چکیده :
A number of different analytical and numerical methods have previously been proposed to estimate solar
cell/module parameters. For a single diode model, the parameters include the photocurrent, the saturation
current, the parasitic series and shunt resistances, and the ideality factor. Among the proposed optimization
techniques, the differential evolution (DE) based method besides its computational advantage,
provides better accuracy compared to other methods. However, it is not an easy task to determine the
control parameters for the DE algorithm. This paper presents an improved adaptive DE (IADE) based optimization
technique. New formulas for the scaling factor and crossover rate are proposed. The proposed
IADE algorithm uses a simple structure based on the feedback of fitness value in the evolutionary process.
It provides better performance for estimation of the solar cell and module parameter values than other
popular optimization methods such as particle swarm optimization, genetic algorithm, conventional
DE, simulated annealing (SA), and a recently proposed analytical method. Comparisons with existing
methods for solar cell and module parameter estimation are presented using both synthetic and experimental
data under various environmental conditions. The proposed scheme offers higher accuracy, and
also eliminates the need for users to manually tune the control parameters of DE algorithm
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