## 4 Results and Discussion  
To check the proposed system's performance, MATLAB/Simulink tool is used to simulate the AC/DC hybrid microgrid system. Moreover, two modes of operation were studied (Islanded and grid-connected mode), under which the centralized barrier function-based adaptive sliding mode controller's performance is analyzed. In both the AC/DC microgrid modes, the primary aim is to stabilize the AC/DC bus voltages. The general configuration of the non-linear adaptive control technique illustrating the design procedure and structure during the entire operation of the micro-grid is given in Figure 7. Where energy sources (wind, PV, and battery) are attached with the power converters. RESs are firstly attached with the MPPT blocks before connecting with the power converters. Powers of the RESs are fed to the energy management block to ensure the power balance in the microgrid by the appropriate use of ESS during the islanding mode. Moreover, during the grid-connected mode, ESS will be in idle mode and the VSI side will be used to ensure the flow of power between the grid and RESs as per the load demands. The centralized barrier function adaptive SMC block generates all the control laws during grid-connected and islanding mode. Table 1 shows the irradiance and temperature change due to the weather conditions, heat, fog, and dust on the panels and generated MPPT voltages for the PV stacks in the system. The designed parameters used in the microgrid are listed in Tables 2-4. Moreover, Table 5 shows the comparison results of the proposed controller as compared to the other non-linear techniques. Simulations are performed for 19 s only. The profile of the wind speed for the considered model is shown in Figure 8a and the DC load power profile is given in Figure 8b. The references are generated by the high-level controller, assuming that they will ensure energy balance during the operation of the microgrid. However, these references are not designed separately. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Irradiance (W/m\({}^{2}\))** & **Temperature (\({}^{\circ}\)C )** & **V\({}_{\text{MPP}}\) (V)** \\ \hline
640 & 21 & 294 \\
700 & 26 & 286 \\
800 & 31.6 & 281 \\
900 & 37.4 & 270 \\
1000 & 42 & 266 \\
855 & 36 & 273 \\
740 & 33 & 278 \\
615 & 30 & 281 \\
515 & 27.2 & 287 \\
445 & 25 & 288 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Parameters of PV energy system. \begin{table}
\begin{tabular}{c c} \hline \hline
**PV Parameters** & \\ \hline Photo Voltaic module & 10 per string \\ Parallel linked strings & 1 \\ Cells per module & 60 \\ OC voltage & 363 V \\ SC Current & 7.84 A \\ Maximum power point voltage (\(V_{mpp}\)) & 290 V \\ Maximum power point current (\(I_{mpp}\)) & 7.35 A \\ Nominal power output capacity & 2.1 kW \\ \hline \hline \end{tabular}
\begin{tabular}{c} \hline Air density & 1.225 kg/m\({}^{3}\) \\ Wind speed & 5 m/s \\ Rotor diameter & 5.5 m \\ \(\lambda_{opt}\) & 7.5 \\ C\({}_{p-max}\) & 0.43 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Parameters of energy sources. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Battery type & Lithium-Ion (Li-Ion) \\ Voltage & 190–540 V \\ Rated current capacity & 33.9 Ah \\ Maximum charge current & 17.5 A \\ Maximum discharge current & 30 A \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Simulation Parameters. \begin{table}
\begin{tabular}{c c} \hline \hline
**PV Parameters** \\ \hline \hline
**PMSG** \\ \hline Rated power & 3 kW \\ Stator resistance & 0.036 ohm \\ Stator d-axis inductance & 0.334 mH \\ Stator q-axis inductance & 0.217 mh \\ Number of pole pairs & 4 \\ Flux linkage & 0.192 Wb \\ Moment of inertia & 0.011 kg m\({}^{2}\) \\ Viscos damping & 0.001889 N ms \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._