PV module parameters extraction with maximum power point estimation based on flower pollination algorithm

Modeling of photovoltaic (PV) module remains as an important issue for many applications like monitoring or fault detection. Hence, many models have been proposed in literature, the most popular ones are the single and double diode models. Each model have unknown parameters to be identified. In this paper, a parameters extraction for both single and double diode models by using flower pollination algorithm is proposed. This algorithm is based on flower pollination for optimal reproduction of the plants species and can be considered as an optimization technique. Experimental validation was carried out by comparing the obtained results with real measurements data. In order to give usefulness, the extracted PV module parameters values are incorporated to estimate the maximum power point (MPP) and compared it with the MPP obtained from real data of grid connected photovoltaic system (GCPVS).