*4.4. Simulation Results of a Large-Scale 141-Bus Test System*

In this subsection, the proposed solution methodology is applied on a large-scale 141-bus system. Three cases studied are investigated. The system's initial power loss (without DGs) was 603.821 kW, where bus 87 has the minimum voltage that is 0.9294 Pu. In the 2nd case, the resulted uncertainties of the solar irradiance and wind speed are modeled by Beta-PDF and Weibull-PDF for the PV and WT sources, respectively. Therefore, the PV output power is evaluated at buses 60, 70, 80, 90, and 100. The active and reactive powers are hourly produced from the WT source at bus 50, as displayed in Figure 17.

**Figure 17.** Hourly produced active and reactive power from PV and WT sources for the second MG.

On the other side, the BGs are operated at their full capacity without optimal control. By running the load flow algorithm for these hourly circumstances, Figure 18 shows the total active power of each type of DG and the summation of loads and losses at each hour. During 9 h (1–8 and 24), there is surplus active power to be generated from the DGs in the MG and injected to the grid bus, where the generated power from the DGs in the MG is greater than the loads and the power losses so that the excess power is back to the grid bus. In the other 15 h, the MG absorbs active power from the grid bus.

**Figure 18.** Results of the second MG operation without optimal control.

In the third case, the developed EO algorithm is applied to optimally operate the MG in order to minimize the operational costs and the accompanied pollutants simultaneously over a 24-h scheduling horizon. Based on the developed EO, the output powers of the PV, WT, and BGs are optimized besides the associated power factors of the BGs. Figure 19a

shows the percentage apparent power of the BGs at buses 109, 16, 78, and 63 for each hour, whereas Figure 19b displays the hourly optimized value of the power factor.

**Figure 19.** Hourly apparent power and power factor of each BG for case 3 for the second MG.

To describe the power balance operation of the MG for each hour, Figure 20 illustrates the total active power of each type of DG and the summation of loads and power losses at each hour. At each hour, the generated grid power is always higher than 40% of summation loads and power losses whereas the penetration level of 60% is preserved by means of the developed EO algorithm.

For each hour, Figure 21 displays the minimum voltage for the three-cases studied. For hours 8–23, the minimum voltages are corrected in cases 2 and 3. In addition, in cases 2 and 3, the minimum voltages at all hours are above the permissible limit of 0.95 Pu. In the initial case (case 1), the highest minimum voltage occurs at bus 87 at hour 5, whereas the least minimum voltage occurs at the same bus at hour 15. At both hours, the voltage profile at all MG buses is described in Figure 22. However, the voltage profile at each bus is improved at light loading at hour 5. At this loading hour, bus 87 has the minimum voltage level in case 3. It is declined from 0.9616 to 0.9914 Pu. Additionally, the voltage profile at each bus is corrected at peak loading at hour 15, where the bus 87 has the minimum voltage

level in case 3 that is declined from 0.9294 to 0.9772 Pu which exceeds the minimum limit of 0.95 Pu; consequently, this improvement represents 5.14%.

**Figure 21.** Minimum voltage profiles for different cases studied at each hour **for** the second MG.

**Figure 22.** Bus voltage profiles for different cases studied at hours 5 and 15 for the second MG.

Moreover, the active power losses at each hour for the three cases studied are depicted in Figure 23. The power losses at each hour are greatly reduced from case 1 to cases 2 and 3, whereas the optimal operating strategy based on the developed EO algorithm in case 3 provides the minimum power losses at each hour through the day. Compared to case 1, the percentages of the reduction in power losses that are achieved by case 3 reached 78.9, 67.3, 58.0, 70.0, 77.1, 64.8, 49.5, 72.5, 79.9, 84.1, 80.2, 79.3, 80.6, 80.4, 73.8, 80.7, 79.9, 75.6, 73.4, 77.7, 80.4, 80.9, 77.2, and 71.3% for hours 1–24, respectively. Compared to case 2, the percentages of the reduction in power losses that are achieved by case 3 reached 66.7, 54.9, 48.3, 65.3, 73.2, 54.2, 13.3, 32.4, 38.9, 46.7, 32.0, 28.0, 32.8, 32.2, 11.9, 37.7, 38.5, 27.0, 23.7, 34.9, 41.9, 41.5, 34.1, and 42.6% for hours 1–24, respectively.

**Figure 23.** Active power losses for different cases studied at each hour for the second MG.

Additionally, the operational costs and the associated emissions of the distributed energy sources in the MG at each hour for the three cases studied are depicted in Figure 24. However, the operational costs and the associated emissions in the MG at each hour are greatly reduced from case 1 to cases 3 and 2. Despite case 2 providing the least operational costs and the emissions in the MG in comparison to case 3, the penetration limit of the total output of the DGs in the MG exceeds the limits of the 60% penetration ratio, as described by Figure 18.

**Figure 24.** Hourly optimal operational costs and the associated emissions in the second MG.
