## 3 Proposed Coordinated MPPT Algorithm  
The conventional P&O and INC MPPT methods make a control variable increase or decrease for dragging an operating point toward the expected GMPP region. However, they cannot predict the accurate step size of a control value closest to the reference value under adverse weather conditions and shading patterns that occurred on the PV plant. If a smaller step size of a control parameter is chosen near the GMPP, power losses on the P-V curve decrease with an exceptionally low tracking speed. The proposed coordinated MPPT algorithm can address the speed-oscillation tradeoff while the operating point almost tracks the GMPP in terms of dynamics. The PI controllers are dedicated to controlling both the current and voltage of the boost converter in cooperation with the proposed \begin{table}
\begin{tabular}{c c c} \hline \hline
**Symbols** & **Quantities** & **Values** \\ \hline \(\mathrm{V_{g}^{Rated}}\) & Nominal grid voltage/frequency & 250 V (RMS)/50 Hz \\ \(\mathrm{I_{g}^{Rated}}\) & Rated grid current & 4.72 A (RMS) \\ \(\mathrm{I_{gw}}\) & Switching frequency & 10 kHz \\ \(\mathrm{V_{dc}^{nominal}}\) & Nominal DC-Link Voltage & 400 V \\ \(\mathrm{C_{DC}}\) & DC-Link Capacitance & 945 \(\mu\)F, 450 V \\ \(\mathrm{L_{i}}\) & Bridge side inductor & 3 mH \\ \(\mathrm{L_{g}}\) & Grid side inductor & 3 mH \\ \(\mathrm{C_{f}}\) & Filter capacitor & 55 \(\mu\)F, 450 V \\ \(\mathrm{R_{D}}\) & Filter damping resistor & 1.5 \(\Omega\) \\ \(\mathrm{K_{P}}\) & Proportional gain of PI & 3 \\ \(\mathrm{K_{i}}\) & Integral gain of PI & 200 \\ \(\mathrm{K_{pr}}\) & Proportional gain of PR & 5.7 \\ \(\mathrm{K_{R}}\) & Resonant gain of PR & 1128.3 \\ \(\mathrm{\omega_{o}}\) & Resonant frequency of PR & 314.16 rad/s \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Inverter design parameters. Figure 7: Bipolar SPWM control complementary pulses. MPPT algorithm. Furthermore, the proposed coordinated MPPT method is an improved algorithm deployed in a closed-loop PV array to harness maximum energy at any dynamic weather conditions (exhibiting numerous multiple power peaks on the P-V curves), unlike a conventional open-loop PV system. Nevertheless, the proposed MPPT technique is much superior to the traditional MPP trackers in terms of convergence speed, tracking speed, and power oscillations around the GMPP location. This study uses a trial and error approach to predict PI gain parameters. By tuning the PI controllers and realizing a closed-loop response, the optimum tuned parameters \(\mathrm{Kp}\) and \(\mathrm{Ki}\) are obtained. Then, an INC algorithm is applied to control the duty cycle of the boost converter [35]. The parameters of PI controllers are presented in Table 3. Thus, the optimum PI-tuning parameters necessary for minimizing the oscillations around the MPP can be found. The input current and output voltage of the boost converter are controlled by controlling the duty cycle on a switching device to obtain the output characteristics of the solar cell. The proposed algorithm takes the feedback voltage and current from the PV array as input and generates the optimal duty cycle to track the MPP. The duty cycle addition increases the output voltage of the PV module and decreases the output current of the module. The output power is not directly related to the duty cycle on the switching device; instead, it is directly related to the output current and output voltage of the PV module. This proposed method finds a true GMPP of the PV modules by iteratively perturbing the converter input current and output voltage, and comparing the power (\(\mathrm{P_{PV}}\)) generated by the PV module with the output power of the boost converter (\(\mathrm{P_{o}}\)) (Figure 8). The voltage and current perturbations are achieved through the changes in the duty cycle D. The error sign (\(\mathrm{\Delta P=P_{PV}-P_{o}}\)) is used to determine the direction of the perturbation.