads. This prevents any single load type from dominating the total load profile due to differences in magnitude or units. The normalization for the \(i\)th Bd townhouse is then  
\[L_{\text{normalized},i}(t)=\frac{1}{3}\sum_{j=1}^{3}L_{\text{ normalized},i,j}(t). \tag{18}\]The electricity load is  
\[\text{Electricity Load}=P_{\text{appliance}}+P_{\text{lighting}}+P_{\text{HVAC}}, \tag{19}\]  
where \(P_{\text{appliance}}\), \(P_{\text{lighting}}\), and \(P_{\text{HVAC}}\) represent the power demand from electrical appliances, lighting, and Heating, Ventilation, and Air Conditioning (HVAC) systems, respectively. The gas load is  
\[\text{Gas Load (kWh)}=\text{Gas Volume (m${}^{3}$)}\cdot C_{\text{gas}}, \tag{20}\]  
where Gas Volume (m\({}^{3}\)) is the volume of natural gas consumed, and \(C_{\text{gas}}\) is the calorific value of gas (kWh/m\({}^{3}\)). The water load is  
\[\text{Water Load (kWh)}=\text{Water Volume (m${}^{3}$)}\cdot C_{\text{water}}, \tag{21}\]  
where Water Volume (m\({}^{3}\)) is the volume of water used, and \(C_{\text{water}}\) is the energy required to pump, heat, and treat water (kWh/m\({}^{3}\)). Figures 2-5 present the electricity, gas, and water load profiles over 24 h in kWh for the four townhouse types. These results show the variations in load patterns that reflect the differences in occupancy, space utilization, and resource needs. The 1-Bd SGT has the lowest load due to its compact size and low occupancy and so serves as a baseline for the other townhouses. The 2-Bd SGT shows a moderate increase in load due to the greater demand for heating, lighting, and water. The 3-Bd SGT has a higher load due to the needs of a larger family driven by increased space utilization and occupancy. These results indicate how load demand scales with family size. The 4-Bd SGT has the highest load because it has the largest family which results in significant demands for heating, lighting, and water. The aggregated load profiles for the four townhouse types are given in Figure 6. These results are used to evaluate the load optimization techniques and validate the scalability and adaptability of the proposed framework in addressing the dynamic requirements of CSGTs.