A Study on Maximum Power Point Tracking (MPPT) Converters for Solar Energy Harvesting

Abstract

This research paper presents a brief comparative analysis review paper on Maximum Power Point Tracking (MPPT) converters utilized in the process of solar energy harvesting. The primary focus of this paper is on conventional MPPT converters such as buck, boost, and buck-boost converters. Applications of MPPT controllers such as Perturb and Observe (P&O), Incremental Conductance (INC), Artificial Neural Network (ANN), Fuzzy Logic Control (FLC), Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) have also been analyzed in this review paper. The controllers or algorithms nowadays are rapidly evolving as more new algorithms are developed and applied to MPPT converters. Thus, the benefits and drawbacks of the MPPT converters and controllers have been properly discussed and analyzed based on tracking efficiency, convergence speeds, and steady-state oscillation. Appropriate research reviews are used to properly study and analyze the findings. ABC has been deemed as a good MPPT controller as ABC outperforms the other MPPT controllers in terms of tracking efficiency, convergence speeds, and steady-state oscillation.  This research review is considered to be a guidance resource for new researchers working in the MPPT research.