Abstract :
Due to its ability to handle nonlinear functions regardless of the derivatives information, evolutionary algorithms (EA) are envisaged
to be very effective for extracting parameter of photovoltaic (PV) cell. This paper presents critical evaluation of the parameters extraction
of two diode PV model using three EA methods, namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential
Evolution (DE). For DE, two variations are proposed: (1) boundary based differential evolution (B-DE) and (2) penalty based differential
evolution (P-DE). The performance of each method is evaluated based on several factors: accuracy and consistency of solution; speed
of convergence; computational efficiency and the required number of control parameters. Comparisons are carried out using synthetic
data and are validated by six PV modules of different types (multi-crystalline, mono-crystalline, and thin-film) from various manufacturers.
Information derived from these critical evaluations can be useful to determine the best computational method to build an efficient
and accurate PV system simulator.
2011 Elsevier Ltd. All rights reserved.
