Open AccessROAC: Recursive optimization of Ant colony assisted perturb and observe for a photo voltaic resonant boost converter
Author(s) -
R Selvakumar,
M. Sujatha,
S Palanikumar
Publication year - 2017
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i1.3.10661
Subject(s) - ant colony optimization algorithms , maximum power point tracking , photovoltaic system , maximum power principle , control theory (sociology) , power (physics) , computer science , solar irradiance , inverter , engineering , algorithm , voltage , electrical engineering , physics , artificial intelligence , control (management) , quantum mechanics , atmospheric sciences
This paper introduces a new Hybrid MPPT algorithm by combining new Ant Colony Optimization (ACO) and Perturb & Observe (P&O) method. The maximum power from a solar panel is extracted from all conditions like solar irradiance variation, temperature variation and partial shading conditions. Ant Colony Optimization (ACO) method tracks maximum power from panel under all variations and Perturb & Observe algorithm used in final stage to achieve faster MPP tracking. This proposed algorithm is implemented both in Simulink and hardware. A 5kWp grid connected solar photovoltaic power plant is designed and implemented for the 15 stage 31 level Cascaded Multilevel Inverter (CMLI) with the Selective harmonic elimination algorithm. From the analysis of results, it is found that the proposed hybrid MPPT provides higher MPP tracking performance in any weather conditions compared with other MPPT algorithms