Abstract
In this work, cuckoo search optimization (CSO) and its variants improved CSO (ICSO) and modified CSO (MCSO) techniques are implemented to evaluate parameters of (I) Photovoltaic (PV) cell: single diode model and double diode model, and (II) PV module that consists of 36 series connected PV cells. ICSO algorithm uses adaptive step size coefficient for implementing the random walk based on Lévy flight mechanism. Whereas in MCSO, information interchange between top solutions is utilized to get the better uniformity and the rate of convergence. These algorithms are implemented in MATLAB/SIMULINK and results obtained are compared with experimental data. Parameter perturbation approach is proposed to establish validation of CSO, MCSO, and ICSO algorithms. Further, statistical analysis has been done to compare the reliability of algorithms with the state-of-the-art methods. Results show that ICSO is able to achieve improved accuracy and reliability in comparison with the existing methods, which includes CSO and MCSO.
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