Experimental analysis of genetic algorithms based MPPT for PV systems

This paper presents experimental analysis of Genetic Algorithms (GAs) based Maximum Power Point Tracking (MPPT) for photovoltaic (PV) systems. This method, presented by another paper [1], uses GAs to track the maximum power point (MPP) of PV panels. Comparison with the famous Perturb and Observe (P&O) and Incremental Conductance (Inc-Cond) are given, we tested stability (power oscillation) with real panels (Conergy PowerPlus 214P), to compare response time (rapidity) we used a PV emulator [2] so we can inject the same irradiance profile and see output PV power evolution. The response time, of P&O and Inc-Cond, and the PV power oscillation varies with the duty cycle increment step; with a small step, we get less power oscillation but this needs an important time response, we can improve system rapidity with a bigger duty increment step but important power oscillation will result. With GAs based MPPT we can get more stability with rapid response time. The results obtained show better stability and less oscillation around the MPP with the new method.