## 1 Introduction
A modified P&O algorithm which is basically different from the conventional one by considering a third test in its flowchart--that is, the change in the PV current--was suggested in [20]. The algorithm considered eight cases of operating point perturbation: four were with fixed irradiance, and four were investigated to illustrate the cases of fast weather variation. The results confirmed that this controller can track MPPs very well under uniform conditions; however, this algorithm has to be improved to be able to work under partial shading conditions. Also, a novel adapted variable step size P&O was proposed in [6]. This work was based on the Pythagorean theorem, which can overcome the weaknesses and restrictions of conventional P&O MPPT under fast weather changes, while the performance was still not efficient under partialshading conditions. For efficient tracking, the author of [21] suggested a new GMPP tracking (GMPPT) technique based on the Perturbed-based Extremum Seeking Scheme (PESC). A new autoscaling variable step size MPPT technique which can regulate the step size of the procedure in order to obtain the fast dynamic was proposed in [22]. In the proposed modified P&O technique, a large perturbation step is considered when the current operating point is far from the MPP, whereas a small step size is adopted in close proximity to the MPP. Another technique which can find the characteristic curve from on-site measurements was proposed in [23]. During the process of defining the characteristic curve, the values of both current and voltage at the MPP are also specified. The simulation and experimental outcomes proved the capability of the algorithm to determine the characteristic curve and to fix the GMPP voltage and current values under variations in shading conditions [23]. GMPPT using the Fuzzy Logic methodology based on IC was proposed in [24] to track the GMPP. The suggested fuzzy controller takes the P-V curve slope as an input and produces output adaptable as the duty ratio of the boost converter for MPP tracking. The algorithm robustness was validated via a comparative study. The Fuzzy-Logic-based global MPPT algorithm was also applied in [25], and the simulation evaluation successfully showed that the suggested method is superior to the conventional P&O in terms of tracking efficiency and convergence speed. A GMPPT algorithm was proposed in [26]. The proposed algorithm is Moth-Flame Optimization (MFO) depending on the power optimization at the boost converter output. A combination of two methods was proposed, in which the first one is for tracking the GMPP for the case of a 100 kW array [26], and the second method is the distributed maximum power point tracking (DMPPT) structure for the case of a 1 MW PV plant under different partial shading conditions. The simulation results demonstrated the ability of the proposed algorithm to track the GMPP of the PV array system, but the algorithm is considered complex with low convergence speed. An effective and extremely precise hybrid MPPT controller which combines fuzzy logic control and the P&O method in order to track the MPP of PV under partial shading conditions was proposed in [27]. The proposed technique had the ability to enhance both steady-state and dynamic conditions. The results of simulations clarified the strength and effectiveness of the suggested process under intense atmospheric fluctuations. However, the algorithm suffers from two major drawbacks: the high cost and the difficulty of implementing a stable efficient controller. Another contribution was also made to the conventional MPPT algorithm to improve its effectiveness under partial shading conditions. An enhanced P&O algorithm based on global MPPT integrated with a DC/DC Buck converter was proposed in [1] to work under partial shading conditions. The presented procedure consists mainly of two further parts: the foremost MPP algorithm for unchanging weather conditions and a GMPP algorithm for partial shading conditions.