**6. Comparative Study between the Studied Optimization Techniques**

Figure 16 shows the simulation results of the instantaneous power extracted from the GPV across the four types of coupling, that is, direct coupling and coupling by an MPPT tracker. The latter is controlled by three types of algorithms: P&O, modified incremental, and hybrid FL-INC. The efficiency of the SWPS is very influenced by the weather conditions and the operating point of the system. The results in Figure 16 show that with direct coupling, the system efficiency is poor and the system operates farther from the maximum power point. The SEPIC converter with MPPT control has variable efficiency and tracking dynamics. With the P&O technique, the tracking of the power point is significantly improved over direct coupling, but the system is not able to have a better tracking speed during sudden changes in irradiance. The M-INC technique can overcome the tracking problem, but suffers from power overshoot during sudden irradiance changes compared with the hybrid technique.

**Figure 16.** Instantaneous power of different solar water pumping techniques studied.

To show the influence of the power point tracking techniques on the solar water pumping flow rate, the histogram in Figure 17 presents a comparative study of the flow rate for each technique used. In fact, the flow rate in this simulation is calculated from a rotational speed that varies over the entire range of the simulation. According to Equation (3), the calculated flow rate is directly in proportion to the speed motor in the simulation. From

the results, the hybrid technique has a better pumping rate than the others, that is, 55% rate compared with direct coupling, 8.5% compared with the P&O technique, and 5% rate compared with M-INC. Finally, the hybrid technique based on fuzzy logic for the artificial intelligence and the incremental technique has effectively improved the performance of SWPS.

**Figure 17.** Water flow pumped from different techniques.
