<p>This paper introduces a procedure for the modelling of a Photo<em>ــ</em>Voltaic (PV) cell and the application of maximum power point tracking (MPPT) in step-by-step with MATLAB/Simulink. The model of one diode is used to explore the characteristics of I<em>ــ</em>V and P<em>ــ</em>V curves of 60W PV module. Due to the non-linear and time varying of PV characteristics, the generated power of the PV is continually varying with atmospheric conditions like temperature and irradiation, the MPPT technology is very important to chase maximum power point (MPP) on the P<em>ــ</em>V curve to obtain maximum output power from PV array. This study focuses on two common types algorithms of MPPT, namely perturb and observe (P&amp;O) and incremental conductance (INC). A DC--DC boost converter is implemented to regulate the voltage output from the PV array's and for the application of MPPT algorithm.</p>

In photovoltaic (PV) systems, the maximum power point trackers are very important for increasing their efficiency. Maximum power can be achieved by using different methods such as P&O, INC so that the PV module can operate under different weather conditions and still produces maximum output power. In this paper, a smart method is presented for a maximum power point tracking (MPPT) based on a fuzzy logic control (FLC). The photovoltaic system consists of a solar panel type MXS 60W, DC-DC boost converter, FLC (MPP) tracker and resistive load are analyzed and simulated in MATLAB program. The output voltage of the solar panel is increased by the boost converter and it depends upon the duty cycle (D) of the MOSFET of the boost converter. Any change in the duty cycle is performed through sensing the output power of the solar panel. The controller tracks the maximum power of a solar panel by adjusting the duty cycle of the DC-DC converter switch. The simulation results show that the FLC controller can track the Maximum Power Point in a shorter time with less power oscillation around the MPP as compared to the most widely conventional method known as perturb and observe (P&O). Both techniques have been modeled and simulated in (MATLAB/Simulink).