## 4 Simulation Results and Discussion  
The proposed PV power system, connected via a boost converter to the DC load, was implemented using MATLAB/Simulink. The MPPT algorithms employed to track the GPP output were the CSO and PSO. To assess the performance of these two metaheuristic MPPT techniques, numerical simulations were performed under both uniform and PSCs considering static and dynamic scenarios. A comprehensive analysis of the results is provided, highlighting the performance characteristics of the CSO and PSO in these varying environments. The following sections present the key findings of the results for the CSO and PSO methods under static and dynamic environmental conditions in both uniform and partial shading. Scenario 1: Static Uniform Circumstances  
In the scenario of uniform conditions, the PV array receives an equal amount of sunlight, leading to a single MPP. In this scenario, the three PV modules receive identical irradiance levels (1000, 1000, 1000) as a uniform condition, producing an output power and output voltage value of 749 W and 92.5 V at the MPP. Figure 5 indicates the PV output power tracked by the CSO and PSO under these uniform irradiance conditions. The figure demonstrates that both CSO and PSO successfully identify the unique peak power (749 W and 748 W, respectively). However, the CSO outperforms the PSO by exhibiting significantly reduced oscillations and requiring less tracking time (0.6 s) to reach the peak power compared with the PSO, which exhibits higher oscillations and a longer tracking time (1.6 s). Table 5 introduces a comparison of the performance metrics of CSO and PSO under static uniform circumstances. Figure 5: Scenario 1: Output generated power and output voltage under uniform conditions [1000,1000,1000]: (a) CSO and (b) PSO. Scenario 2: Static or Time-Invariant Partial Shading  
In the presence of static PSCs, the three modules of the PV are exposed to distinct irradiance levels. This variation results in the formation of multi-peaks on the P-V curve consisting of a single global maximum alongside several local maxima. In this scenario, the solar irradiance levels applied to the modules of the PV are [1000,900,800], leading to multi-peaks with a theoretical GPP value of 637.9 W at a maximum power point voltage (V\({}_{\text{MPP}}\)) of 95.5 V, as demonstrated in the power-voltage characteristic in Figure 6. The figure also presents the PV-generated power tracked by the CSO and PSO under these non-uniform irradiance conditions. While both CSO and PSO successfully identify the global peak power (637.9 W) and voltage (95.5 V), the CSO method demonstrates superior performance by exhibiting fewer oscillations and a shorter tracking time (0.48 s) compared with the PSO, which shows significant oscillations and a longer tracking time (1.7 s). Scenario 3: Dynamic Uniform Conditions  
In dynamic PSCs, the three PV modules are exposed to the same values of uniform irradiances (1000, 1000, 1000) for a specific interval [0 to 2 s], leading to GPP with a theoretical maximum power and output voltage of 749.3 W and 92.9 V, as illustrated in Figure 7 (P-V curve). Subsequently, the irradiance levels were adjusted to [850,850,850] for the time interval between 2 and 4 s, resulting in a shift to another GPP with theoretical GPP and output voltage values of 638.4 W and 92.8 V, respectively. The major objective of this case is to investigate if the PSO and CSO technique can follow the new GPP or stick to the first GPP. Figure 7 shows the obtained findings of the PV-generated power and the output voltage captured by the CSO and PSO under dynamic uniform conditions. Figure 7 shows that the CSO succeeded in tracking the first GPP with fewer oscillations, and it requires a shorter tracking time to detect the global peak of 749 W. After changing the irradiances to [850,850,850], the CSO technique sticks to the previous position and cannot track the new GMP at the new place.