Open AccessMaximum Power Point Tracking using Grey Wolf Technique Under Fast-Changing Irradiance
Author(s) -
Rubi Debbarma*,
Champa Nandi
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.k7838.0991120
Subject(s) - maximum power point tracking , particle swarm optimization , matlab , control theory (sociology) , heuristic , tracking (education) , irradiance , power (physics) , point (geometry) , maximum power principle , computer science , swarm behaviour , photovoltaic system , mathematical optimization , algorithm , mathematics , control (management) , engineering , artificial intelligence , physics , psychology , pedagogy , geometry , quantum mechanics , inverter , electrical engineering , operating system
In this paper, maximum power point tracking (MPPT) using Grey wolf optimization (GWO) algorithm is presented using MATLAB/Simulink. As we know that meta-heuristic or nature-inspired algorithm has proven to be superior in performance compared to the conventional MPPT methods. Grey Wolf optimization algorithm is a meta-heuristic algorithm based on the hunting behaviour of grey wolves. The proposed system includes modelling of PV system under changing irradiance and the MPPT control is driven by GWO algorithm. Most of the conventional MPPTs are unable to track multiple peaks and also shows oscillations on the output side, for this reason proposed MPPT algorithm is used in this paper. For eliminating oscillations, this algorithm has proven to be better compared to perturb and observe (P&O) and particle swarm optimization (PSO). The results are compared in terms of output power.