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Identification of photovoltaic arrays' maximum power extraction point via dynamic regressor extension and mixing
Author(s) -
Pyrkin Anton,
MancillaDavid Fernando,
Ortega Romeo,
Bobtsov Alexey,
Aranovskiy Stanislav
Publication year - 2017
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2768
Subject(s) - photovoltaic system , extension (predicate logic) , identification (biology) , mixing (physics) , extraction (chemistry) , point (geometry) , maximum power principle , power (physics) , computer science , control theory (sociology) , mathematics , engineering , electrical engineering , artificial intelligence , physics , geometry , chemistry , chromatography , botany , thermodynamics , control (management) , quantum mechanics , biology , programming language
Summary This paper deals with the problem of identification of photovoltaic arrays' maximum power extraction point—information that is encrypted in the current‐voltage characteristic equation. We propose a new parameterisation of the classical 5 parameter models of this function that, combined with the recently introduced identification technique of dynamic regressor extension and mixing, ensures a fast and accurate estimation of all unknown parameters. A concavity property of the current‐voltage characteristic equation is then exploited to directly identify the desired voltage operating point. Realistic numerical examples via computer simulations are presented to assess the performance of the proposed approach.