A fractional-order model of a photovoltaic (PV) system is proposed in this paper. The system identification approach is used to develop an effective dynamical model for a PV system. A real PV module and a boost converter are used to gather the experimental input–output data for the identification process. The black box modeling is applied to the system identification to obtain the transfer function, without the requirement to perform any mathematical analysis. The identification process is based on the least squares criteria for minimizing model output error, and the Levenberg–Marquardt algorithm is used for optimizing the model parameters. The proposed fractional-order model (FOM) is investigated using MATLAB to study the frequency response and the model's stability. Simulation results verify the effectiveness and advantages of the FOM in comparison to identified integer-order model.
A fractional-order model of a photovoltaic (PV) system is proposed in this paper. The system identification method is used to construct an accurate dynamical model for a PV system, a real PV module and boost converter are used to collect experimentally input-output data for the identification process. A black box modeling is considered for system identification to obtain a transfer function, without needing to make mathematical analysis. the input-output data which is measured is fitted by the least-square curve fitting method, and the parameters of the curve fitting are optimized by the Levenberg-Marquardt algorithm. the proposed fractional-order model is employed with the MATLAB and Simulink software to obtain a fractional order PID controller, which is used to extract maximum power from the PV system.
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