Research on Parameter Identification of Photovoltaic Array Based on Measured Data

The accuracy of PV array model is very important for grid connected operation and scheduling of large scale PV system. Based on the measured data of a PV power station, the hybrid artificial fish swarm and frog leaping algorithm is adopted to identify the unknown parameters in the mechanism model of PV array. The hybrid algorithm combines the advantages of the fast convergence of artificial fish swarm algorithm (AFSA) and the high accuracy of local search of shuffled frog leaping algorithm (SFLA). The identification results of hybrid algorithm and the results of individual identification of AFSA and SFLA are compared and analyzed which proves that the hybrid algorithm has the superiority and effectiveness of the two algorithms.