# Design and Analysis of a Hybrid MPPT Method for PV Systems Under Partial Shading Conditions
## 3 Results and Discussion
### Comparison of the Proposed Method with the Other Methods  
In this section, the simulation cases are analyzed in detail. For all simulations made, except for the algorithm codes in the MATLAB/Simulink Function block, all remaining circuit elements and values are the same. A signal generator is used for all simulation cases and 1000 W/m\({}^{2}\), 800 W/m\({}^{2}\), 600 W/m\({}^{2}\), 500 W/m\({}^{2}\) and 900 W/m\({}^{2}\) irradiance values are given, respectively. Then, all simulation cases and the PV system including the proposed MPPT method are tested. The method proposed in this study is Perturb & Observe and Particle Swarm Optimization Hybrid Algorithm. The reference voltage generation graph is examined in detail compared to other simulation graphs. Figure 19: PV array output voltage and reference voltage graphs for the P&O and PSO Hybrid MPPT method. Figure 18: PV array output power graph and converter output power graph for the P&O and PSO Hybrid MPPT method with real irradiance. In the proposed algorithm, the reference voltage tracking speed is better than that of the other algorithms. It is seen that the reference voltage fluctuation is lower than that of other methods. It is observed that a graph closer to the reference voltage in terms of voltage value is formed. In most close-up views, the voltage pulses seen in other algorithms are lower or not seen at all. Simulation results show that the proposed Perturb & Observe and Particle Swarm Optimization Hybrid MPPT algorithm is a more efficient algorithm than the other algorithms. The following graphs show the reference voltage plots for all running simulation cases. Purple represents the Perturb & Observe MPPT method. Blue represents the Perturb & Observe and Kalman Filter Hybrid MPPT method. Red represents the proposed Perturb & Observe and Particle Swarm Optimization Hybrid MPPT algorithm. Lastly, green represents the PV array voltage. Figures 21 and 22 show the reference voltages produced by different algorithms in a case where the irradiance value changes seriatim. When the graph is examined, the proposed P&O and PSO Hybrid MPPT algorithm produce a closer reference voltage than the P&O MPPT algorithm. Compared to the P&O and KF Hybrid MPPT algorithm, the pulse signal appearance is less or absent in the reference voltage graph of the proposed method. Figure 21: The reference voltages graph produced by different algorithms in a case where the irradiance value changes. Figure 20: PV array output voltage and reference voltage graphs for the P&O and PSO Hybrid MPPT method with real irradiance. As seen in these graphs, the P&O and PSO Hybrid MPPT algorithm provides tracking earlier than the P&O and KF Hybrid MPPT algorithm. When the reference voltages produced by different algorithms are in a stable situation where the irradiance value is constant, the P&O and PSO Hybrid MPPT algorithm produces a more stable and accurate reference signal than the other algorithms. The energy production at the MPP provided by the proposed MPPT method according to real solar irradiance data is given in Table 4.  
In summary, the simulation results are compared and evaluated in terms of accuracy and tracking speed. Table 5 includes these comparisons. In the PV system where the Perturb & Observe MPPT algorithm is used, the reference voltage is followed by MMP at a moderate level compared to the other methods. In the simulation of the PV system where the Perturb & Observe and Kalman Filter Hybrid MPPT algorithm is used, the reference signal tracking is at a medium level. It has been observed that its performance at times of irradiance change is also at a medium level compared to the others. In the PV system simulation where the Perturb & Observe and Particle Swarm Optimization Hybrid MPPT algorithm is used, a higher accuracy MPP tracking is observed