Enhancing Photovoltaic System Performance with MPPT-PID Controller Using Particle Swarm and Tasmanian Devil Algorithms

In photovoltaic systems (PV), given the non-linear relationship between voltage and power, the implementation of a controlled power electronic converter is essential to achieve the desired voltage level. In this study, the boost converter is controlled by an MPPT-PID controller to obtain maximum power from the designed PV system. The PID (proportional-integral-derivative) controller parameters are determined by Particle Swarm Optimization (PSO) and Tasmanian Devil Optimization (TDO) algorithms. The objective function, Integrated Time Weighted Absolute Error (ITAE), is selected for the engineering problem. The system was applied to a series of tests within the MATLAB/Simulink environment, encompassing constant irradiance-fixed load, variable irradiance-fixed load, and constant irradiance-variable load conditions. A comparative analysis was subsequently performed. The performance of the scenarios was analyzed by peak value, overshoot ratio, rise time, and converter efficiency. The findings emphasize the important role of parameter optimization in enhancing energy efficiency and contribute to the current state of knowledge, leading to the development of more effective control strategies in solar energy systems.