PARAMETER EXTRACTION OF SOLAR PHOTOVOLTAIC MODELS USING CROW SEARCH ALGORITHM

Maniraj Baskar and Peer Fathima Abdul Kareem

Keywords

Crow search algorithm (CSA), single diode model, double diode model, parameter extraction

Abstract

This paper deals with the application of a crow search algorithm (CSA), based on intelligent behaviour of crows for the parameter extraction of various solar photovoltaic (PV) models. Single diode and double diode models have five and seven unknown parameters, respectively. The problem of parameter extraction process is defined as nonlinear optimization problem. An inaccurate current–voltage (I-V) production in PV cell modelling leads to low efficiency. Hence, making an accurate PV cell model and analysis under different climatic conditions before experimental installation is mandatory. The different optimization techniques seen in literature dealing with the extraction of the parameters from different solar PV models have the inability to do extraction for finding the optimum value. Hence, the author has proposed a new optimization algorithm for extracting parameters for both models under different environmental conditions. The proposed CSA algorithm is found to be a good match between simulated and experimental results with effectiveness. Evaluation of the performance of proposed algorithm with various types of PV system such as monocrystalline, polycrystalline and amorphous crystalline modules was done. Finally, the results of proposed algorithm were compared with practical and other reported bio-inspired optimization techniques.

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