Open AccessAnalysis, Modeling, and Simulation of Adaptive Control Based on Dynamic Conductance Estimation of Photovoltaic Generator Interfaced Current-Mode Buck Converter
Author(s) -
Yakov Malinkovich,
Simon Lineykin,
Moshe Sitbon
Publication year - 2022
Publication title -
elektronika ir elektrotechnika
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.224
H-Index - 26
eISSN - 2029-5731
pISSN - 1392-1215
DOI - 10.5755/j02.eie.29205
Subject(s) - control theory (sociology) , controller (irrigation) , buck converter , photovoltaic system , operating point , maximum power point tracking , generator (circuit theory) , computer science , open loop controller , voltage , engineering , control engineering , electronic engineering , power (physics) , control (management) , electrical engineering , closed loop , agronomy , biology , physics , quantum mechanics , artificial intelligence , inverter
In this paper, a novel adaptive control method is presented, aimed at robustifying the terminal voltage of the photovoltaic generator, interfaced by the current-mode-controlled buck DC-DC converter load, and based on conductance estimation. The photovoltaic generator, which is integrated into the buck converter and a battery storage unit, is continuously affected by the operating point of the system and environmental variables, thus presenting a nonlinear behavior. Furthermore, the development of small-signal equations reveals a potentially unstable condition when the system is used as a micro-grid with a battery storage unit. This study shows that when the nonlinear behavior of the photovoltaic generator is combined with a typical nominal controller, designed for a single nominal operating point and due to the possibility of an unstable condition, it forces the controller to operate mostly outside the nominal operating point. These conditions result in significantly varied closed-loop performance. In contrast, an almost perfect loop gain performance can be achieved when implementing an adaptive controller based on an online conductance estimation method. Applying estimator results and injecting its value in real-time into the inverse-based plant controller results in an adaptive controller. Therefore, the closed-loop performance of the system integrated with an adaptive controller achieves an almost nominal response throughout the operating range.