Photovoltaic MPPT control and improvement strategies considering environmental factors: based on PID-type sliding mode control and improved grey wolf optimization

Abstract

Given the importance of promoting a greener and more sustainable future, it is crucial to promptly tackle and improve the issues surrounding carbon emissions and inefficiency linked to traditional energy sources. This study presents a new optimization method for PV systems. It combines an IGWO Algorithm with PID-type SMC to enhance the effectiveness of MPPT. Using IGWO, the optimal MPP voltage is determined even in the face of changing environmental conditions. Afterwards, the PID-type SMC adjusts the actual output voltage of the Boost based on the expected voltage to generate the required duty cycle. The integrated approach considers the natural fluctuations in PV systems, where changes in the environment can greatly affect the maximum power point. An in-depth evaluation was conducted using simulation software based on MATLAB, and a practical testing platform was built accordingly. The simulation and experimental results in real-world scenarios show that the new MPPT strategy has excellent overall performance and can quickly determine and track the voltage value for MPP compared to established algorithms. This study lays the groundwork for applying IGWO and new SMC control theories in the field of renewable energy generation. It also contributes to the development of MPPT technology, considering the challenges posed by the controlled environment.