A comparative study of MPPT methods for PV array under partial shading condition in MATLAB /Simulink

Photovoltaic solar power is considered as the most important renewable energy sources which uses solar radiation to generate electricity. The main aim remains to get the maximum power from the photovoltaic (PV) system at different weather cases. The efficiency of the PV array is affected by shading conditions as in partially cloudy, neighboring buildings and towers, and trees. At partially shaded cases characteristics of PV array become more complex, multiple peaks appear on the PV characteristics curve then, it becomes difficult to track the maximum power point this is lead to significant power losses. To solve this problem Bypass diode is connected with the PV arrays which is provide an alternative electrical path for the current to flow through the diode as it can not flow through the shaded cell. However, those bypassing diodes causing loss in power due to the forward voltage drop for those diodes high. To overcome this drawback, the bypass diodes are replaced by Smart bypass, which has a low forward voltage drop. Maximum power point tracking (MPPT) is a technique employed with photovoltaic (PV) application to increases the output power of the photovoltaic array by tracking the maximum power point (MPP), which depends on atmospheric conditions such as temperature and insolation. Several MPPT methods have been proposed. In this thesis work, four MPPT methods are used the Perturb and Observe (P&O) method, the Incremental Conductance (IC) method, neural network method and hybrid MPPT method, to make a comparison between them based on performance like percentage tracking efficiency, speed, and time response by using MATLAB /Simulink. So, it's easy for the researcher to choose the best way for practical application.