A MISO Nonlinear Model of Photovoltaic Panel Based on System Identification

The growth in the use of renewable energy sources has made photovoltaic (PV) systems increasingly popular. PV systems are mostly composed of a PV panel to generate dc power and an inverter to convert dc to ac power. Many events may occur on the PV modules, resulting in possible faults and loss of generated power, due to their exposure to environmental conditions. Thus, modeling the PV panel allows to determine the estimation of the output power of the PV system. In this context, this paper presents a nonlinear model based on the black-box modeling of System Identification. In addition, Hammerstein-Wiener (HW) model structure was selected due to its simplicity of representing the nonlinearity of the PV panel. The irradiance and temperature on the PV panel represent the input signals for the proposed model. The current and voltage are measured to calculate the output power, resulting in a Multi Input Single Output (MISO) model. The proposed HW model is compared with the classical Single Diode Model and the results show that the proposed model is more accurate.