Open AccessA novel global MPP tracking scheme based on shading pattern identification using artificial neural networks for photovoltaic power generation during partial shaded condition
Author(s) -
Kota Venkata Reddy,
Bhukya Muralidhar Nayak
Publication year - 2019
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2018.5142
Subject(s) - maximum power point tracking , photovoltaic system , shading , maximum power principle , controller (irrigation) , computer science , control theory (sociology) , particle swarm optimization , artificial neural network , voltage , artificial intelligence , engineering , algorithm , control (management) , electrical engineering , computer graphics (images) , biology , agronomy , inverter
Efficiency of the photovoltaic (PV) power generating system is affected during partial shaded condition (PSC). The power‐voltage characteristic of PV system exhibits multiple peaks during PSC. It is the task of maximum power point tracking (MPPT) controller to track global maximum power point (GMPP). Conventional MPPT schemes stop at first peak and fail to accomplish GMPP during PSC. Metaheuristic algorithms developed to track GMPP are complex, costly and require much time to track GMPP. Hence, this study put forwards a novel GMPPT scheme for effective tracking based on shading pattern identification using artificial neural network (ANN). In this scheme, ANN is used to estimate the shading pattern on PV panels and a two‐dimensional lookup table supplies the MPP voltage corresponding to the shading pattern. By maintaining this voltage across PV panel, maximum power is extracted. The proposed scheme is compared with the existing artificial bee colony and particle swarm optimisation algorithms under different shading configurations to verify their performance under PSC. It is observed that the proposed scheme extracts maximum power effectively under various partial shading conditions. The proposed scheme is implemented in field‐programmable gate array (FPGA) controller and the experimental results prove effectiveness of the proposed scheme.