Open AccessEfficient maximum power point tracking using model predictive control for photovoltaic systems under dynamic weather condition
Author(s) -
Mosa Mostafa,
Shadmand Mohammad B.,
Balog Robert S.,
Abu Rub Haitham
Publication year - 2017
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
ISSN - 1752-1424
DOI - 10.1049/iet-rpg.2017.0018
Subject(s) - maximum power point tracking , control theory (sociology) , photovoltaic system , maximum power principle , controller (irrigation) , model predictive control , computer science , power optimizer , power (physics) , boost converter , engineering , control (management) , voltage , agronomy , physics , inverter , artificial intelligence , quantum mechanics , electrical engineering , biology
This study presents a high‐efficient maximum power point tracking (MPPT) of photovoltaic (PV) systems by means of model‐predictive control (MPC) techniques that is applied to a high‐gain DC–DC converter. The high variability and stochastic nature of solar energy requires that the MPPT control continuously adjust the power converter operating point in order to track the changing maximum power point; a concept well known in the literature. The main contribution of this study is a model‐predictive‐based controller with a fixed step that is combined with the traditional incremental conductance (INC) method. This technique improves the speed at which the controller can track rapid changes in solar insolation and results in an increase in the overall efficiency of the PV system. The controller speeds up convergence since MPC predicts error before the switching signal is applied to the high‐gain multilevel DC–DC converter and thus is able to choose the next switch event to minimise error between the commanded and actual converter operation. Comparing the proposed technique to the conventional INC method shows substantial improvement in MPPT effectiveness and PV system performance. The performance of the proposed MPC‐MPPT is analysed and validated experimentally.