## 4 Results and Discussions
### The Results Obtained by WOA in Case 4  
In this section, the WOA is reapplied to reach the optimal power loss value of the IEEE-85 with the evaluation of load demand variation and power supplied from WTs within 24 h in two scenarios, as mentioned earlier. According to [40], load demand varies within 24 h in a day, by specific load factors corresponding to four quarters of a year. The load factors are cited and displayed in Table 12 in the Appendix A. By using these load factors, the particular load demand at each hour in a day of a month on the considered grid is calculated. Note that the optimized positions of WTs are taken from Case 2; these positions are already determined in the previous section. The selected WTs are the three-megawatt platforms of General Electric manufacturers [41]. All of the basic specifications of the selected WTs are listed in Table 13 in Appendix A. In addition to that, the two WTs are supposed to be placed at two different coordinates: the first WT is placed at Ninh Hai District, Ninh Thuan province, Vietnam, with the exact coordinate 11.697626\({}^{\circ}\) N 109.15947\({}^{\circ}\) E, and the average wind speed is 8.5 m/s; the second WT is placed at Loi Hai, Thuan Bac District, Ninh Thuan province, Vietnam, with the exact coordinate 11.771915\({}^{\circ}\) N 109.073639\({}^{\circ}\) E, and the average wind speed is 7.37 m/s. Additionally, all of the related data about the wind indexes of the two WTs for twelve months within a year are collected from the Global Wind Atlas (GAS) [42], and these data are described in Tables 14 and 15, respectively, of the Appendix A. By using the data collected from GAS, the power supplied by the WTs within 24 h of an average day in twelve months is fully determined. Figure 15 describes the power loss of 24 h in a day of the twelve months obtained in Scenario 1. In the figure, the months with the lowest and the highest power loss values belong to September and November, respectively. Note that the two WTs are only optimized for their power factors, while the power supplied by these WTs is fully injected into the grid. Figure 16 illustrates the power loss of 24 h in a day of twelve months obtained by the WOA in Scenario 2. In the figure, November and August are the two months with the lowest and highest power loss values within 24 h. Note that the WTs are optimized for both their power supply to the grid and their power factors in this scenario. Moreover, the power loss values within 24 h of each month achieved in Scenario 2 are substantially decreased compared to the similar ones achieved in Scenario 1 that has been presented above. Figure 14: The power loss comparisons of systems with and without WTs. By multiplying the power loss at each hour of a day with the number of days corresponding to each month, the energy loss value of each month is determined. Figure 17 shows the comparison of the power loss values of twelve months in three cases: (1) Base system without WTs, (2) Scenario 1, (3) and Scenario 2. It is easy to realize that the energy loss values of the twelve months resulting from Scenario 2 are noticeably lower than those from the Base system and Scenario 1 from January to June and from October to December. From July to September, the differences in the energy loss values given by Scenario 2 are still very large compared to the Base. However, compared to Scenario 1 in these months, the differences in the energy loss values achieved by Scenario 2 are not that much, and even a bit lower in September. Figure 16: The power loss at each hour of twelve months of Scenario 2. Figure 15: The power loss at each hour of twelve months of scenario 1. Figure 18 summarizes the total energy loss of the three cases in the year as described earlier. The implementation of Scenario 2 results in the best energy loss values compared to others. Specifically, the energy loss values obtained in Scenario 2 are only 223,090.53 kW, while the similar values obtained in Scenario 1 are 5,554,596.56 kW and up to 7,376,664.27 kW in the Base case.