Utilizing two models of the converter to eliminate the partial shading on solar panel: a comparative scheme between classical offline and advanced online control strategies

In recent times, the single-stage photovoltaic (PV) system has gained notable attention due to its capacity to reduce installation costs and minimize overall energy losses. This paper introduces a comparative approach aimed at mitigating the impact of partial shading (PS) on PV surfaces by employing two modeling circuits of the DC–DC buck converter. The study begins by deriving the s-domain transfer function of the converter through data fitting techniques. It proceeds with a comprehensive assessment of the linear time-invariant (LTI) and nonlinear circuit (NLC) models, exploring their behavior under diverse weather conditions. Subsequently, two control strategies are employed to activate these converters: (1) model predictive control (MPC), representing advanced control methods, and (2) proportional–integral–derivative (PID) control, a robust and classical control technique. To conduct the simulations, MATLAB Simulink is utilized, with the primary objectives of regulating the DC output voltage for both converter models (NLC and LTI) and accurately tracking the maximum power point (MPP) using both MPC and PID controllers. The results obtained reveal that in the case of the LTI model, when triggered by MPC, the converter exhibits efficient regulation of the output voltage and precise MPP tracking even under varying transient conditions, as demonstrated by the trajectory. However, when controlling the NLC model with a PID controller, higher oscillations are observed due to inherent system nonlinearity and the effects of IGBT triggering events. This research provides valuable insights into the performance of single-stage PV systems under partial shading scenarios and highlights the effectiveness of advanced control techniques, such as MPC, in improving system stability and MPP tracking. Additionally, it underscores the challenges posed by nonlinearity in the NLC model when employing PID control.