Comparative study of meta-heuristics based approaches for maximum power point tracking for PV systems

• Published in: 2016 IEEE 7th Power India International Conference (PIICON) pp. 1 - 6
• Main Authors: Joshi, Puneet, Arora, Sudha
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-11-2016
• Subjects: C# languages; Gravitational Search Algorithm (GSA); MPPT; Particle Swarm Optimization (PSO); Photovoltaic (PV); PSO-GSA
• DOI: 10.1109/POWERI.2016.8077318

Solar energy has seen an exponential advancement in the past decade. It has gained significant attention as an alternate energy and has proved to be effective for both distributed and stand-alone applications. The non-linear behavior of the PV cells and the repositioning of the Maximum Power Point (MPP) with changing irradiances and temperate makes the tracking even more complicated. As a result, Maximum Power Point Tracking (MPPT) has turned out to be an obligatory part of PV generation systems. In recent years, a great heap of inquiry for new meta-heuristics based MPPT methods have been investigated and advised. In this paper, the focal point has been on such most popular and widely accepted MPPT schemes. MATLAB/SIMULINK has been utilized for performance appraisal. It is envisaged that this inspection work will help as a base for the PV mavens to keep au fait with the state-of-the-art involvements in the expanse, as well for a neophyte to get started on MPPT.