## 5 Digital Simulation Experiments and Analysis
### Simulation Case 2  
In this case, simulations are carried out under different scenarios to compare the proposed MPPT method with other methods such as the conventional P & O method [5] and the improved P & O  
Figure 12: Output current and voltage in different parts of the PV array.  
Figure 13: DC-link voltage and inverter output current: (**a**) DC-link voltage; (**b**) three-phase output current.  
method [4]. The duration of simulation is 2 s, which is separated into three sections as illustrated in Table 2.  
From Table 2 and Figure 14, it can be observed that the simulation process consists of three different partial shading processes. It is assumed that under the simulation pattern 1 (SP1), all three methods can achieve MPP.  
1. As shown in Part I of Figure 14, when the shading condition changes to SP2 from SP1, the PV output characteristic changes from the pink curve to the brown curve. The traditional P & O algorithm (the green curve in Figure 14) can track the MPP (point a) in section SP1. However, only the local MPP (point b) in section SP2 can be tracked by the traditional P & O algorithm, which indicates that the traditional P & O algorithm for MPPT fails to track the GMPP in section SP2. Since the instantaneous power change \(\Delta\)P is large, the improved P & O algorithm (the blue curve in Figure 14) can start the global search module and track the GMPP (point c), similar to the method proposed in this paper (the red curve in Figure 14). It is clear from the dynamic process that the response time of the proposed method is much less than that of the improved P & O algorithm, and that the tracking speed is increased more than 6-fold. By combining this inference with the information in Table 3, it can be inferred that the steady-state maximum power of the proposed method is also superior to that of the improved P & O algorithm.
2. When the shading condition changes to SP2 from SP3, the PV output characteristic changes from the brown curve to the black curve, as shown in Figure 14 II. It can be seen that the MPP (point c) of the SP2 shading condition is near the local MPP (point d) of the SP3 shading condition. It is difficult to start the global search because the power change due to the shading condition change is not large enough. Therefore, the improved P & O and traditional P & O algorithms track the local MPP (point d) in identical manners, which indicates that the GMPP tracking fails in the cases of the improved P & O and traditional P & O algorithms. It can be seen from Table 3 that the power loss caused by MPPT failure is 699 W, which accounts for approximately 10% of the maximum power. The method proposed in this paper can track the MPP (point e) quickly and accurately, and effectively solve the MPPT failure problem caused by local shadow conditions.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Section No.** & **Time (s)** & **Shading Pattern [G\({}_{1,1-12}\), G\({}_{2,1-12}\), G\({}_{3,1-12}\), G\({}_{4,1-12}\), G\({}_{5,1-12}\), G\({}_{6,1-12}\)] (W/m\({}^{2}\))** \\ \hline SP1 & 0.1–0.3 & [300, 300, 300, 1000, 700, 700] \\ SP2 & 0.3–1.5 & [300, 300, 300, 1000, 500, 500] \\ SP3 & 1.5–2.0 & [300, 300, 300, 1000, 1000, 300] \\ \hline \hline \end{tabular}
\end{table}
Table 2: Considered shading conditions.  
Figure 14: Comparison of proposed MPPT method with the P & O (perturb and observe) and improved P & O methods, under different scenarios.