Comparison between conventional methods and GA approach for maximum power point tracking of shaded solar PV generators

The characteristics of a photovoltaic (PV) array are affected by temperature, solar insolation, and shading. In fact, under partially shaded conditions, the PV array characteristics get more complex with multiple maxima in the P–V and I–V characteristics. In this paper, a photovoltaic solar system composed of a solar panel under shade, connected to a DC/DC boost converter and controlled with different techniques, is studied and simulated under Matlab/Simpowersystem software.The study allowed us to conclude that the two common algorithms, the Perturb and Observe (P&O) and the Incremental of Conductance (IncCond), fail to extract the maximum power of the PV panel if the PV generator is partially shaded. So, in these conditions, these techniques fail to extract the global maximum; however, they only detect the first maximum encountered either local or global and regardless of the course. To resolve these problems, a technique based on Genetic Algorithm (GA) is studied and simulated under the same software.The results show that the GA method has succeeded to overcome these difficulties and reach the global MPP.

► We study and model a shaded photovoltaic generator (PVG). ► We simulate P&O and IncCond methods in the case of partially shaded PVG. ► Under different atmospheric changes, these techniques fail to track the Maximum Power Point (MPP). ► We simulate a non-conventional approach based on Genetic Algorithm (GA). ► The GA method succeeds to extract the MPP under the same atmospheric changes.