## 2 System Description  
The dynamic simulation of the PV system, was carried out using the Simulink model presented in Figure 1.  
The block P&O MPPT contains the P&O algorithm in a function and a limiter block that limits the duty cycle to values between 0.2 and 0.7, which enables a better control of the boost converter gains. The solar panel model used was developed by NREL (National Renewable Energy Laboratory), and is available in the Simulink library.  
The Simulink model for the fuzzy logic enhanced P&O MPPT controller contains instead a block named Fuzzy MPPT, which is presented in Figure 2.  
This block contains two functions, one of them calculates the error and the other calculates the change of error between iterations. Like the model for the P&O MPPT controller, it also contains a limiter block that limits the duty cycle to values between 0.2 and 0.7.  
Figure 1: Simulink Model of a boost converter, connected to the photovoltaic (PV) system.  
Figure 2: Fuzzy maximum power point tracking (MPPT) block, for the boost converter model connected to the photovoltaic (PV) system and controlled by a FLC.  
The PV Array block, contains information regarding 5 solar PV panels connected in series. The PV panel used was the monocrystaline 315 \(Wp\) solar PV panel, commercialized in Portugal by Zantia [24]. The total number of PV panels in the simulation is half of the total dimensioned PV system, which was projected for a small office building (with a medium occupancy of four people) with three phase power, in order to produce and consume more than 50% of the building's energy consumption without batteries, due to the fact that the chosen inverter [25] contains two boost converters. The most important parameters of the selected PV panel, are listed in Table 1.  
The PV Array block uses the solar irradiation (\(\mathrm{W/m^{2}}\)) and ambient temperature (\(\mathrm{{}^{\circ}C}\)), as input parameters. In order to obtain a better understanding of the solar PV array behavior, the environment conditions will change after 2 s as shown in Figure 3, with the dynamic simulation having a total run time of 10 s.  
The objective of the Simulink model is to study the parameters variation, related to the generated power of the PV system and the efficiency of the boost converters contained in a three phase inverter, in the changing environment conditions of the simulation. In  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline \(I_{sc}\) (Short-circuit current) & 9.98 A \\ \(V_{oc}\) (Open circuit voltage) & 40.80 V \\ \(I_{MPP}\) (Current at Maximum Power Point) & 9.45 A \\ \(V_{MPP}\) (Voltage at Maximum Power Point) & 33.35 V \\ \(\%I_{sc}\) & \(0.05\%/\mathrm{{}^{\circ}C}\) \\ \(\%V_{oc}\) & \(-0.29\%/\mathrm{{}^{\circ}C}\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Main PV panel characteristics, for the test conditions (solar irradiation of 1000 \(\mathrm{W/m^{2}}\) and ambient temperature of 25 \(\mathrm{{}^{\circ}C}\)) [24].  
Figure 3: Diagrams of (**a**) the solar irradiation values, (**b**) the ambient temperature variation.  
order to better analyse the behaviour of the boost converters, in the next subsection it will be detailed how the values of the boost converter components were obtained.