## 3 Results and Discussion
### Results and Discussion for Area 1  
The modeled system has been operated for 200 s. The changes of \(ACE_{1}\) for area 1 are shown in Figure 16. In Figure 16b, the effect of increasing the demand power in area 2 on the frequency in area 1, is demonstrated. According to the results obtained from the four different controllers, the GA-FLC demonstrates a better performance than the others, in terms of the sudden oscillations. Additively, Figure 16c illustrates the effect of a long-term power drop of the solar power plant due to climatic conditions on the \(ACE_{1}\) value. According to the results of Figure 16, the proposed GA-FLC could set the desired value within certain limits, such that there is hardly any oscillation. In Table 6, the obtained results are presented. The proposed GA-FLC also exhibited the best performance, with a settlement time of 5.5 s. from the 70 th s, as indicated in Table 6. It is also seen that the GA-FLC has a better value as \(0.06\times 10^{3}\)\(Pu\), when compared to other controllers at the 70 th s. In Figure 17, variations of the absolute value of the \(ACE_{1}\) value for area 1; (a) PID; (b) GA-FLC; (c) GA-PID; and (d) FLC, are demonstrated. The reason why the absolute value of the \(ACE_{1}\) is displayed is that the reference error variance of the system used in the GA processes could be seen from zero, to how much it changes in the positive direction. In addition, the \(ACE_{1}\) signal, which is controlled by four different controllers, was converted to the form, \(U_{(t)1}\), in Figure 18, and was then transferred to the governor and the turbines to balance the frequency value. The purpose of this is to observe which signals sent to the turbines and the generators are more effective. The \(U_{(t)1}\) signals obtained from the controllers are shown in Figure 18. As shown in Figure 18b, GA-FLC produced a wider and higher frequency value. This is due to the use of more mathematical functions while modelling the GA-FLC in a Simulink environment. With frequency damping blocks, this high frequency signal can be prevented from damaging the turbine valves. Moreover, Figure 19 shows that the frequency value in the interconnected network controlled by the proposed GA-FLC is better than the other control methods. The effect of a load increase in area 2 on area 1 was shown to be minimized. Furthermore, the frequency oscillations of the proposed GA-FLC were shown in this way, which shows the frequency value in the interconnected network, to be kept at the minimum value. The best results obtained by GA-FLC have also been reached by a settling time of 5.1 s and an overshoot value of \(-0.00018\)\(P_{u}\), as indicated in Table 6.  
Figure 15: Power variations in the solar power plant and areas and: (**a**) solar insolation; (**b**) solar power; (**c**) area 1 demand power; (**d**) area 2 demand power.  
Figure 16: Changes of \(ACE_{1}\) in the area 1: (**a**) during all simulation time; (**b**) 5 th change; (**c**) 70 th change.  
Figure 17: Variations of the absolute value of the taken \(ACE_{1}\) change for area 1: (**a**) PID; (**b**) GA-FLC; (**c**) GA-PID; (**d**) FLC.  
Figure 18: \(U_{(l)1}\) changes using controllers for area 1: (**a**) PID; (**b**) GA-FLC; (**c**) GA-PID; (**d**) FLC.