Improving Performance of Photovoltaic Solar Pumps Using PSO-Based Maximum Power Point Tracking

Abstract

This research project aims to enhance the efficiency and performance of photovoltaic (PV) solar pumps through the implementation of a Particle Swarm optimization (PSO)-based Maximum Power Point Tracking (MPPT) technique. The primary objective of this study is to design and model the Cuk converter for application in a PV water pump system, integrating the PSO-based MPPT technique to achieve optimal power extraction from the PV array. The MPPT algorithm, based on the PSO method, was developed and thoroughly validated through comprehensive simulations conducted in MATLAB/Simulink. Key highlights of the project include the achievement of over 80% accuracy for the solar module combined with a Brushless DC (BLDC) water pump, while effectively increasing the pumping speed by more than 50%. Through the incorporation of the PSO-based MPPT strategy, the system demonstrates superior power extraction and transfer capabilities, ensuring the maximum utilization of PV energy for water pumping operations. This research contributes to the advancement of sustainable energy solutions by enhancing the operational efficiency of PV water pumps. The proposed PSO-based MPPT technique, integrated with the Cuk converter, offers an innovative and effective approach to harnessing solar energy for water-pumping applications. The findings of this study provide valuable insights for researchers and practitioners working towards the integration of renewable energy systems in various applications