@inproceedings{b856701764454b368f16d69f79932b0a,
title = "Sensitivity analysis to model parameter errors of MPPT by model predictive control for photovoltaic applications",
abstract = "Due to variability of solar energy resources, maximum power point tracking (MPPT) of photovoltaic (PV) is required to ensure continuous operation at the maximum power point (MPP) and maximize the energy harvest. This paper presents a digital model predictive control technique to employ the MPPT for flyback converter for photovoltaic applications. The MPP operating point is determined by using perturb and observe (P&O) technique. The proposed two-steps predictive model based MPPT presents significant advantages in dynamic response and power ripple at steady state. A characteristic of MPC is the use of system models for selecting optimal actuations, thus evaluating the effect of model parameter mismatch on control effectiveness is of interest. In this paper the load model is eliminated from the proposed MPC formulation by using an observer based technique. The sensitivity analysis results indicate a more robust controller to uncertainty and disturbances in the resistive load.",
keywords = "Load modeling, Mathematical model, Maximum power point trackers, Power electronics, Predictive control, Predictive models, Switches",
author = "Morcos Metry and Shadmand, {Mohammad B.} and Balog, {Robert S.} and Rub, {Haitham Abu}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 1st Workshop on Smart Grid and Renewable Energy, SGRE 2015 ; Conference date: 22-03-2015 Through 23-03-2015",
year = "2015",
month = aug,
day = "17",
doi = "10.1109/SGRE.2015.7208736",
language = "English",
series = "2015 1st Workshop on Smart Grid and Renewable Energy, SGRE 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2015 1st Workshop on Smart Grid and Renewable Energy, SGRE 2015",
address = "United States",
}